performance testing of x-ray and gamma … testing of x-ray and gamma-ray detectors for imaging and...
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PERFORMANCE TESTING OF X-RAY AND GAMMA-RAY DETECTORS
FOR IMAGING AND SPECTROSCOPY
Richard Giordmaina
A dissertation submitted to the Physics Department at the University of Surrey in
partial fulfilment of the degree of Master in Physics.
Department of Physics
University of Surrey
April 2008
ii
ABSTRACT
Spectroscopic detection of X and gamma (γ) radiation is of great importance in medical and security
applications. Research was undertaken at the University of Surrey and the Dstl Fort Halstead
laboratories to identify the imaging and spectroscopic capability with both existing and novel radiation
detection technology. There is a real need for spectroscopic information to be provided by radiation
detectors to offer the possibility for material discrimination, providing essential benefits that come with
this knowledge. Testing of the imaging and spectroscopic detection capabilities took place mainly
using a Cadmium Zinc Telluride (CZT) detector array, and novel Silicon Photomultiplier (SPM)
detector technology.
An initial review explored the various detection technologies which are currently available, populating
a graphical model to illustrate how these link together. Preparation and characterisation of CZT
radiation detectors was conducted to explore how raw detector materials can be tested and made ready
for use, and research using these detectors continued throughout the year, involving many experiments
to characterise and measure the performance of radiation detection equipment.
A CZT detector array was characterised by measuring the uniformity and energy resolution using
radioactive calibration sources to identify the spectroscopic capability of the detector. This was
repeated after a hardware upgrade to higher quality CZT, showing a noticeable improvement. It was
found that the CZT has energy resolutions of 7.91 0.03% at 59.5keV and 4.00 0.02% at 122keV
(an increase with energy as expected). The spectroscopic performance was then tested using two
calibration sources to determine the linearity of the counts recorded with time and inverse square law
with distance. The efficiency was found to be 72 1% at 122keV, proving that most photons will be
detected at 140keV, an energy commonly used in medical imaging.
The CZT detector was then used as a pinhole imager of backscattered X-ray photons from a variety of
objects, and the resulting images were compared to those obtained with an Intensified Charged
Coupled Device (ICCD) detector. These demonstrated that backscatter X-ray images can be produced
with both detectors. Analysis of the acquired images showed that the larger pixels of the CZT detector
make a more sensitive and better quality imaging camera, although with coarser images than the ICCD.
The majority of the research placement explored the characterisation and spectroscopic capability of
Silicon Photomultiplier (SPM) detectors, a relatively new technology, which are marketed to be a
possible replacement for Photomultiplier Tubes (PMTs) in many detection applications. A model
exploring the expected efficiency and energy resolution when different single pixel SPM detectors
(1mm and 3mm pixel sizes) are coupled to different scintillator crystals was produced to identify if
spectroscopy is theoretically possible. It was found that in certain scintillator, γ-source and SPM
combinations, spectroscopy would be possible as there would be enough photons remaining after losses
for an energy resolution of less than 15% to be obtained. The SPMs were then tested by measuring the
spectra produced when different scintillator crystals (CdWO4, CsI(Tl), BGO and LYSO) were coupled
to the three different SPMs and irradiated with radioactive γ-sources (241
Am, 57
Co, 22
Na and 137
Cs).
Many results found were directly comparable to the results expected using the model. From the
various measurements, energy resolutions were achieved, including 11.78 0.02% at 662keV. The
practical use for SPM detectors as small, fast counting spectroscopic radiation detectors has been
shown to be possible from the results obtained.
iii
Acknowledgements
The author would like to take this opportunity to thank Dr Regan and Dr Sellin for organising the
placement which was a new, varied and exciting experience, which will no-doubt be of benefit in the
future. In addition, their assistance during the initial placement delays was greatly appreciated.
Dr Sellin has been very supportive as visiting tutor, by being available during the research year for
advice and help during my time away from the University.
The author would also like to show gratitude to his friends and colleagues at Dstl, especially Ian, Jane,
Dave and Paul for providing guidance and assistance, especially at the beginning of the new role.
Additionally thanks go to Paul for the use of portions of his existing programming code, which saved
're-inventing the wheel' in several cases, and for his help in checking through sections of new code.
Finally, the author would like to thank his friends and family, for their support, patience and
understanding during the research year and whilst writing this dissertation.
Author Declarations
Whilst preparing this dissertation, the author has not been registered for any other academic
qualifications, and this dissertation has only been submitted for the Master of Physics academic award.
iv
List of Abbreviations
A list of all the abbreviations used throughout this dissertation is included here.
Abbreviation Description
APD Avalanche Photodiode
BGO Bismuth Germinate
CCD Charge Coupled Device
CdWO4 Cadmium Tungstate
Cs Cesium
CsI(Tl) Cesium Iodide (Thallium activated)
CT Computerised Tomography
CZT Cadmium Zinc Telluride
DAQ Data Acquisition System
DGF Digital Gamma Finder
Dstl Defence Science and Technology Laboratory
ehp(s) Electron-hole pair(s)
et al. and others
etc. et cetera
eV Electron volt
FF Fill Factor
FNA Fast Neutron Activation
FWHM Full Width at Half Maximum
GAPD Geiger mode Avalanche Photodiode
GMS Graphical Modelling System
IC Integrated Circuit
ICCD Intensified Charged Coupled Device
IV Current-Voltage
LED Light Emitting Diode
LYSO Lutetium Yttrium Silicon Dioxide
MCP Micro Channel Plate
M.Phys. Master in Physics
MCA Multi Channel Analyser
MOD Ministry of Defence
NaI Sodium Iodide
NIST National Institute of Standards and Technology
NQR Nuclear Quadrupole Resonance
PAB Probability to initiate Avalanche Breakdown
PDE Photon Detection Efficiency
PFNA Pulsed Fast Neutron Activation
PMT Photomultiplier Tube
ROI Region of Interest
SCA Single Channel Analyser
SPES Single Photoelectron Spectrum
SPM Silicon Photomultiplier
SNR Signal to Noise Ratio
TNA Thermal Neutron Activation
UK United Kingdom
XCOM Attenuation Database
XIA X-ray Instrumentation Associates
v
List of Tables
A list of all the tables used in this dissertation is included here.
Table 2-1: Scintillator crystals and their key properties [12 (LYSO details from 13)]. ......................... 19
Table 3-1: Procured calibration source details. (*Used for CZT detector uniformity and energy
resolution experiments and were original laboratory sources.) ................................................... 47
Table 4-1: The results for the uniformity (after flat fielding) and energy resolution of the CZT detector
before and after the hardware upgrade. ...................................................................................... 56
Table 4-2: The uniformity of the ICCD detector for each source before and after applying the flat field
corrections. ................................................................................................................................ 56
Table 4-3: The effect of „flat fielding‟ on the CZT Gaussian peaks, for the upgraded detector. ............ 57
Table 4-4: A close match for the measured values to that expected from the model for energy resolution
measurements. ........................................................................................................................... 80
Table 4-5: The average measured energy resolutions (%). (Errors at the 95% confidence level). ....... 85
Table 5-1: The best obtainable spectroscopic energy resolutions (nearest %) for the two detectors at the
same energies. ........................................................................................................................... 96
Table 5-2: The best obtainable detection efficiencies (nearest %) for the two detectors at the same
energies. .................................................................................................................................... 96
Table 6-1: Resistivity values and results from the conducting foam experiment. ............................... 106
vi
List of Figures
A list of all the figures in this dissertation is included here.
Figure 1-1: The summed attenuation in two regions for various materials over 2cm. ............................. 5
Figure 2-1: The electromagnetic spectrum (left) [4] and a diagram of an X-ray tube (right) [5]. ............ 6
Figure 2-2: A typical X-ray spectrum showing the characteristic peaks of the target material and the
Bremsstrahlung spectrum which accounts for most of the energy [4]. .......................................... 7
Figure 2-3: The energy level transitions in an atom. .............................................................................. 7
Figure 2-4: The main photon interaction mechanisms in matter varying with energy [6]. ...................... 9
Figure 2-5: Possible photon interactions in a detector (left) [6] and the Compton scattering of an
electron (right) [4]. ...................................................................................................................... 9
Figure 2-6: A typical X-ray transmission imaging arrangement. .......................................................... 12
Figure 2-7: An image of a brain tumour identified by 99
Tcm imaging [3]. ............................................ 13
Figure 2-8: Pinhole imaging providing sharper images for a smaller entrance aperture [8]. ................. 14
Figure 2-9: The operation of a semiconductor (CZT) radiation detector [6]. ........................................ 15
Figure 2-10: The drift velocity (Vd) as a function of applied electric field [6]. ..................................... 16
Figure 2-11: The stages in an ICCD detector [11]. .............................................................................. 18
Figure 2-12: The readout in a charged coupled device [6]. .................................................................. 18
Figure 2-13: The emission of scintillation crystals and the response of PMT devices [6]. .................... 19
Figure 2-14: The scintillation process from activated states [6]. .......................................................... 20
Figure 2-15: A photomultiplier tube with the amplification stages in the dynodes [3].......................... 21
Figure 2-16: A single pixel SPM (on a square base approximately 3x3cm) [20]. ................................. 22
Figure 2-17: A 1mm2 SPM pixel with many microcells on the top (left) [17] and the GAPDs in the
pixel are connected together to provide a photon proportional output [17] (right). ..................... 23
Figure 2-18: A graph containing the PDEs for 4V over bias for various SPM products [19]. ............... 23
Figure 2-19: The attenuation ratio I/I0 for the three detector materials explored for the project. ........... 25
Figure 2-20: The attenuation ratio over the energy range to be tested for the four scintillator crystals
used at 3mm thickness and the CZT detector at 5mm for direct comparison. ............................. 26
Figure 2-21: Operation of an MCA, an extension of many single channel analysers (SCAs) [6]. ......... 27
Figure 2-22: Typical pulse height spectra from γ-sources [6]. ............................................................. 28
Figure 2-23: An improved energy resolution is obtained with a thinner peak [6]. ................................ 29
Figure 2-24: The source emitting in 4π, where only a proportion of the activity is incident on the
detector at some distance (d) away............................................................................................. 30
Figure 3-1: The CZT detector array. ................................................................................................... 34
Figure 3-2: The experimental setup for the uniformity and energy resolution measurements. .............. 35
Figure 3-3: An image (based on detector area ~12.5cm2) from a γ-source illumination (left) and a
histogram from which the detector uniformity can be calculated (right). .................................... 35
vii
Figure 3-4: The Gaussian fit to the 241
Am peak (at 0.5m for 10 minutes). ............................................ 37
Figure 3-5: The ICCD detector (with a 2mm pinhole plate attached). .................................................. 38
Figure 3-6: The housing applied to the CZT detector providing a pinhole aperture at 10cm from the
centre of the detector. ................................................................................................................ 39
Figure 3-7: Top view of the arrangement for X-ray backscatter pinhole imaging................................. 39
Figure 3-8: An image created using a pinhole receiving backscattered X-rays (left) and the effect
chamfering has on the pinhole (right-above before and right-below after chamfering). .............. 39
Figure 3-9: The leakage obtained before the additional shielding (detector area ~7.9x10-3
m2). ............ 40
Figure 3-10: The optimum shielding configuration (left) and the more uniformly distributed counts
with this shielding. .................................................................................................................... 41
Figure 3-11: The experimental arrangement for separation experiment (CZT pinhole covered for a
background measurement). ........................................................................................................ 42
Figure 3-12: The positions of the tubes of salt and sugar, moving closer together in 1cm steps. .......... 42
Figure 3-13: The line of data extracted for ICCD images (left) and CZT images (right). ..................... 43
Figure 3-14: The transistor astable circuits produced to pulse an LED [30] (left) and a circuit diagram
for the 555 IC used to pulse an LED [32] (right). ....................................................................... 45
Figure 3-15: The oscillator circuits produced to pulse an LED using transistors and capacitors (left) and
the pre-packaged oscillator in the IC NE555 timer (right). ......................................................... 45
Figure 3-16: Experimental arrangement for the SPM pulse linearity experiment. ................................ 47
Figure 3-17: The pulse exploration and SPM spectroscopy experimental arrangement. ....................... 49
Figure 3-18: The Xia Pixie-4 system used to acquire the spectrum from the SPM detectors. ............... 50
Figure 3-19: A summary of the planned SPM testing, showing each SPM coupled to each scintillator
crystal activated by each γ-source, and the background measurements. ...................................... 50
Figure 3-20: The single photoelectron spectrum possible with an SPM [21 modified]. ........................ 51
Figure 4-1: The activity calculator with extrapolated activity over two months. .................................. 52
Figure 4-2: A screenshot from the shielding requirements spreadsheet for pinhole imaging. ............... 52
Figure 4-3: An image (left) and histogram (right) from the 241
Am illumination (over 30 minutes) ....... 53
Figure 4-4: A histogram with a fitted Gaussian for the 30 minute integration of 241
Am. ...................... 53
Figure 4-5: Flat field corrections applied to the 10 minute data for 241
Am (left) and 57
Co (right). ........ 54
Figure 4-6: The energy resolution per pixel for the 57
Co 30 minute integration (left) and for the 241
Am
30 minute integration (right). ..................................................................................................... 54
Figure 4-7: Energy spectra using 57
Co for 30 minutes (left) and
241Am for 30 minutes (right). ............. 55
Figure 4-8: Illumination of the 30 minute 57
Co (left) and 241
Am for 30 minutes (right) showing crystal
artefacts. .................................................................................................................................... 55
Figure 4-9: Flat fielded image with 57
Co (left) and 241
Am (right) showing the artefact has now gone.
Note the bright pixels (right) mask the true discontinuities image. ............................................. 55
Figure 4-10: The effect of flat fielding on the 30 minute flood illuminations for both sources 241
Am
(left) and 57
Co (right). ................................................................................................................ 57
Figure 4-11: A linear relationship successfully identified between increase in counts and integration
time, for two γ-sources. ............................................................................................................. 58
viii
Figure 4-12: The energy spectrum after just one second, showing 241
Am (59.5keV) and 57
Co source
(122 and 136keV) peaks. ........................................................................................................... 59
Figure 4-13: The effect of time and distance on the maximum number of counts received for two of the
integrations times tested using the CZT detector, showing the inverse square law. ..................... 60
Figure 4-14: The measured energy spectrum (left) and one just published for 57
Co (right) [38]. .......... 60
Figure 4-15: The efficiency of the CZT detector with increasing source distance. ............................... 61
Figure 4-16: A direct comparison for the same object (sugar) with the 4mm and 2mm pinholes (before
flat field corrections) from the ICCD detector. ........................................................................... 62
Figure 4-17: Flat fielded images of cotton in a case, using CZT (left) and ICCD (right). ..................... 62
Figure 4-18: Talc and aluminium powder on a plastic base (flat fielded) using CZT (left), ICCD
(middle), and before flat field corrections applied to the CZT (right). ........................................ 63
Figure 4-19: Images of the same object (but reversed) of the sections taken for analysis of the mean and
standard deviation (CZT left and ICCD right). ........................................................................... 64
Figure 4-20: A graphical representation of the data collected for the ratio of object to background each
image from both detectors. ........................................................................................................ 64
Figure 4-21: The number of counts from the average of 10 pixels in the CZT and ICCD detector for all
of the objects (error as the standard deviation). .......................................................................... 65
Figure 4-22: 1cm apart before flat field corrections (left) and after (right) for the CZT detector. ......... 66
Figure 4-23: 2-4cm (left to right) after flat field corrections for the CZT detector. .............................. 66
Figure 4-24: 1cm apart before flat field corrections (left) and after (right) for the ICCD detector. ....... 66
Figure 4-25: 2-4cm (left to right) after flat field corrections with 57
Co 30 minutes for the ICCD
detector. .................................................................................................................................... 66
Figure 4-26: The separation seen using the CZT (top) and ICCD (bottom) detectors over 5cm, where
the background for the ICCD is always higher than CZT. .......................................................... 67
Figure 4-27: The separation displayed as the change in normalised intensity for both detectors (error
bars as smallest unit taken from the trough height). ................................................................... 68
Figure 4-28: Results for the modelled energy resolutions for each crystal and SPM over the energy rage
to be tested. Clockwise from top left: CsI(Tl), BGO, LYSO and CdWO4. ................................. 69
Figure 4-29: The 1mm SPM pulses with no sources present seen in oscilloscope mode on the DAQ
(left) and expanded on another oscilloscope showing distinguishable dark photons (right). ........ 70
Figure 4-30: The dark counts in the 3mm 20μm SPM (top) and 3mm 35μm SPM (bottom), showing
noise photons not as clearly defined as the 1mm SPM. .............................................................. 70
Figure 4-31: 3mm 35µm SPM at 32V bias using the 555 IC timer (left) and 3mm 35µm 32V (right) for
an LED pulse where the SPM response (pink) to the LED pulse (blue) ...................................... 71
Figure 4-32: The onset times of all three SPMs using pulsed LED circuits to show that the pulses are
indeed produced in around 12ns. ............................................................................................... 71
Figure 4-33: A pulse caused by the pulsing of a red square LED, with black tape around the four
exposed sides on the 1mm SPM................................................................................................. 72
Figure 4-34: The SPM response to an LED pulse not fully recorded. .................................................. 72
Figure 4-35: The counting of the SPM to be at least 2x105Hz. ............................................................ 73
ix
Figure 4-36: The effect of resistance (and therefore LED power from the 555IC timer) on the size of
the SPM pulses produced. .......................................................................................................... 74
Figure 4-37: A scintillation pulse from the 3mm 20µm SPM (at 32V bias) using CsI(Tl) with the 22
Na
source. ....................................................................................................................................... 74
Figure 4-38: A comparison of the voltage pulses from scintillator crystals and sources using the 3mm
20μm SPM at 32V. .................................................................................................................... 75
Figure 4-39: The CdWO4 response to 22
Na on the 3mm 20μm SPM, the decay lasting much less than
the 20µs expected. ..................................................................................................................... 75
Figure 4-40: Comparing the response of the pulse preamplifier which cuts off the full pulse duration
(left) with the transimpedance amplifier (right). ......................................................................... 76
Figure 4-41: The effect of bias on the SNR for each SPM. .................................................................. 77
Figure 4-42: The energy spectrum using CsI(Tl) with the 22
Na source, providing an energy resolution
of 14% using the 3mm 35μm SPM. ........................................................................................... 78
Figure 4-43: The modelled energy resolutions (top) and measured average energy resolutions using
CsI(Tl) for each SPM (bottom). ................................................................................................. 79
Figure 4-44: An energy spectrum from the 3mm 20μm SPM using BGO and 137
Cs. ............................ 79
Figure 4-45: Two separate SPM linearity experiments; using the 3mm 20μm SPM with 137
Cs and
CsI(Tl), and the 3mm 35μm SPM with 22
Na and BGO. .............................................................. 80
Figure 4-46: A ln-ln plot of energy vs. energy resolution using BGO on the 3mm 35μm SPM. ........... 81
Figure 4-47: The average measured energy resolution results using BGO, LYSO and CsI(Tl)
scintillator crystals on the 3mm 20µm SPM. .............................................................................. 81
Figure 4-48: The average measured energy resolution results from several scintillator crystals coupled
to the 3mm 35µm SPM. ............................................................................................................. 82
Figure 4-49: The average measured energy resolution results for the CsI(Tl) scintillator crystal
compared to the modelled result for the 1mm SPM. ................................................................... 83
Figure 4-50: The measured energy resolutions with the 1mm SPM and the modelled results based on a
complete match in areas and at a 1/9 area match. ....................................................................... 83
Figure 4-51: A comparison of the measured energy resolutions for the three SPMs using all of the
sources on the CsI(Tl) crystal. ................................................................................................... 84
Figure 4-52: The extrapolated energy resolution (based on measured results) to 140keV for eight
scintillator and SPM combinations. ........................................................................................... 85
Figure 4-53: A 137
Cs Spectrum for two minutes on the 3mm 35μm SPM (left) and the effect seen when
241Am (further back at 5cm) from the crystal is added to the experiment (right). ........................ 86
Figure 4-54: The 122keV peak clearly to the right of the cursors showing the position around the
59.5keV peak. ........................................................................................................................... 87
Figure 4-55: Illumination with 57
Co (left) and both 241
Am and 57
Co (right) showing a broadening due to
the 59.5keV source from 33% to 52% at 150 counts. ................................................................. 87
Figure 4-56: Both high energy sources (511 and 662keV) when integrating for two minutes. .............. 88
Figure 4-57: The energy spectrum for 22
Na (511keV) without the 662keV source, the peak is missing
when integrating for two minutes............................................................................................... 88
x
Figure 4-58: BGO with 137
Cs for two minutes on the 3mm 35μm SPM. .............................................. 89
Figure 4-59: The addition of 22
Na to the 137
Cs source for two minutes. ................................................ 89
Figure 4-60: Integrating 22
Na and 137
Cs for 30 minutes better defines the spectrum. ........................... 89
Figure 4-61: The beta spectrum from LYSO taken for 30 minutes with no additional radioactive
sources using the 3mm 20μm SPM. ........................................................................................... 90
Figure 4-62: The linear increase of counts with integration time for the 3mm 35µm using 57
Co and
CsI(Tl). ..................................................................................................................................... 90
Figure 4-63: A comparison of the system efficiencies for each SPM using CsI(Tl). ............................ 91
Figure 5-1: An array of 16 3mm pixel SPMs [34]. .............................................................................. 97
Figure 6-1: The system start-up screen. ............................................................................................... 99
Figure 6-2: The Pixie4 Run Control menu......................................................................................... 100
Figure 6-3: The positions of the cursors to find the energy resolution. ............................................... 101
Figure 6-4: The cursors around the peak to provide the energy resolution and value of the peak. ...... 101
Figure 6-5: The attenuation jumpers for each channel of the acquisition system. ............................... 102
Figure 6-6: GMS with no object selected. ......................................................................................... 103
Figure 6-7: Identifying who takes Mathematics by moving the mouse over Mathematics. ................. 103
Figure 6-8: The „Weld View‟ of the Students Tutorial. ..................................................................... 104
Figure 6-9: A schematic of the conducting foam used [35]. ............................................................... 105
Figure 6-10: The experimental arrangement to find the CZT sample resistivity. ................................ 106
Figure 6-11: The change of source energy from 662keV (top) to 59.5keV (bottom). ......................... 108
xi
Contents
ABSTRACT ................................................................................................................................... ii
Acknowledgements ........................................................................................................................ iii
Author Declarations ....................................................................................................................... iii
List of Abbreviations....................................................................................................................... iv
List of Tables ................................................................................................................................... v
List of Figures ................................................................................................................................. vi
Contents .......................................................................................................................................... xi
Chapter 1 : Introduction and Background .............................................................................................. 1
1.1 Background ..................................................................................................................... 1
The Research Problem ............................................................................................................. 2
Detection Techniques Review .................................................................................................. 3
Material Modelling .................................................................................................................. 4
Chapter 2 : Theory ................................................................................................................................ 6
2.1 Production and Properties of X and Gamma-rays ............................................................. 6
X-rays ...................................................................................................................................... 6
Radioactive Sources ................................................................................................................. 8
Photon Interactions in Matter ................................................................................................... 8
Photon Attenuation ................................................................................................................ 11
2.2 Detection Technologies ................................................................................................. 12
X-ray Transmission Imaging .................................................................................................. 12
Medical Imaging .................................................................................................................... 12
Backscatter X-ray Imaging ..................................................................................................... 13
2.3 Radiation Detection Systems ......................................................................................... 14
Cadmium Zinc Telluride (CZT) Detectors .............................................................................. 14
Intensified Charge Coupled Device Detectors ........................................................................ 17
Scintillator Crystal Properties ................................................................................................. 18
The Silicon Photomultiplier (SPM) ........................................................................................ 21
2.4 Radiation Measurement and Spectroscopy ..................................................................... 26
What Happens to the Detected Radiation? .............................................................................. 26
Pulse Height Spectra .............................................................................................................. 27
Detector Calibration ............................................................................................................... 28
How is Spectroscopic Capability Determined? ....................................................................... 28
Error Analysis ........................................................................................................................ 32
xii
Chapter 3 : Experiments and Work Conducted .................................................................................... 33
3.1 Calculations and Modelling ........................................................................................... 33
Radioactive Source Calculator ............................................................................................... 33
CZT Shielding Requirements ................................................................................................. 33
3.2 CZT Experiments .......................................................................................................... 34
The CZT Detector .................................................................................................................. 34
Uniformity and Energy Resolution ......................................................................................... 34
CZT Spectroscopy ................................................................................................................. 37
CZT Efficiency Measurements ............................................................................................... 37
The ICCD Detector ................................................................................................................ 38
CZT and ICCD X-ray Backscatter Pinhole Imaging ............................................................... 38
CZT and ICCD Angular Resolution ....................................................................................... 42
3.3 SPM Experiments .......................................................................................................... 43
Scintillator and SPM Energy Resolution Model ..................................................................... 43
Light Emitting Diode (LED) testing ....................................................................................... 45
SPM Pulse Linearity .............................................................................................................. 46
SPM Pulse Observations ........................................................................................................ 47
SPM Spectroscopy ................................................................................................................. 49
SPM Detector Efficiency ....................................................................................................... 51
The Single Photo Electron Spectrum ...................................................................................... 51
Chapter 4 : Results and Analysis ......................................................................................................... 52
4.1 Modelling Results.......................................................................................................... 52
Radioactive Source Calculator ............................................................................................... 52
CZT Shielding Results ........................................................................................................... 52
4.2 CZT Experimentation Results ........................................................................................ 53
Uniformity and Energy Resolution ......................................................................................... 53
CZT Spectroscopy ................................................................................................................. 58
CZT Efficiency ...................................................................................................................... 61
CZT and ICCD X-ray Backscatter Imaging ............................................................................ 61
Angular Resolution ................................................................................................................ 65
4.3 Scintillator and SPM Experiments ................................................................................. 68
Scintillator and SPM Energy Resolution Model ..................................................................... 68
Scintillator and SPM: Preliminary Test Results ...................................................................... 70
xiii
LED Testing .......................................................................................................................... 70
SPM Pulse Linearity .............................................................................................................. 73
SPM Pulse Observations ........................................................................................................ 74
SPM Spectroscopy ................................................................................................................. 77
Observing Complex Spectra using SPMs ............................................................................... 86
SPM Detection Time .............................................................................................................. 90
SPM Efficiency Results ......................................................................................................... 91
Chapter 5 : Review, Conclusions and Further Work ............................................................................ 92
6.1 Conclusions ................................................................................................................... 92
6.2 Further Research ........................................................................................................... 96
References .......................................................................................................................................... 98
Chapter 6 : Appendices ....................................................................................................................... 99
APPENDIX I: OBTAINING A SPECTRUM ............................................................................ 99
APPENDIX II: GMS ............................................................................................................... 103
APPENDIX III: Initial Research: Introduction and CZT Resistivity ........................................ 105
APPENDIX IV: Experimental Equipment List ........................................................................ 107
1
Chapter 1 : Introduction and Background
This dissertation describes the research conducted in 2007 into current and novel spectroscopic and
imaging radiation detectors, which could have widespread applications.
1.1 Background
The research placement at the Defence Science and Technology Laboratory (Dstl) started in April.
Dstl is a trading fund of the Ministry of Defence (MOD), comprising over 3500 employees in several
locations across the UK providing “essential, impartial, high quality, timely advice on science and
technology issues”. Working for the “UK Armed Forces, the MOD or other government departments,
Dstl does not engage in work that can be done outside Government and therefore does not compete for
business with Industry” [1]. Dstl is divided into 14 departments (including Electronics, Biomedical
Sciences and Physical Sciences) and teams [1]. The research placement was undertaken in the Physical
Detection team of the Energetics Department. The broad aims of the team are to investigate, develop
and refine the sensors used in non-invasive detection. Technologies using X-rays, neutrons and nuclear
quadrupole resonance are some of those of interest.
There is a vital need to detect materials non-invasively, and an obvious example of this is aviation
security which has the requirement for rapid threat detection, due to a high volume of items.
Frequently, imaging using transmitted X-rays is performed, which relies upon the attenuation of
photons due to different absorption in different materials to produce an image. When materials
overlap, differentiation is more difficult as a thick amount of one material could be similar to a thinner
amount of another [2]. A key question is „could detection systems provide any more information?‟
For example, if spectroscopic information was obtained, there could be the possibility to identify
materials based on their elemental composition, rather than just an image to be interpreted.
The need for non-invasive detection in also vital for diagnostic medicine using passive γ-radiation
detectors to identify tumours in Positron Emission Technology (PET) and Single Photon Emission
Computerised Tomography (SPECT), where it is not always required to operate on a person to
diagnose certain tumours. By inducing a γ-emitter which is taken up by a tumour, it is possible to build
2
up a picture of the inner body from the outside. The energy range of the diagnostic medicine includes
140keV and 511keV (higher for some radiological treatments).
The possibility for improved detectors could have important benefits including rapid detection (to
reduce exposure time and dose required) and imaging in medical and threat detection applications.
The placement has explored three strands of detection:
active transmission X-ray modelling to determine how well metals and organics can be
separated;
active backscatter X-ray imaging to identify imaging when there is only access to one side of
an object;
passive γ-ray spectroscopy and detector characterisation.
The Research Problem
The research has been driven by the requirement to improve the current sensors for radiation detection
measurements, by exploring the characteristics of new detector materials and their ability to provide
spectroscopy. There is the potential to improve the information provided by detection systems.
Detailed detector characterisation was conducted by:
identifying the detector performance of a CZT detector array (before and after a hardware
upgrade), in terms of the uniformity (and comparing this to existing imaging technology using
an ICCD detector) and spectroscopic energy resolution to determine the level of peak
separation possible;
exploring the detection efficiency of the CZT detector using single and multiple γ-sources (to
include linearity of count rate over integration time and confirming the inverse square law
with increasing distance from the detector);
demonstrating backscatter X-ray imaging through a pinhole using the CZT detector with a
specifically designed graded material housing, and comparing these images to ones taken with
existing technology (an ICCD detector);
3
characterisation of three novel single pixel Silicon Photomultipliers (SPMs) to identify
detection efficiency, proportionality of the light output and the noise of the detector to
establish the performance possible;
spectroscopic testing of the SPMs with several different scintillator crystals in combination
with a large energy range of γ-sources;
comparing the different detection systems tested in terms of detection efficiency, energy
resolution, portability and linearity of the detectors.
All of this research focuses on identifying the characteristics and capabilities of two main detector
systems detectors (CZT, and scintillators with SPMs) as spectroscopic imagers to quantify their current
characteristics and to determine the suitability of these in passive γ-ray detectors, active transmission or
active backscatter detectors. Should these new detector systems have superior qualities, they could
replace existing technology in many applications.
Detection Techniques Review
The need for the research was identified by conducting a review of current detection techniques used,
providing an understanding of the systems that currently exist, and their method of operation. This
included metal detectors, X-ray detection (such as transmission and backscatter), neutron-based
detectors (such as Thermal, Fast and Pulsed Fast Neutron Analysis (TNA, FNA, PFNA)), vapour
detection, millimetre wave radiation and Nuclear Quadrupole Resonance (NQR). Information was
found using journals, texts and the Internet (product manufacturer web pages) for current and relevant
information. Where a piece of equipment using the technique existed, it was explored for advantages
and disadvantages.
Using a graphical modelling system (GMS 4.2 produced by the Office of Naval Research) a model was
produced summarising this information based on equipment identified, showing graphically the
different detection techniques. The software allows a technique to be selected, to display equipment
available using the technique, or select an item to be detected (e.g. metals) to display methods to detect
this. The report and model were designed to give an understanding of the techniques available and
how the research over the placement would aid the area of detection by adding spectroscopic sensors.
4
Material Modelling
To create a complete picture of the three detection methods, X-ray transmission imaging was explored
to identify the level of material discrimination possible. The attenuation data of nine common
materials (aluminium, copper, iron, salt, iron, Perspex, cotton, water and sucrose) was investigated
using XCOM (an Internet based attenuation calculator). The ratio of X-ray intensities through to that
absorbed was calculated for a range of energies for a range of material thickness. This explored how
the X-ray attenuation in these materials varies with X-ray energy and material thickness over a 1-
140keV (every keV) range over a material thickness of 2mm up to 2cm thickness (every 2mm).
A pre-existing modelled X-ray spectrum was normalised for intensity at each energy, and was
multiplied into the material attenuation data in a spreadsheet to produce attenuation curves (or „banana
curves‟) for each material. Attenuation curves were made using data at specific attenuation energies;
80 and 140keV, and 90 and 120keV. Then by dividing the 140keV energy range into sections (1-
85keV and 86-140keV) the sum of the attenuations for each thickness in each section was plotted. The
level of material discrimination possible is determined by how close the data points lie together.
Multi-energy attenuation was explored by further dividing the 140keV energy range into three equal
sections and sums and averages were taken of the attenuation in each material in each energy section,
for thicknesses of 0 to 2cm. To visualise three-dimensional plots, the values of summed attenuation
were read into a program, which showed organic materials, such as sucrose and water are very different
to inorganic materials such as iron and aluminium when explored at these energies.
By further dividing the energy 140keV range into 4, 5 and 6 energy ranges, multi-energy material
discrimination could be explored. However attenuation curves cannot be created for more than three
dimensions, so at the time of writing, various mathematical methods were being explored to analyse the
data collected, including Principle Component Analysis. The results of the mathematical analysis of
this should determine the ability for differentiation based on more than two energies used.
5
Figure 1-1: The summed attenuation in two regions for various materials over 2cm.
Figure 1-1 shows the attenuation curves for common materials and that there is clear separation
between metals and organic materials. The results of this study showed that material discrimination is
possible based on the attenuation of X-rays through a material. With this introductory work completed,
the next section of the project was to experiment with X-ray backscatter imaging and spectroscopy
using newly acquired experimental equipment.
6
Chapter 2 : Theory
This chapter contains relevant theory used over this research project.
2.1 Production and Properties of X and Gamma-rays
X-rays
X-rays were first discovered by Röntgen in 1895 [3], and applications for them has continued to
increase since their ability to penetrate matter was identified. They are used in medical X-rays and
Computerised Tomography (CT) scans, and industrial applications such as fault finding in structures.
X-rays are part of the high energy section of the continuous electromagnetic spectrum comprising radio
waves (wavelength (λ) ~ 108m) through to X-rays (λ~10
-10m) and γ-rays (λ~10
-15m).
Figure 2-1: The electromagnetic spectrum (left) [4] and a diagram of an X-ray tube (right) [5].
To produce X-rays, an electron beam can be produced by thermionic emission (heating off electrons)
from a cathode. By applying a high potential difference between the anode and cathode, an electric
field is produced (Equation 13) and the electrons are rapidly accelerated towards a target metal
(commonly tungsten). In the metal, electrons are excited into higher energy levels which promptly
decay, producing X-ray photons with energy directly proportional to the difference between energy
levels. This process takes place under vacuum to remove the air in the path of the electrons which
would otherwise cause a breakdown of the air inside the generator due to the high voltages applied (a
160kV potential produces 160keV photons).
7
X-rays are the result of atomic de-excitation, and are distinguished from γ-rays which are the result of
nuclear de-excitation. There are two types of X-ray. Bremsstrahlung radiation is a range of energies
caused by electrons scattering and changing velocity due to a nucleus, producing Bremsstrahlung
photons. These are seen as a range of energies in a typical X-ray spectrum (Figure 2-2).
Figure 2-2: A typical X-ray spectrum showing the characteristic peaks of the target material and
the Bremsstrahlung spectrum which accounts for most of the energy [4].
Characteristic X-rays are material specific (in terms of energy) X-rays, generated from transitions in
energy levels of the atom. By irradiating a material with high energy photons, enough energy can be
applied to remove an electron in the target material from its orbit, creating a vacancy. Depending on
which shell the electron falls from determines the energy of the resulting X-ray, and these can be
detected and analysed. The levels have historically been assigned letters starting with K for n=1.
Figure 2-3: The energy level transitions in an atom.
1. An electron decaying from the M to the L shell produces a Lα X-ray.
2. An electron decaying from the M to the K shell produces a Kβ X-ray.
3. An electron decaying from the L to the K shell produces a Kα X-ray.
A branch of spectroscopy explores the peaks corresponding to these transitions which appear in the
energy spectrum, which are specific to each element and can therefore be used to identify that element.
8
Radioactive Sources
Radiation comes in many forms, from charged alpha and beta particles to radiation comprised of
uncharged photons such as X-rays and γ-rays. In fact, the use of alpha particles helped physicists to
formulate a model of the atom in the famous „gold leaf experiment‟. X-rays can be artificially
produced and switched on and off as required, making them a useful probing tool. Radioactivity from
natural sources is a random process which has no such capability and is therefore stored in lead when
not required. Radiation detection can be active or passive. Active imaging requires additional
radiation to be supplied externally such as in transmission X-rays, whilst passive detection makes used
of existing radiation being emitted, such as in thermal imaging, which makes use of radiation already
emitted by a body. The decay constant (λ) in Equation 1 gives the probability of a decay per second,
which is inversely proportional to the half life (t1/2).
Equation 1
2/1
2ln
t
The activity (A) in Equation 2 is the number of decays per second in Becquerel (Bq) (where 1Bq is 1
decay per second). Activity decreases exponentially with time.
Equation 2 teAA 0
The half life (Equation 3) is a measure of the time it takes for half of a sample to decay, and this varies
widely for different sources. For the sources to be used in the experiments, it is required to determine
the change in source activity over the time of the project. The half life can be derived using the
exponentially decaying number N0 or activity A0 as they are simply related by the decay constant,
reducing to N0 /2 or A0/2.
Equation 3 2ln
2
1t
Photon Interactions in Matter
A photon is defined as a quantum of electromagnetic radiation (Equation 4) with an energy E (where h
is the Planck constant and υ is the frequency of the radiation [5]). There are three main photon
9
interactions in matter which are, in ascending order of energy, the Photoelectric effect, Compton
scattering and Pair production.
Equation 4 hc
hfE
The following interaction mechanisms have different probabilities of occurring (determined by the
cross section (σ)) which relate to the atomic number (Z) of the detector material seen in Figure 2-4.
The photoelectric effect and Compton scattering are most relevant to the energies explored.
Figure 2-4: The main photon interaction mechanisms in matter varying with energy [6].
Figure 2-5: Possible photon interactions in a detector (left) [6] and the Compton scattering of an
electron (right) [4].
10
Photoelectric Effect (or Photoelectric Absorption) – An incident photon surrenders its energy to eject
an inner electron from an atom, and a photoelectron with kinetic energy T is produced from the energy
of the photon (with energy hυ) once the energy required to eject the electron (the material‟s work
function Ф) is gained (Equation 5). The vacancy from the ejected electron is filled from the de-
excitation of a higher shell electron, with the energy released being an X-ray photon with energy equal
to the difference between the two levels.
Equation 5 Th
The likelihood of an interaction via the photoelectric effect (P) occurring is approximated in Equation
6, where Z is the atomic number (to the power of between 4 and 5) of the material and Eγ is the energy
of the incident photon. An interaction via this method is more likely for higher Z materials.
Equation 6 5.3
5.4~
PE
Z
Compton Scattering – An incident photon collides with a stationary electron in a material and the
photons scatters (now carrying a reduced energy 'E in Equation 7) with the remaining energy given to
the electron, causing it to carry a momentum (Figure 2-5 right). The photons which interact in the
detector by this method scatter at the different angles (θ) depositing only some of the energy. The
probability of scatter is a function of the incident energy, depositing more energy with a larger angle of
scatter. When only a portion of the photon energy stays inside the detector, energies less than the peak
are recorded. The range of energies appears as the Compton continuum in Figure 2-22.
Equation 7
2
0
'
)cos1(1cm
E
EE
Pair Production – An electron-positron pair is produced equally sharing the γ-ray energy in the
presence of the nuclear electric field. The positron loses energy in scattering events and then produces
two 511keV (almost) back-to-back photons following annihilation with a free electron. An initial
photon energy of at least 1.022MeV is therefore required for pair production to occur and is unlikely to
11
be seen in these measurements. Equation 8 shows how the energy of the incident photon is distributed
in pair production, where e
T and e
T are the kinetic energies of the electron and positron respectively,
and 2m0c2 is the rest mass energy of the electron and positron.
Equation 8 2
02 cmTTEee
When one annihilation photons leaves the detector, an escape peak appears 511keV less than the full
energy peak, or 1.022MeV less than the full energy peak if both annihilation photons escape (Figure
2-22).
Photon Attenuation
Attenuation is the reduction in number of photons in a beam due to passing though a material and all
materials (including air) attenuate photons. In Equation 9, Io is the initial number of photons, I is the
number remaining after attenuation through thickness (x), of the material. Colour coding based on the
attenuation detected is possible in some detector systems, separating metals into blue and organics into
orange for example, to help with identification of materials. The linear attenuation coefficient, µ, is a
measure of the attenuation in a medium, and it is constructed from the sum of the attenuations of the
three main photon interactions (Equation 10), where µ varies with photon energy. I / Io usefully
provides the ratio of photons through, regardless of the initial number of photons.
Equation 9 xeII 0
Equation 10 PPCSPE
12
2.2 Detection Technologies
X-ray Transmission Imaging
The technique of using X-rays to produce an image (a radiograph or just an X-ray) of an object by
transmitting X-rays through it is well understood. In this „standard‟ transmission imaging, such as a
bone X-ray, an X-ray generator is placed on one side of an object and a detector (commonly silver
halide film [7]) is placed on the opposite side of the object. The X-ray photons pass through the object
and due to attenuation of the photons in the beam, fewer pass through the object to reach the detector.
Film darkens where a photon strikes it, so bones for example, which are more dense (higher µ) than the
surrounding tissue will absorb more photons, so a film based detector on the other side will show bone
as whiter as fewer photons have struck the detector. The attenuation of the X-ray photons is the main
factor to determine the image obtained. The detection of these photons used in transmission imaging
has advanced dramatically since photographic film, to include charge coupled devices (CCDs) and
research is constantly conducted into finding new detector materials.
Figure 2-6: A typical X-ray transmission imaging arrangement.
Medical Imaging
Common medical imaging techniques include Positron Emission Tomography (PET) and Single
Photon Emission Computed Tomography (SPECT). In PET, a natural radionuclide is induced into the
body (such as carbon oxygen or nitrogen depending on the region required to be imaged) which decay
by emitting a positron. The positron travels a short distance (millimetres) losing energy within the
body. When enough energy has been lost in scattering events, the positron annihilates with a free
electron creating a pair of 511keV γ-ray photons approximately back-to-back, which are detected from
13
outside the body. Detecting the concentration of these photons allows an image to be constructed to
identify abnormalities.
In SPECT imaging, the collection of 140keV γ-ray photons emitted from inside the body is another
method to non-invasively image the internal body structure. Molybdenum decays by β- emission into
technetium (metastable or long-lived state), which then decays into technetium and a single 140keV γ-
ray photon (Equation 11). Choosing a pharmaceutical which is taken up by a specific organ allows
imaging of that region when the emitter is added to the solution. These photons can be detected after
collimation by scintillator crystals and a bank of photomultiplier tubes [3].
Equation 11 99
Mo 99
Tcm
99Tc + γ
Figure 2-7: An image of a brain tumour identified by 99
Tcm
imaging [3].
New sensors for the detection of these photons could make lower power, light and portable radiation
detectors a possibility, whilst retaining or improving the spectroscopic and imaging capability.
Backscatter X-ray Imaging
Compton scattered photons, cause a wide angle of scattered radiation, (determined from Equation 7)
can also be used to provide X-ray images. Backscatter (or single-sided) X-ray can be used when there
is only easy access to one side of an object, if for example the contents of a case are unknown and it
therefore may not be safe to move the item to view it in a traditional transmission X-ray system. This
can provide more information due to the increased photon flux. In this arrangement, a detector is
placed on the same side as the X-ray source, which records X-rays that have returned from the object.
The amount of energy from a backscattered X-ray is significantly less than the transmitted energy due
14
to the scattering. Higher Z materials will absorb more of the X-rays (Equation 6) whilst lower Z
materials will scatter more.
The pinhole effect is a well understood method for imaging light rays, commonly by exposing film.
The recorded image will be a reflection of the true one as seen in Figure 2-8. When beams of light are
passed through smaller apertures, sharper images are obtained but will take more time to form, as a
lower photon flux is incident on the film.
Figure 2-8: Pinhole imaging providing sharper images for a smaller entrance aperture [8].
When the diameter of the pinhole aperture is of the order of the wavelength of the radiation, diffraction
occurs, which is the spreading of waves from a source. Maximum diffraction occurs at the point when
the size of the aperture is of the same order as the wavelength of the radiation (light). The wavelengths
being used in this application are 7.8x10-12
m (Equation 4) and therefore it is determined that diffraction
will not need to be compensated for, when using a 2mm pinhole.
2.3 Radiation Detection Systems
Cadmium Zinc Telluride (CZT) Detectors
Radiation detectors are broadly divided into two categories; „charge-based‟ and „light-based‟. The
proportional counter, Geiger-Muller tube and semiconductor detectors are charge-based detectors
working on the principle of electron and holes charges; whilst light-based detectors such as a
photomultiplier tubes (PMTs) or photodiodes operate by detecting and amplifying optical photons
produced by light-emitting (scintillator) materials. CZT is a semiconductor based radiation detector
which has gained a lot of attention over the past few years due to its room temperature (without the
need for liquid nitrogen cooling to reduce the thermally created charges) detection of X- and γ-ray
Larger
aperture
leads to
blurred
image
15
photons. CZT is made from materials with high atomic numbers (Z) of 48, 30 and 52 respectively,
which have the ability to attenuate photons better than lower Z materials, and therefore detect an
interaction. Other materials which are used as direct semiconductor radiation detectors include silicon
(Z=14, suited for low energy photons) and germanium (Z=32, requires cooling) and research into new
materials for detecting radiation is constantly ongoing. CZT is more formally written as Cd1-xZnxTe
where x is the blending fraction of zinc telluride in cadmium [6]. A higher zinc concentration increases
the band gap of the material, allowing fewer thermally generated electrons to be detected as noise.
CZT resistivity values between 2.5x1010
Ωcm (4% zinc concentration) and 1.5x1011
Ωcm (20% zinc
concentration) are expected for CZT depending on the blending fraction of zinc in the sample [9]. The
value of resistivity is an important feature in the detection of radiation photons in the material, as a
higher resistivity implies a lower leakage current (as resistivity is inversely proportional to current)
providing a better quality material.
Incident radiation such as those from radioactive sources producing X- or γ-rays will deposit energy
creating electron-hole pairs (ehp) proportionally to the amount of incident energy (Figure 2-9). The
ehp pair creation energy (W) for a typical Cd0.9Zn0.1Te detector 4.64eV [10].
Figure 2-9: The operation of a semiconductor (CZT) radiation detector [6].
The capacitance (C) of the detector system is generally a constant, and includes the capacitance of the
detector and all leads (which should therefore be kept short). The voltage (V) detected is then directly
proportional to the charges produced by the radiation (Equation 12).
16
Equation 12 )(VC
QV
Inside a semiconductor detector, an applied voltage (V) between the two electrodes (at thickness d)
creates an electric field (Equation 13) often 105Vm
-1, causing the charges created by radiation to drift
with a velocity υ. The electrons migrate to the positive electrode (anode) and the holes to the negative
electrode (cathode). The drift velocity (for electrons υe and holes υh in Equation 14) is proportional to
the mobility, μ, of the electrons and holes (how easily they can move in the material), and the strength
of the electric field. The charges created in the detector move between 106 and 10
7ms
-1 to the
collection points at the electrodes of the detector material.
Equation 13 illustrates how a smaller distance between the anode and cathode will linearly increase the
electric field. CZT and SPM detectors can be made very thin providing a very large electric field
(105Vm
-1). However, thinner detectors will be less able to attenuate radiation photons causing a lower
detection efficiency. Figure 2-10 shows how the increase in the electric field causes the drift velocity
to increase in silicon (in semiconductor detectors the electric field is approximately 103Vcm
-1).
Equation 13 d
VE (Vm
-1)
Equation 14 Eee and Ehh (ms-1
)
Figure 2-10: The drift velocity (Vd) as a function of applied electric field [6].
17
From Ohm‟s Law (Equation 15) for a given voltage (V) and current (I) the resistance (R) of a detector
material can be found. By measuring the current at different voltages, a plot of current vs. voltage
provides resistance from the reciprocal of the gradient.
Equation 15 I
VR (Ω)
Resistivity ( ) is “a measure of a material‟s ability to oppose the flow of an electric current” and
increases with resistance (R) and cross sectional area, A [5]. It is commonly expressed in units of Ωcm
for CZT devices. An IV graph can be used to determine the sample‟s resistivity, where m in Equation
16 is the gradient of an IV graph is the reciprocal of resistance.
Equation 16 mL
A
L
RA (Ωm)
Intensified Charge Coupled Device Detectors
[11] describes the operation of Intensified Charge Coupled Device (ICCD) detectors. Figure 2-11
shows incident photons striking a photocathode, producing photoelectrons. A micro channel plate
(MCP) receives these photoelectrons and through the electric field, many more secondary electrons are
produced. These strike a fluorescent screen (such as phosphorus), producing optical light flashes
which are usually transferred by fibre optic cable. A CCD receives these photons which are converted
to charges, which are moved and read out row-by-row in the readout section (Figure 2-12).
18
Figure 2-11: The stages in an ICCD detector [11].
Figure 2-12: The readout in a charged coupled device [6].
This device is used for imaging only, as only counts and no energy information is recorded. Having a
pixellated input phosphor allows for imaging, as variations in intensity over the pixels can be displayed
graphically as an image.
Scintillator Crystal Properties
A scintillator is a light-based radiation detector which emits photons due to excitation from the incident
radiation, and qualities such as high linear light yield (the number of photons created per unit of energy
deposited (usually given in MeV)) and a short decay time are desired, such that fast and efficient
detection is possible. Scintillators, such as cesium and sodium iodide, are commonly coupled to a
19
Photomultiplier tube (PMT) increasing a low level of light photons into a much higher one. The PMT
turns the light produced from the scintillator into electrons in the photocathode by the photoelectric
effect, and the efficiency of this process is determined by the quantum efficiency of the photocathode.
There is a rapid increase the number of electrons using stages of dynodes [3]. According to [6], the
charge creation energy is 3.6eV for silicon and around 15-20 times that for scintillators, which only
convert 5-10% of energy to light. Scintillators are therefore intrinsically less efficient than
semiconductor detectors at stopping and detecting radiation photons. Radiation damage to scintillators
and other detectors is possible, as the lattice can be altered from the regular periodic structure,
compromising the ability to effectively detect and respond to radiation events [6].
Many materials scintillate in response to radiation. Scintillator materials are sub-divided into organic
(liquids and plastics) and inorganic materials, the latter being used for the project. Using Equation 4,
the energy of the optical photons from four scintillator crystals was determined.
Scintillator Light Yield /
MeV
Decay Time (μs) Peak λ (nm) Photon
Energy (eV)
BGO 9,000 0.3 480 2.57
CdWO4 13,000 20 520 2.19
LYSO 32,000 0.04 420 2.94
CsI(Tl) 52,000 1 565 2.38
Table 2-1: Scintillator crystals and their key properties [12 (LYSO details from 13)].
Based on these detector properties, these four scintillators were procured to provide a range of fast and
slow decay times, and high and low light yields to fully test the range of the SPM. Hygroscopic
crystals were not chosen to avoid degradation in crystal performance over the period of experiments.
Figure 2-13: The emission of scintillation crystals and the response of PMT devices [6].
20
Figure 2-13 shows the different responses of PMTs and scintillator crystals (Figure 2-18 shows the
SPM detector response). The best response of a detector would be where the peak detector response
matches the peak crystal emission, however, this is rarely the case for many crystal-detector
combinations due to the range of scintillator wavelengths. The emission spectrum of light emission
from scintillator crystals and the spectrum that detectors are sensitive to, allows detection of light from
scintillator crystals using detectors which are not perfectly matched (albeit with lower sensitivity).
Lutetium Yttrium Silicon Oxyorthosilicate (LYSO) is a scintillator crystal which was chosen for its
very fast decay time and high light yield. However, Lutetium is itself radioactive decaying by β-
emission, causing a level of background radiation in all measurements [14]. Using values from [14]
and scaling these values for the scintillator size used in experiments, the intrinsic activity of the
scintillator due to lutetium is about 13.5kBq, whilst the sources used at the energy of interest are much
more active at approximately 370kBq.
Activation of a scintillator using Thallium is common for sodium and cesium iodide which adds sites in
the scintillator that can produce optical photons in the forbidden band [6]. This increases the
probability that de-excitation of an optical state due to radiation will lead to optical photons (Figure
2-14). Having a fast, bright scintillator crystal which has a high attenuation of radiation photons over a
large energy range (detection efficiency) with a peak emission wavelength of the detector used, is the
ideal scintillator crystal. As this doesn't exit, a compromise of detection properties is usually made.
Figure 2-14: The scintillation process from activated states [6].
The light yield of a scintillator material arises as more charges are successfully created from the
incident radiation. By having a linear light output the amount of incident radiation can be determined
to deduce the energy of the incident radiation. The rise time varies in a scintillator crystal is related to
21
the mobility of the charges in the material [15, 16] where more prompt decay times are due to a better
charge mobility in the material.
[16] describes the process of fluorescence in a scintillator crystals. The absorption of radiation causes
electron-hole pairs to be created in the crystal at between two and seven times the band gap energy.
Electrons scatter to reduce in energy until they can excite luminescent centres which produce optical
photons. Due to the incident radiation, the scintillator emits photons in the visible part of the
electromagnetic spectrum (~400 – 700nm). The light produced from a scintillator can be recorded by a
photomultiplier, a photodiode, an avalanche photodiode and a new detector technology, the SPM.
The Silicon Photomultiplier (SPM)
The high gain, low noise and availability in large sizes are some of the reasons making the PMT system
a popular detector for scintillation light. There are however, several disadvantages to the technology;
fragility of the glass, large power requirements and sensitivity to magnetic fields [17]. For portable
radiation detectors, the large sizes of the PMTs can be a disadvantage.
Figure 2-15: A photomultiplier tube with the amplification stages in the dynodes [3].
Anode
Dynodes
Scintillator
Photocathode
Photomultiplier
tube
22
Photodiodes have been used as an alternative to PMTs to detect optical photons from scintillator
crystals, which enter the photodiode material and create electron-hole pairs. Photodiode gain is not as
large as the PMT, so a better alternative to the PMT is the avalanche photodiode (APD) which can
provide a much larger gain (several hundred is possible [6]) than a standard photodiode. A rapid
increase in the number of electrons is created due to further collisions and the multiplicative process
occurs due to the presence of a large electric field [6]. The gain is still a limiting factor and alternative
methods to readout from scintillator crystals are being explored.
Figure 2-16: A single pixel SPM (on a square base approximately 3x3cm) [20].
SPMs (Figure 2-16) combine the features of PMTs and APDs providing a high gain (~10
6) whilst
requiring a low operating voltage [18] making portability a possibility. Geiger mode Avalanche
Photodiodes are (GAPDs) are operated with a bias above the breakdown voltage such that only one
carrier is required for „breakdown‟. This breakdown is stopped or „quenched‟ by a large resistance in
series with the GAPDs. By connecting the output of thousands of GAPDs together in parallel, a photon
flux causes a current which is “directly proportional to the number of incident photons” [17]. Each
GAPD is a „microcell‟, any many are tightly packed such that there are thousands in a single pixel.
23
Figure 2-17: A 1mm2 SPM pixel with many microcells on the top (left) [17] and the GAPDs in the
pixel are connected together to provide a photon proportional output [17] (right).
When coupled to a scintillator crystal, the SPM detects the optical photons produced by radiation
incident on the scintillator. SPMs have intrinsic characteristics causing the loss of photons, including
the active area (the area able to detect a photon interaction), photon detection efficiency (PDE) and fill
factor (the ratio of the active area to the total area) which reduces the possible energy resolution as
fewer photons are present. The PDE (Equation 17) is the product of quantum efficiency (QE), the
probability an avalanche breakdown occurs (PAB), and the fill factor (FF). According to [19], the PDE
is “the probability that an incident photon produces a Geiger pulse from one of the microcells”, and
encompasses the probability of the photon initialising the avalanche breakdown and the quantum
efficiency of the detector.
Figure 2-18: A graph containing the PDEs for 4V over bias for various SPM products [19].
Equation 17 FF*PAB*QEPDE [22]
24
With the number of photons remaining after the losses caused by the scintillator and SPM system, the
energy resolution (R) can be determined using Equation 18 and Equation 19.
Equation 18 available photons No.
FWHM R
Equation 19 available photons No.
available photons No.*35.2 R
It is known [3, 6] that the energy resolution improves (by reducing) with increasing energy (E)
provided by Equation 20, where K is a constant of proportionality.
Equation 20 E
K R
By taking logarithms of both sides, Equation 21 is produced, which should produce a straight line and
finding the constant K allows the statistical broadening of the peak to be found [6].
Equation 21 )0.5ln(E-ln(K)R)ln(
A pre-amplification („preamp‟) board is connected to the SPM which increases the signal to hundreds
of mV, with the brightest scintillators predicted to produce (negative) SPM pulses of the order of volts
out. [22] states that the dead time of the detector to be 0.1µs, leading to a maximum count rate of
10MHz. Equation 22 shows how SPM gain is linear with the bias voltage (Vo) after breakdown
voltage (Vbr) (the electron charge (e) and the capacitance of the system (C) are constants). [22] also
shows how the dynamic range (the maximum number of simultaneous photons which can be detected
is limited to the number of microcells) increases with the number of microcells. As the microcell size
reduces, the gain decreases, so there is an important trade-off between the gain and microcell size.
Equation 22 e
brV
oVC
G)(
25
Two of the many possible areas where the SPMs have been proposed for use includes; [17]
Medical: PET scanning is dependant on fast coincidence timing which the SPM
should be capable of;
Portable security applications: such as portable radiation detectors due to the small
size and low power requirements.
Silicon has a low Z (14) which has a lower stopping power for X- and γ-ray photons than CZT (Figure
2-19). However, in SPMs, radiation detection is indirect, as optical photons come from the scintillator
crystals, not directly from the radiation photons. Scintillator materials have a good stopping ability of
low energy photons (especially 0-100keV). The noise in an SPM takes the form of „dark photons‟,
which are thermally generated (there is the option of cooling the SPM to reduce these). [33] shows that
the dark rate is 9 times higher in the 3mm SPM than the 1mm SPM and therefore the individual dark
photon pulses cannot be as clearly distinguished. It also states that the 1mm SPM has a faster onset
and decay time than the 3mm SPM. [23] describes how optical cross talk causes distinct „levels‟ of
noise present. This is where a photon is recorded across two or three microcells, with the probability
decreasing with the increased number of microcells. The onset time and dark photons were
investigated in the project.
Figure 2-19: The attenuation ratio I/I0 for the three detector materials explored for the project.
Using attenuation data collected from XCOM, Figure 2-19 shows how CZT attenuates far more
photons over the energy range and should therefore have the better detection efficiency of all the
detectors explored. (An I/Io value of 1 indicates that all of the photons pass through the material
26
unattenuated). Silicon as a direct radiation detector is seen to be very inefficient at energies greater
than 100keV.
When comparing the efficiency of the CZT to the scintillator materials (in the thicknesses used for the
detector experiments) it is seen that the detection efficiency of CZT is comparable to the scintillator
crystals.
Figure 2-20: The attenuation ratio over the energy range to be tested for the four scintillator
crystals used at 3mm thickness and the CZT detector at 5mm for direct comparison.
2.4 Radiation Measurement and Spectroscopy
What Happens to the Detected Radiation?
Imaging is possible when more than one pixel is present, so differences in the radiation detected over
the pixels can be seen. At the detector, the radiation interaction of the photon in the material is
analysed by two common methods;
Photon counting is used for low numbers of photons where a background level is set and all
counts above this are amplified and recorded.
Charge integration is used where there is a much higher flux of photons. The number of
counts incident on each pixel can be found with knowledge of the time each pixel was
integrating for, and the current for that integration time per pixel. The electron-hole pair
creation energy (W) for the detector material is known and therefore the number of counts per
27
pixel can be found. With this information, an image can be built up from the amount of
counts incident on each pixel in the detector by assigning a greyscale which typically lightens
with a higher number of counts in a pixel. The charge deposited is found by integrating the
current pulses produced in a given time according to Equation 23.
Equation 23
t
IdtQ0
Pulse Height Spectra
The energy spectrum from the radiation is typically displayed using a Multi Channel Analyser (MCA).
Here the channels (which are related to the energy of the radiation according to Equation 24) are
displayed on the x axis, and the number of counts at this channel on the y axis. In this way, a
distribution of counts over the number of available channels is produced, resulting in a pulse height
spectrum or simply „spectrum‟. The location of the peak determines the its energy, which can be used
to identify the material from the energy value. For example, a peak at 59.5keV would show that 241
Am
is present.
Figure 2-21: Operation of an MCA, an extension of many single channel analysers (SCAs) [6].
A pulse height spectrum (Figure 2-22) shows features such as the Compton edge, the peak centroid (or
full energy peak where the counts corresponding to the main γ-energy are), and escape peaks.
28
Figure 2-22: Typical pulse height spectra from γ-sources [6].
Detector Calibration
When spectroscopic data is collected, the x axis is usually a channel which is not directly equivalent to
an energy. The y axis displays the number of counts received in each channel. By irradiating the
detector with calibration sources (with peaks at known γ-energies) the channels corresponding to the
peaks can be identified with energies according to Equation 24.
Equation 24 Energy = Calibration constant * Channel Number
At least two peaks are required so an accurate calibration constant for the detector can be calculated.
More points will provide a more accurate peak value when an unknown source is used.
How is Spectroscopic Capability Determined?
Energy resolution is the ability to distinguish between two close energy peaks seen in the energy
spectrum as separate. This is a very important basis for comparison between spectroscopic detectors,
and is found using Equation 27. Spectroscopy is possible when the energy resolution, commonly
expressed as a percentage at a given energy, is low enough so the separation of close energy peaks can
be identified. The following three equations show how the energy resolution is calculated to identify
the possibility for spectroscopy from the counts in the energy peak, where σ is the standard deviation
(and according to Poisson statistics is also the error) and FWHM is the Full Width at Half Maximum.
29
Equation 25 counts of No.
Equation 26 *35.2FWHM
Equation 27 Centroid
35.2
Centroid
FWHMResolutionEnergy
Figure 2-23: An improved energy resolution is obtained with a thinner peak [6].
Ideally, a single line would be produced corresponding to the photon's γ-ray energy, and this is
approached with some very high resolution detectors, however, according to [6], the peak broadens
(Figure 2-23) due to statistical fluctuations in how the pulse is recorded, as there are inherent
fluctuations in the number carriers produced each time. For detectors with the same efficiency, the
better energy resolution will be taller (the efficiency is not dependant on the energy resolution). As
more charge carriers are produced, the error becomes less significant, so at higher energies, the energy
resolution is improved (the peak is less broad) as, for an equivalent number of photons, more charge
carriers are produced from higher energy photons, reducing the peak broadening.
The radiation peak produced is assumed to follow a Gaussian distribution (Equation 28), where the
parameters for A, B, and C correspond to the peak height, peak centroid and standard deviation
respectively.
Equation 28
2)(
2
1exp
C
BxAy
30
The area of Gaussian peaks (Equation 29) provides the number of counts in them (to be used with
Equation 28) to find the detector‟s efficiency.
Equation 29 2πAArea
Other properties of a radiation detector determine its effectiveness:
Intrinsic efficiency of a detector (εint) (Equation 30) is a measure of how many photon
interactions the detector has recorded from the number of photons which can interact with the
detector, based on the area the detector occupies.
Equation 30 detectoron incident pulses No.
recorded pulses No.int
Figure 2-24 shows how the radioactive sources radiate in a sphere, where a detector usually occupies a
small area of this. The further back the source is from the detector, the smaller the area of the sphere
incident on the detector, where fewer counts are expected to reach the detector.
Figure 2-24: The source emitting in 4π, where only a proportion of the activity is incident on the
detector at some distance (d) away.
The sources used are at different activities, and as for most sources, the γ-decays of interest for
spectroscopy (59.5, 122, 511 and 662 keV) do not account for the whole source activity (% determined
from the decay scheme). The activity (and therefore the number of counts received by a detector)
reduces as the source is moved further away from a detector according to the inverse square law as
31
seen in Equation 31, where C is the number of counts, K is a constant of proportionality for the detector
and d is the source to detector distance.
Equation 31 2d
KC
Once a number of counts recorded at a given distance is known, it is possible to determine how many
counts are expected at another source to detector distance by determining K. By using this method for
several points, the change in counts with distance to the source can be identified.
Saturation is the point at which no new counts can be detected due to a maximum number of
counts a detector can record being reached. It is an important quantity to know so the sources
which are used are kept below this level.
Dead time is the time that the detector cannot detect radiation (or count) due to the previous
counts being recorded and processed. This is equal to the difference between live time and
real time where the live time is the time the detector has actually been counting for, whilst the
real time is the time elapsed since the starting the experiment. Reducing the number of counts
(placing the source further from the detector) will be reduce the dead time.
Uniformity (Equation 32) is a measure of how similar the recorded radiation is over all the
pixels in a detector for the same incident radiation. σ is the standard deviation and centroid is
the peak energy.
Equation 32 Centroid
σUniformity
Gain is the amplification of a signal to utilise the full dynamic range of the detector. By
increasing the gain, the noise is also amplified, and therefore the level of the gain needs to be
carefully checked to ensure that any benefit in signal is not at the expense of more noise. The
signal to noise ratio (SNR) was determined for the SPM detector using Equation 33 at two
different bias voltages.
Equation 33 Size Noise
Size Pulse SNR
32
Error Analysis
The standard error in the mean (sm) (Equation 34) was commonly used to provide an uncertainty
estimate where multiple measurements were taken, where σn-1 is the standard deviation and n is the
number of readings or samples.
Equation 34 n
s nm
1
Various techniques of error analysis were performed over the course of the project in order to give
results with an estimate of the associated error. Applying Poisson statistics allows the error in a
number of counts to be recorded simply as the square root of the value as seen in Equation 35,
therefore at larger numbers of counts the statistical error in the count rate is lower.
Equation 35 counts No.Error
Background radiation is a random factor adding to the uncertainty. It is naturally occurring, however,
in a radiation laboratory, levels of background are likely to be higher and therefore needed to be
accounted for by talking measurements without the additional radiation used in the experiments.
[6] describes the propagation of errors for a function (u) dependant on three variables (x, y and z).
Equation 36 2
2
2
2
2
2
2
zyxuz
u
y
u
x
u
When appropriate, a confidence level was applied to a measured value, the most common being 95%.
The coverage factor (k) is used to give the confidence in a measurement and commonly the intervals
used are k=2 (95% confidence) and k=3 (99% confidence) [24].
There are an almost infinite number of possible sources of uncertainty when taking a measurement
including the temperature, humidity, the time of the reading, the ability of the measurer, ambient light,
presence of drafts, fields and the list goes on. Therefore any uncertainty applied to a value is only an
estimate of the error, and it is almost impossible to get a perfect measure of the uncertainty.
33
Chapter 3 : Experiments and Work Conducted Many programs, models and practical experiments were carried out to meet to aims of quantifying
spectroscopic and imaging performance of different radiation detector systems.
3.1 Calculations and Modelling
Radioactive Source Calculator
A spreadsheet was created to calculate the current activity of the radioactive sources used for the
experiments based on a known activity at some point in the past. By entering the half life of the
source, and the activity at a known date, the current activity was calculated. Using Equation 1 for each
source, the activity at any time was determined. By extrapolating the date over time from the current
activity, the future activity was calculated by Equation 2.
This was a useful spreadsheet to create, which was used several times over the project to determine
which and when sources need replacing, and the effect of diminishing activity over the measurement
period was determined.
CZT Shielding Requirements
The thickness of shielding required for the CZT detector housing needed to be calculated so the
detector could be used as a pinhole imager with a pinhole (at 10cm) away which can be added and
removed as required. All of the X-ray photons other than those from the pinhole needed to be
attenuated. The thickness of lead to do this was calculated using Equation 9. With values of „total
attenuation with coherent scattering‟, from XCOM, which varies with different materials and energies.
A spreadsheet was produced calculating the material thicknesses required (based on the absorption of
different materials) to reduce the photon flux to a desired amount. 5mm of lead would sufficiently
attenuate the X-rays, however, to reduce the fluorescence lines from the lead, the thickness of tin was
found, and finally the thickness of copper was found to reduce the fluorescence lines from the tin. The
exponentially decreasing intensity (I) was calculated as the material thickness (x) increases, reducing
the initial number of photons (I0) due to the type of material defined by the absorption coefficient (µ).
34
3.2 CZT Experiments
The CZT Detector
Figure 3-1: The CZT detector array.
The CZT detector array (Figure 3-1) has a pixel size of 1.5mm on a 1.6mm pitch which is 5mm thick.
An electric field is produced with a 500V bias, resulting in an electric field of 105Vm
-1. With electron
mobility (µe) in CZT of 1000 cm2/Vs [25] this leads to a υe of 10
6ms
-1. According to the CZT detector
manufacturer, the detector can record at 100kcps, which corresponds to 32 cps / pixel, however, the
system could equally handle all 100kcps in one pixel if all the others had zero counts [26].
Uniformity and Energy Resolution
The CZT detector was irradiated with
241Am and
57Co γ-sources to determine the uniformity and energy
resolution of the detector. The purpose of these experiments was to identify any improvement (or
deterioration) in the CZT detector performance in terms of energy resolution and uniformity, after an
upgrade, to determine whether to fully populate the detector with the upgraded material.
35
Figure 3-2: The experimental setup for the uniformity and energy resolution measurements.
The sources were in turn placed 10cm from the centre of the detector, integrations of the flood
illumination were taken over 10 and 30 minutes for each source as seen in Figure 3-2. The detector
records energy spectrum information per pixel. The analysis required code to be written in IDL (a
programming language similar to FORTRAN 90) to obtain a greyscale image of the pixel intensity. By
producing histograms (such as Figure 3-3) from the data producing this image, an inbuilt Gaussian fit
function was applied to provide values for standard deviation (C) and centroid (B). Using Equation 32,
the uniformity was calculated for both sources, to provide the spread of this data. „Binning‟ is a useful
tool, especially in with low count levels, which allows the available number of channels to be
combined such that a count with a small accepted range of energies is added to only one channel.
Figure 3-3: An image (based on detector area ~12.5cm2) from a γ-source illumination (left) and a
histogram from which the detector uniformity can be calculated (right).
36
Code was then written to correct for the artefacts and discontinuities at the CZT module boundaries by
„flat fielding‟ which uses the data taken over a large time integration (30 minutes which is much longer
than data would be collected for) to provide a data set high statistical quality data. By programming an
iterative loop to calculate the average number of counts received per pixel for the 30 minute data
(performed for each source in turn), a factor was found giving the difference from the average number
of counts per pixel. This factor was multiplied to each pixel for any other image captured with the
detector (this was initially applied to the 10 minute source flood illumination data to produce flat
fielded images). A „flat‟ (uniform number of counts over the image) image should then be produced.
Flat fields (using both calibration sources) were available to correct for other artefacts in images
collected by the detector.
Importantly, using the flood illumination data, the energy resolution was found per pixel (for each
source separately), using Equation 27. The data was read out into a spreadsheet, where statistical
analysis on the energy resolution could take place (principally the average energy resolution per pixel,
standard deviation and error) to determine the spread of the data over the pixels.
The detector was then returned to its manufacturer to have all 25 modules (5x5 array with 6400 pixels)
of CZT replaced with 12 modules (3x4 array with 3072 pixels) of higher quality CZT (the exact details
are unknown but it is assumed better leakage and uniformity across the material). Following the
detector hardware upgrade, the CZT detector was again illuminated using the previous method with the
same calibration sources in turn at 10cm from the centre of the face of the detector. Again, 10 and 30
minute integrations were taken to check the functionality of the flat field program. All of the previous
IDL programs were modified to account for the change in size of the array.
It was hoped that the CZT detector will be an improvement to the imaging quality of the ICCD
detector, and as spectroscopic information can be obtained from the detector (the CZT records the
charge and the energy per pixel) a much more compact and useful system will then be available.
37
CZT Spectroscopy
The spectroscopic capability of the detector was tested in experiments with the pinhole cover and
housing removed (to use the full area) using the 241
Am and 57
Co sources both individually and
separately. The time taken and the type of γ-spectrum which can be obtained from the CZT detector
was determined.
Using the
241Am and
57Co sources at 10cm and 12cm from the centre of the detector respectively, the
simultaneous energy spectrum (and counts recorded by the detector at each energy) were recorded.
The sources were then aligned at 15cm from the detector and were incrementally moved further from
the detector (every 5cm from 15cm to 30cm) and the energy spectrum was recorded in increasing time
increments from 1 to 10 seconds at each distance. This experiment was designed to quantify the
maximum number of counts received by the detector over the energy range to identify if the detector
counts linearly over time and that the inverse square law is followed.
CZT Efficiency Measurements
241
Am and 57
Co sources were placed separately at three distances (0.5, 1 and 1.5m) from the CZT
detector, without the housing and pinhole, and 10 minute integrations for each source at each distance
were taken. To determine the intrinsic efficiency (Equation 30), the number of counts in the energy
peak is required, which for the CZT detector was determined by calculation (Equation 29) using the
height and standard deviation values from the fitted Gaussian peak. (The energy peak is assumed to be
a Gaussian, where the fit is a good match to the data as seen in Figure 3-4).
Figure 3-4: The Gaussian fit to the 241
Am peak (at 0.5m for 10 minutes).
Energy (keV)
Sum
med
counts
38
From the activity incident on the detector (based on the distance to the detector and source), the portion
of the sphere occupied by the detector created by the source, and the activity at the energy peak of
interest (59.5 and 122keV for the CZT detector) the detection efficiency was determined.
The ICCD Detector
The Intensified Charge Coupled Device (ICCD) detector has a thin (2.5mm thick) pixellated CsI(Tl)
crystal array converting X- and γ-ray photons into optical photons.
Figure 3-5: The ICCD detector (with a 2mm pinhole plate attached).
Removing the cover and pinhole plate exposes the front of the detector, which allowed the detector
area to be flooded with the same two calibration sources used for the CZT detector, in the same
experimental arrangement. Software used with the detector allows use of the previously acquired data
for flat field corrections. For a fair comparison to the CZT for the detector uniformity, flat field
measurements were made using the ICCD detector.
CZT and ICCD X-ray Backscatter Pinhole Imaging
The use of the CZT detector as an imager using a newly designed graded shielding was tested and
compared to the images obtained using an ICCD detector in the same experimental configuration.
39
Figure 3-6: The housing applied to the CZT detector providing a pinhole aperture at 10cm from
the centre of the detector.
Figure 3-7: Top view of the arrangement for X-ray backscatter pinhole imaging.
By facing an X-ray generator towards a target material and irradiating it with 160keVp (peak energy of
160keV) X-rays for 10 seconds, the CZT detector (with the 2mm pinhole) received backscattered
photons from the target and surroundings.
Figure 3-8: An image created using a pinhole receiving backscattered X-rays (left) and the effect
chamfering has on the pinhole (right-above before and right-below after chamfering).
CZT detector
(with pinhole)
Target
material
X-ray
generator
40
Figure 3-8 (right) shows that the area covered by the pinhole (exaggerated) which was not initially the
entire active area of the detector (in Figure 3-8 (left) black indicates where there are fewer photon
interactions due to the collimation effect). It was therefore necessary to chamfer behind the pinhole by
calculating the angle required to allow the whole detector area to be used.
With the chamfering successful, a background measurement with the pinhole covered and
backscattered X-rays being incident on the detector was made. This found that X-rays were leaking in
to the detector, causing the image shown in Figure 3-9.
Figure 3-9: The leakage obtained before the additional shielding (detector area ~7.9x10-3
m2).
Before any backscatter images were taken, this leakage needed to be eliminated to avoid the additional
effect on the measurements. The best method for additionally shielding the detector was established by
applying lead shielding all around the detector (including the pinhole) and sequentially removing the
lead in sections to identify where the leak was coming from, by measuring the average number of
counts per second in the imaging section of the CZT software for short (10-60 second) integrations. It
was found that the optimum arrangement (using the least additional lead to produce a uniform output)
of lead shielding requires blocks between the X-ray generator and the side of the CZT detector, and
additional blocks at the back of the detector to reduce X-rays getting in this way, as seen in Figure
3-10.
41
Figure 3-10: The optimum shielding configuration (left) and the more uniformly distributed
counts with this shielding.
After warming up the X-ray generator (required to recondition the vacuum after a period of inactivity),
various objects were illuminated with 160keVp X-rays from a continuous X-ray generator for 10
seconds. The detector recorded all the time X-rays were being produced. The objects were placed
55cm from X-ray generator and 30cm from the pinhole aperture of the detector. These distances and
times were determined after looking at several settings and integration times, so the output images were
centred, a good size in proportion to the background and not saturated. The same experimental
arrangement (integration times, pinhole, distances and energies) was setup for the ICCD detector and
images were taken using the 2mm pinhole, once removed from the CZT detector housing.
Images were taken of several objects with different atomic numbers (Z) and densities (including salt,
sugar, cotton, talc powder, aluminium powder and tungsten) which were on their own, and then in a
typical luggage case. To elevate the objects that were not in a suitcase (for differentiation between the
floor and the object and to reduce scatter from the floor), the objects were placed on a plastic block
5cm high when out of case measurements were made for a direct comparison between the images. The
ICCD images had a „best fit‟ function for the brightness and contrast applied using Image Pro Plus
software. The CZT data was processed with IDL code to display the images. The flat field corrections
acquired prior to these measurements for both the CZT and ICCD detectors, (based on the 30 minute
57Co illumination) were used to „clean-up‟ the images by removing the artefacts caused by the detector.
42
CZT and ICCD Angular Resolution
This experiment was conducted to provide another basis of comparison between the ICCD and CZT
detectors. A tube of salt and a tube of sugar (arbitrary objects 7.5cm long (up to the lid) with a
diameter of 2.5cm), were placed at 40cm from the both detectors, and the X-ray generator was placed
at 60cm from the objects to be imaged. Additional shielding was again added around the CZT detector.
The 2mm pinhole was used for both detectors, and as there is only one pinhole, the experiments were
run first for the CZT and then for the ICCD using the same experimental setup.
Figure 3-11: The experimental arrangement for separation experiment (CZT pinhole covered for
a background measurement).
The salt tube was placed on one circle and was fixed there, and the sugar was placed in decreasing
distances in increments of 1cm closer to the salt tube. At distances of 1 and 2cm from the tube of salt,
the sugar was placed further back from the salt (Figure 3-12) else both tubes would have overlapped.
Figure 3-12: The positions of the tubes of salt and sugar, moving closer together in 1cm steps.
CZT Detector
ICCD
Detector X-ray
Generator
Objects
Fixed
salt position 3 4 5
1 2
43
Backscatter X-ray images were taken for 10 seconds using 160keVp X-rays. The images from the CZT
detector were then processed using IDL code to flat field each image using the 30 minute 57
Co data.
The ICCD images were also flat fielded using a pre-existing function in the image processing software,
also based on the 30 minute 57
Co illumination for the ICCD detector.
Using IDL code for each flat fielded image from each detector, each image was modified so a line of
data (or a profile), of counts (CZT) and intensity (ICCD) was stored to a file, recording the change
through the objects and background. (This line was identified by setting the pixel values along a line to
an arbitrary number, which was returned to its original value when the data was read out).
Figure 3-13: The line of data extracted for ICCD images (left) and CZT images (right).
This data was normalised for each image, and plots of the intensity with pixel value were made
separately for each image, combined for individual detectors and combined for both detectors to
numerically quantify how the images vary for each detector records over each image.
3.3 SPM Experiments
Scintillator and SPM Energy Resolution Model
A spreadsheet model was created to estimate the number of photons reaching each SPM and then being
lost, to find the energy resolutions possible using Equation 18 and Equation 19 over the energy range.
Starting from an initial energy deposited to each scintillator through the four calibration sources, this
study was performed to indicate if spectroscopy is theoretically possible from the energy resolutions
44
obtained. For example, an energy resolution of 20% at 662keV would allow another peak to be
resolved below 530 and above 795keV. According to [28] values for the scintillator efficiency are
between 3 and 15%. The justification for using scintillator efficiencies for each of the scintillators of
5% comes from the fact that not all of this light produced will be transferred to the SPM (coupling
losses between the scintillator and SPM with an imperfect match) which will reduce this efficiency.
Numbers corresponding to each scintillator material and SPM are chosen by the user, and the
spreadsheet automatically looks up the values for light yield, active areas, and photon detection
efficiency from product manufacturer data. The number of photons remaining after each deduction can
be seen for each scintillator and SPM combination over the energy range, resulting in the overall
expected system efficiency and the expected energy resolution.
Multiplying the PDE (obtained from Figure 2-18) at each wavelength by the scintillator by the active
area (which varies between SPMs) gives a number of photons, which was used to find the energy
resolution for that combination. According to the manufacturer [27], Figure 2-18 could be used to
determine the PDEs for all of the SPMs by multiplying by a constant (1.5) from the 20µm PDE values
to find the PDE for the 35µm SPM. These values were used in the model to calculate the energy
resolution for each combination of scintillator, crystal and SPM when used with each source. The PDE
technical note was released in August 2007 showing the recent development in the technology. Plots
based on the model provided the expected energy resolution as a function of energy for each of the
scintillator crystals with each SPM. These were compared to the measured spectra produced later on.
The spreadsheet can easily be upgraded with new values or materials.
Saturation of the SPM occurs when all of the microcells simultaneously detect photons, and there are
1144 microcells on the 1mm 20μm SPM, and 3640 and 8640 in the 3mm 35μm and 20μm SPM [37].
Therefore the SPM with the highest PDE is the 3mm 35μm SPM, which will however saturate before
the 3mm 20μm SPM.
45
Light Emitting Diode (LED) testing
Before the scintillator crystals arrived, experiments utilising LEDs were designed and built to simulate
light flashes. This series of experiments was used to identify the speed of the SPM response from an
off to an on state, and the size of the SPM response pulses for a given LED light pulse incident on the
SPM. Astable multivibrator (pulsing) circuits were setup using various combinations of components
(Figure 3-14) providing a selection of duty cycles, frequencies and durations to cause an LED to flash.
Figure 3-14: The transistor astable circuits produced to pulse an LED [30] (left) and a circuit
diagram for the 555 IC used to pulse an LED [32] (right).
The 555 Integrated Circuit (IC) was used to pulse an LED for the SPM experiments. Usually a 555
operates with a duty cycle (the amount of time the unit is on) of over 50%. Using a diode in parallel
with the R2 resistance allowed the duty cycle to be less than 50%, and the „on‟ time is then related to
R1*C, and the „off‟ time by R2*C. These were used to find values of resistors and capacitors to keep
the LED pulse on and off for the desired times (between 0.5 and 20µs).
Figure 3-15: The oscillator circuits produced to pulse an LED using transistors and capacitors
(left) and the pre-packaged oscillator in the IC NE555 timer (right).
46
A 555 Integrated Circuit (IC) was used for the majority of the measurements with the timer output
pulsing an LED requiring fewer components to set the frequency than Figure 3-15 (left). An
oscilloscope placed in parallel with the LED, was used to capture the pulses the LED was receiving to
confirm the frequency, duration and size. The timer is capable of microsecond pulsing [31] and the
LED was then pulsed with the maximum repetition frequency of the 555 (on for 0.5μs).
The tests were initially conducted on the 1mm SPM at a bias of 30V. The LED was placed on top of
the SPM in contact with the glass, and secured there. The equipment was all housed in an aluminium
box and covered with black cloth to prevent as much extraneous light as possible reaching the SPM.
The rise time of the SPMs was found by using LED pulses incident on the SPM to determine the time
taken for the SPM pulse voltage to go from off to on (onset time). The SPM was connected to a
channel of the oscilloscope and another channel of the oscilloscope was connected in parallel with the
LED to allow the LED pulse and SPM response to be recorded simultaneously. Various amplitudes
and frequencies of light pulses were sent to the LED and the SPM responses were captured using a
printer connected to the oscilloscope (Lecroy 334AM). This was repeated for various frequencies for
each SPM.
SPM Pulse Linearity
Tests were again conducted on the 1mm SPM at a bias of 30V, to determine how the SPM responds to
the varying power of an LED (changing the number of photons produced). It is expected that the
parallel arrangement of the SPM microcells will provide a proportional output to the amount of
incident light. A variable resistor (potentiometer) was placed in series with the output of the 555 timer
circuit and a red 3mm LED (which was in contact with the SPM) to adjust the power to the LED. An
ohmmeter was placed across the resistor to determine its resistance, whilst simultaneously the current
through the LED was determined by placing an ammeter in series with the LED.
Readings were taken approximately every 10Ω, from 0 to 70Ω, however, it was extremely difficult to
get 10Ω increments accurately, due to a very small adjustment on the potentiometer changing the
47
resistance by several ohms. Repeat measurements were therefore not possible using the same values of
resistance, however, by taking many measurements over the range from the LED on to off (around 10
measurements) a graphical fit can be obtained. The data collected (the current and voltage for each
resistance) was used to calculate the power going through the LED, so comparisons between the
resistance and LED voltage, resistance and SPM voltage, and power and SPM voltage can be made.
Figure 3-16: Experimental arrangement for the SPM pulse linearity experiment.
SPM Pulse Observations
To activate the scintillator crystals 57
Co, 22
Na and 137
Cs sources at high activity with different γ-
energies were selected and procured, providing peak γ-energies from 59.5 to 662keV which were used
with an existing 241
Am source.
Source Peak γ-Energy
(keV)
Activity (kBq)
(1/10/07)
Half life % of Source
Intensity
241Am* 59.5 465 432.2 yr 35.75
57Co 122 362 270 days 85.64
22Na 511 343 2.6 yr 180.00
137Cs 662 410 30.174 yr 85.05
57Co (original)* 122 30 270 days 85.64
Table 3-1: Procured calibration source details. (*Used for CZT detector uniformity and energy
resolution experiments and were original laboratory sources.)
48
Four scintillator crystals (CsI(Tl), BGO, LYSO and CdWO4) which produce light at different
wavelengths with different light yields and decay times were supplied as 3x3x3mm cubes to couple to
the SPMs. These cubes were tightly wrapped with reflective material (Tyvek paper) around 5 of the
sides which was held in place with „plumbers tape‟, to ensure as much light as possible leaves through
the exposed aperture to the SPM. The free side was then coupled to the SPM surface using a tiny
amount of silicone grease (just enough to cover the exposed side of the scintillator) allowing
conduction of the light from the scintillator to the SPM, and providing enough friction to hold the
crystal on top of the SPM. The scintillator and SPM combination was then placed in the aluminium
box. Power and output to an oscilloscope were connected to the SPM through a small hole in this box,
and each γ-source was placed in turn at approximately 2.5cm from the scintillator crystal. The box was
then closed and covered with a black cloth (in the absence of a dark room). This setup can be seen in
Figure 3-17. The source caused the SPM to record pulses from the scintillator crystal light, the voltage
pulse size and decay times from the scintillator were found for each combination and directly printed
from the oscilloscope once a pulse had triggered (trigger set above the noise). To prevent radiation
damage to the crystals, sources were placed only placed near the crystals when necessary. The
printouts were used to find the decay time and size of pulses so the data acquisition system could be
setup to „look‟ for decay times and voltages of the pulses from each experimental combination. These
values for rise time and pulse height were entered to a spreadsheet, where the differences between the
sizes of the pulses from the different SPMs and crystals were quantified.
Using CsI(Tl) with 22
Na in the experimental arrangement above, the effect of the increase in the SPM
bias voltage from 30 to 32V was determined by exploring the sizes of the scintillation pulses printed
from an oscilloscope. Noise pulses were found by removing the source and printing the SPM
responses. The sizes of the pulses were read from the oscilloscope printouts for both the noise (dark
photons) and for the scintillation photons, and a comparison plot of the SNR (Equation 33) for all three
SPMs at the two bias voltages was produced.
49
Figure 3-17: The pulse exploration and SPM spectroscopy experimental arrangement.
SPM Spectroscopy
Using a similar experimental setup for the pulse measurements, the wrapped scintillator cubes were
coupled to the SPMs using silicone grease (RS 494-124). The SPM output was then connected to a
DAQ system (Figure 3-18), which records and displays the energy spectrum produced from the SPM.
Parameters on the DAQ were set based on the decay of the crystals found previously and all settings
needed to be very carefully adjusted by collecting spectra for about 10 minutes using a range of rise
times and decay times to provide the best energy resolution. Once correctly setup, the spectra were
collected for 30 minutes for each radioactive source, and these measurements were repeated again to
allow for the standard error in the mean (Equation 34) to be applied to the energy resolutions measured.
Following these measurements, the source was changed such that all four sources were used on the
same scintillator crystal and SPM. The system was then setup again using the second of the four
scintillator crystals, and the four radioactive sources used in turn to activate them. The measurements
using this crystal were then repeated to allow an average and error to be applied. Finally, the SPM was
tested without any sources present, to quantify the background.
Power
SPM Wrapped
crystal
Source
Output
50
Figure 3-18: The Xia Pixie-4 system used to acquire the spectrum from the SPM detectors.
The setup was then disassembled and the experiments repeated for the next SPM where all of the
measurements were repeated, and then finally for the third SPM. A summary of all the measurements
planned is included in Figure 3-19.
Figure 3-19: A summary of the planned SPM testing, showing each SPM coupled to each
scintillator crystal activated by each γ-source, and the background measurements.
For consistency, the same set of scintillator crystals (cubes 3x3x3mm) was used for each of the SPM
experiments even though there was a mismatch in sizes when using the 1mm SPM. For best light
transfer, the area of the detector and scintillator should match. It was initially estimated that 1 in 9 of
the photons would be detected due to the difference in scintillator area to the SPM area.
For 1mm spectra, another MCA channel (without a 7.5x attenuation) was used with a lower SPM bias
voltage (30V compared to 32V for the 3mm SPMs), and a higher threshold was set to eliminate the
noise pulses. MCA events seen in the MHz region (due to noise) were reduced to ~10Hz with the
correct threshold set, indicating that only scintillation events are recorded.
51
SPM Detector Efficiency
Previously (Figure 2-20) it was seen that the ability of the scintillator crystals to attenuate at 59.5keV is
much higher than at 662keV. It was required to determine the SPM detector efficiency over a range of
energies.
Using several energy spectra found from in previous section, the number of counts in the photopeak for
the SPM detector was easier to determine than for the CZT. Using the MCA software to select a region
of interest (ROI) around the γ-peak to return the number of counts, Equation 30 was used to find the
system efficiency (as for the CZT efficiency seen previously, to find the area of a sphere occupied).
The Single Photo Electron Spectrum
The SPMs are able to detect single photons and the Single Photo Electron Spectrum (SPES) is
produced when the charge from the short light pulses are integrated [21]. Using the pulsed LED
circuits placed on top of the SPMs, attempts to collect the SPES were made. It was however very
difficult to perform this experiment due to the requirements to produce such a small number of
photons. The fastest the circuits made could pulse was in microseconds, whilst for SPES nanoseconds
are preferred to ensure fewer photons are created. The distance from the LED to the SPM was
maximised, the power to the LED was reduced as much as possible (using a resistor in series with the
LED) and varying thicknesses of paper were placed over the SPM to reduce the light. However, when
exploring the spectrum, blurring of the peaks was found, indicating the increased number of photons
from the LED. This spectrum has been successfully produced by others [21] (Figure 3-20) for the SPM
devices, showing three clear photoelectron peaks (corresponding to 1, 2 or 3 microcells firing due to an
incident photon) after the pedestal (integration of the noise of the system [17]) peak.
Figure 3-20: The single photoelectron spectrum possible with an SPM [21 modified].
52
Chapter 4 : Results and Analysis
Vast amounts of data and spectra were collected from the experiments using the various detectors
which produced graphs, images and numerical values for comparison. These were mainly analysed
using IDL software, MCA software and spreadsheets.
4.1 Modelling Results
Radioactive Source Calculator
It can be seen from Figure 4-1, that the biggest decrease in radioactive source activity occurs with 57
Co
due to its relatively short half life. Additionally, the activity on the date of the measurements could be
found allowing the intrinsic detector efficiency calculations to be performed.
Figure 4-1: The activity calculator with extrapolated activity over two months.
CZT Shielding Results
A spreadsheet using data from XCOM was used to determine the amount of attenuation provided by
three different metals to attenuate the X-rays and the fluorescence lines from the materials.
Figure 4-2: A screenshot from the shielding requirements spreadsheet for pinhole imaging.
It can be seen that to reduce the number of photons to an acceptable level (taken as approximately 2%)
from the fluorescence lines of lead (Pb), 2mm of tin (Sn) is required, and to reduce the fluorescence
lines of tin, 1mm of copper (Cu) is required. At these thicknesses, the greatest contribution to a
spectrum would be from the 85keV peak from lead, which is only 2.3% of its original value. The final
design included an aluminium casing so that lead is not handled directly.
53
4.2 CZT Experimentation Results
Uniformity and Energy Resolution
The results of the first 30 minute integrations for the original combination of the 5x5 CZT array clearly
show the module edges (Figure 4-3 is 241
Am). A greyscale image for the intensity at each pixel
(brighter pixels shows higher photon counts) and a histogram were produced for both sources.
Figure 4-3: An image (left) and histogram (right) from the 241
Am illumination (over 30 minutes)
Figure 4-4: A histogram with a fitted Gaussian for the 30 minute integration of 241
Am.
The CZT detector uniformity was found using Equation 32 using values from the fitted Gaussian in
Figure 4-4, where C is the standard deviation and B is the peak centroid. It was found that the
uniformity of the detector after applying flat fielding corrections was 8.7% for 241
Am and 9.8% for
57Co. With this low spread in the data we can determine that after these corrections, any images
produced should have a similar (within error from the flat field corrections) greyscale intensity for the
same incident radiation as the number of counts from an object. Flat fielding the 10 minute
illumination using the 30 minute flat field data for each illumination results in Figure 4-5 for both
sources, where the majority of the defects (module edges) in Figure 4-3 are removed. It should be
noted that the bright pixels (Figure 4-5 right) make the image appear more uniform or „flat‟ than they
really are, numerically there is not as much difference between the two which is shown in Table 4-1.
Number of counts
Num
ber
of
pix
els
wit
h t
his
count
inte
nsi
ty
54
Figure 4-5: Flat field corrections applied to the 10 minute data for 241
Am (left) and 57
Co (right).
Based on the data collected, the energy resolution was calculated to be 4.16 0.05% for 57
Co and
8.14 0.05% for 241
Am, which is very encouraging, showing that spectroscopy should be possible at
these energies, with another energy peak able to be resolved above 127keV in the presence of a
122keV 57
Co peak. This was tested to determine if the 136keV peak in 57
Co was seen in the energy
spectrum.
Once upgraded, the CZT detector had 3072 pixels on a 3x4 array (reduced from 6400 on the 5x5
array). The energy resolution per pixel was plotted following the CZT detector upgrade based on the
30 minute integration data for 241
Am and 57
Co are shown in Figure 4-6.
Figure 4-6: The energy resolution per pixel for the 57
Co 30 minute integration (left) and for the 241
Am 30 minute integration (right).
When plotted, the summed energy spectrum from each pixel shows clear peaks at the energy of the
sources used (Figure 4-7) demonstrating spectroscopic capability. The 136keV is also present at 10%
the activity of the 122keV line as expected.
Bright pixels
masking true
discontinuities
Ener
gy R
esolu
tion (
%)
Channel Number
Ener
gy R
esolu
tion (
%)
Channel Number
55
Figure 4-7: Energy spectra using 57
Co for 30 minutes (left) and
241Am for 30 minutes (right).
Plotting the intensity per pixel for the upgraded CZT detector clearly shows an artefact in the top
middle module and the module boundaries (Figure 4-8) which appear in images for both sources before
flat fielding. By applying the flat field corrections in IDL to the 10 minute integration image, these
artefacts are removed, and the flat fields were then applied to the future images taken. Without
applying the flat field, the artefacts will continue to be present in any images taken.
Figure 4-8: Illumination of the 30 minute 57
Co (left) and 241
Am for 30 minutes (right) showing
crystal artefacts.
Figure 4-9: Flat fielded image with 57
Co (left) and 241
Am (right) showing the artefact has now
gone. Note the bright pixels (right) mask the true discontinuities image.
Substantial
artefact in
this module
Energy (keV) (keV)
Sum
med
Ener
gy S
pec
trum
Energy (keV)
Sum
med
Ener
gy S
pec
trum
56
Creating a histogram from these images and fitting a Gaussian curve in IDL produces values for the
standard deviation and centroid used to find the upgraded detector uniformity. (The uniformity ratio
encompasses an error as the standard deviation is the error in the centroid.)
Source Before Upgrade After Upgrade
Uniformity (%) Energy Resolution (%) Uniformity (%) Energy Resolution (%) 241
Am 8.69 8.14 0.05 7.04 7.91 0.03 57
Co 9.84 4.16 0.05 2.94 4.00 0.02
Table 4-1: The results for the uniformity (after flat fielding) and energy resolution of the CZT
detector before and after the hardware upgrade.
The 10 and 30 minute flood illuminations were also completed for the ICCD detector using the same
experimental setup and sources as the CZT detector measurements, so flat field corrections would be
available to correct for systematic artefacts in the images produced by the ICCD detector. Table 4-2
shows the effect the flat field corrections have on the 10 minute collected data compared to that
collected for 30 minutes for the ICCD detector. For both sources, the flat field causes the spread in the
data to be reduced by over a factor of 2.
The results in Table 4-2 show that on average the CZT detector has an overall better uniformity after
the flat field corrections, than the ICCD detector, which is thought to be due to the much larger pixel
size (1.6mm compared to 0.5mm) of the CZT collecting more charges reduces the statistical error on
the uniformity.
Source Before flat field
corrections
After flat field
corrections
% Improvement
241Am
Mean 1073.069 1510.657
SD 155.9503 98.334
SD/Mean 14.53% 6.51% 223% 57
Co
Mean 482.7793 1673.786
SD 83.526 138.8751
SD/Mean 17.30% 8.30% 209%
Table 4-2: The uniformity of the ICCD detector for each source before and after applying the flat
field corrections.
The errors in the CZT detector energy resolution were found using the average energy resolution per
pixel and calculating the standard error (Equation 34, where n is 6400 for the original detector and
57
3072 for the upgraded detector). It can be seen that the error in the energy resolution is reduced for the
upgraded detector indicating there is less spread over all pixels.
It can be seen that a 4% improvement in energy resolution has been gained from the upgrade with the
57Co source, even with a more pronounced artefact in one of the top modules. With this performance
increase, better γ-peak separation (as the energy resolution is improved) and more uniform images
(more similar pixel values for the same incident radiation) should be obtained from this detector. It
was found that both the energy resolution and the uniformity of the new detector is improved compared
to the original detector. Initial observations showed that the number of obviously hot pixels (those with
a number of counts substantially higher than the mean) was also reduced (however, this is also because
there are fewer pixels available). To quantify the effect the flat field had in addition to Figure 4-8,
normalised Gaussian curves were plotted based on the parameters (A, B and C) provided by IDL for
both before and after the flat field for the upgraded CZT detector using both γ-sources.
Using the four sets of Gaussian parameters (both sources before and both sources after the flat field
corrections), four Gaussian curves were plotted using Equation 28. The curves were normalised so a
comparison for each source of before and after flat field corrections were applied to determine the
change in statistical spread in the data (as seen in Figure 4-10).
Source FWHM before corrections FWHM after corrections Improvement (%)
241Am 1975 136 1452%
57Co 382 44 868%
Table 4-3: The effect of ‘flat fielding’ on the CZT Gaussian peaks, for the upgraded detector.
Figure 4-10: The effect of flat fielding on the 30 minute flood illuminations for both sources 241
Am (left) and 57
Co (right).
58
CZT Spectroscopy
To test the spectroscopic capability of the detector, in terms of linearity in the number of counts
recorded over time and the energy resolutions possible, radioactive sources were placed near the
detector. The results seen in Figure 4-11 show that for two different sources with different activities
there is linearity with a high goodness of fit, in the detection of the counts (taken as the maximum
number in the peak) at 59.5 and 122keV with time. The CZT detector background (cover off with no
sources) is insignificant compared to these values providing 14 1 counts per second (error taken as
nearest count from the average background measurements of 10 and 60 seconds).
Figure 4-11: A linear relationship successfully identified between increase in counts and
integration time, for two γ-sources.
The expected number of counts for each source can be confidently extrapolated, based on the data
collected due to the uniformity of the fit. Dividing the number of counts by the integration time, the
count rate (in counts per seconds) was determined for each source over the 10 second integration
period which was repeated for both sources. These were found to be 868 6 for 57
Co and 1103 4 for
241Am. When incrementally decreasing the integration time, it was possible to obtain a spectrum with
over a thousand counts in only one second using this detector, with well defined peaks at the two γ-
energies used. Figure 4-12 shows an energy spectrum with three clearly distinguishable peaks (59.5,
59
122 and 136keV). The detector uniformity is indicated by the hits / channel chart on the bottom
showing nearly all pixels receive a similar number of counts (all but one pixel has approximately 10
counts).
Figure 4-12: The energy spectrum after just one second, showing 241
Am (59.5keV) and 57
Co
source (122 and 136keV) peaks.
It was found that the CZT detector counts linearly for both sources over the experimented time range,
(as the count rate remains constant when graphed they are within error bars).
As the source to detector distance increases, the number of counts decreases following the inverse
square law (Figure 4-13) as expected from Equation 31. The results in this section prove that the
detector can make a high resolution and fast spectroscopic detector when integrating for short times,
for passive γ-ray detection, currently operating in the range of ~20 – 200keV.
60
Figure 4-13: The effect of time and distance on the maximum number of counts received for two
of the integrations times tested using the CZT detector, showing the inverse square law.
Figure 4-14 shows the excellent correspondence to recent (in the final weeks of the placement)
published results using 57
Co [38] also using a CZT detector array.
Figure 4-14: The measured energy spectrum (left) and one just published for 57
Co (right) [38].
The energy resolutions have also recently been explored by others [38], where an excellent match to
the measured results in addition to the measured spectra. It was found in the „Uniformity and Energy
Resolution‟ section that the upgraded CZT detector provides an energy resolution of 7.91 0.03 % at
59.5keV and 4.00 0.02 % at 122keV. [38] presents an average energy resolution of 5.5keV FHWM
at 122keV, equivalent to 4.5% which is strikingly similar to the results measured.
16.0 27.5
61
CZT Efficiency
Efficiency is a measure of how well the detector records the incident radiation. The CZT detection
efficiency was measured to be 72 1% for the 241
Am source and 58 2% for using the 57
Co source
(calculated as the standard error in the measurements where error bars were found using the fractional
errors based on the error in the distance from the detector, and the error in the number of counts). This
corresponds to a 24% decrease in efficiency at the 122keV energy compared to at 59.5keV, where from
the attenuation of the material, only a 6% decrease is expected due to the increase in energy. The CZT
detector efficiency is less than expected, based on the attenuation of the CZT material for these energy
photons and is possibly due to not all of the CZT thickness able to detect photons.
Figure 4-15: The efficiency of the CZT detector with increasing source distance.
CZT and ICCD X-ray Backscatter Imaging
To determine the performance of the imaging quality using the CZT detector and for comparison with
the ICCD detector, X-ray backscatter images through a pinhole were taken. The same experimental
setup was used for both detectors using the newly created graded shielding with a 2mm pinhole
aperture with the CZT detector (along with the additional lead shielding required).
It was proved that imaging using both the ICCD and the CZT detector is clearly possible and 20 images
were taken for objects both in and out of a case. The items in a case made no significant impact on the
images using either detector, due to its thin size and low density. Due to the number of CZT pixels
being substantially less than in the ICCD (3072 vs. approximately 42,000) and much larger pixels
62
being used in the CZT (CZT pixel size of 1.5mm (pitch 1.6mm) vs. 450μm (pitch 0.5mm) for the
ICCD), the images are not as clear using the CZT detector compared to the ICCD. However, the
difference in contrast initially appeared better in the CZT images, where there is an object and where
there is no object, which was quantified later on. The ICCD images sharpen as the pinhole reduces in
size from 4mm to 2mm for the same time integration as expected (Figure 4-16).
Figure 4-16: A direct comparison for the same object (sugar) with the 4mm and 2mm pinholes
(before flat field corrections) from the ICCD detector.
To compare the images between the CZT and ICCD detectors in the rest of this section fairly, the
images are shown with the peak of dynamic range selected for both, such that the contrast is not biased
towards either detector. The images however, are quantified numerically later on, where the effect of
the contrast range selected makes no difference.
Figure 4-17: Flat fielded images of cotton in a case, using CZT (left) and ICCD (right).
63
Figure 4-18: Talc and aluminium powder on a plastic base (flat fielded) using CZT (left), ICCD
(middle), and before flat field corrections applied to the CZT (right).
After flat field correcting, („flat fielding‟) the images produced are much clearer (compare Figure 4-18
left and right). The blackened pixels in the CZT images are assumed to correspond to the pixels
switched off due to erroneously high count rates. Future work on the image processing can eliminate
the effect these pixels have on the images by programming code to identify these pixels (those with an
extremely low count) and setting them equal to the average of the surrounding pixels.
To compare the images produced from the backscattered X-rays on the CZT and ICCD images, it was
necessary to quantify the data numerically. The number of counts (CZT) and intensity (ICCD) of the
pixels were measured for the same images. Regions of the flat fielded images were selected to
encompass a portion of the object and then the same size portion of the background, by identifying an
area „by eye‟ which appears in images from both detectors, and selecting pixels in these areas.
64
Figure 4-19: Images of the same object (but reversed) of the sections taken for analysis of the
mean and standard deviation (CZT left and ICCD right).
For the flat fielded CZT detector images, 20 pixels were manually chosen in these regions of objects
and the background and the count values were taken and recorded in a spreadsheet. This was repeated
so that there were two target objects and two background objects. The same regions were selected in
the ICCD images, where software automatically calculates the mean and standard deviation for all of
the pixels in the selected region.
Figure 4-20: A graphical representation of the data collected for the ratio of object to
background each image from both detectors.
By investigating the same two images for each detector, it was found that for each image, the ratio of
object to background was higher for the CZT detector (Figure 4-20). This means that the objects of
interest stand out better for this detector than for the ICCD detector. A surprisingly high fractional
error was found for the CZT detector for these measurements which was attributed to the vast
65
difference in number of pixels selected for the CZT detector and ICCD detector, causing the standard
deviation to have a much greater effect on the associated error.
Based on the images produced and the improved energy resolution, it is recommended that the CZT
detector be fully populated with the upgraded material, to provide a wider imaging area, and therefore a
larger detection probability. In the future, reducing the CZT pixel size, clearer images will be obtained,
making the CZT better competition for the smoothness provided by the ICCD detector.
Figure 4-21: The number of counts from the average of 10 pixels in the CZT and ICCD detector
for all of the objects (error as the standard deviation).
Figure 4-21 shows how the highest Z element (tungsten) produces the fewest backscattered photons (as
expected as more X-rays are absorbed in the photoelectric effect at higher Z). The effect of the case
the objects were in was found to be negligible for the experiments. The error (taken as the standard
deviation of the data for both detectors) was greater for each of the ICCD images than for the CZT
detector, which reflects the larger pixel size of the CZT providing better sensitivity.
Angular Resolution
The resulting backscatter images from this experiment were processed and displayed using IDL (CZT
detector) and Image Pro Plus software (ICCD detector) to compare the two detectors. The images from
each detector are displayed in Figure 4-22 to Figure 4-25 (the 1cm images for both detectors being used
to compare the flat fielded images to the non-flat fielded images).
Norm
alis
ed a
ver
age
counts
in t
he
obje
ct
66
Figure 4-22: 1cm apart before flat field corrections (left) and after (right) for the CZT detector.
Figure 4-23: 2-4cm (left to right) after flat field corrections for the CZT detector.
Figure 4-24: 1cm apart before flat field corrections (left) and after (right) for the ICCD detector.
Figure 4-25: 2-4cm (left to right) after flat field corrections with 57
Co 30 minutes for the ICCD
detector.
67
Based on the diameter of the two tubes, the first position where the two tubes are physically separate is
at 3cm (the two radii of the tubes are 2.5cm therefore the first tested position where the objects should
be resolved is the 3cm position). A change in intensity indicating separation was found at this distance
for both detectors. For the ICCD detector, the overlapping of the lids in the 2cm image are an
indication that more than one object is present whilst for the CZT detector, the overlapping at 2cm
causes a wider object to be produced than at 1cm. The results from the profile for each separation
image for both detectors are shown in Figure 4-26, which were normalised for a direct comparison.
Figure 4-26: The separation seen using the CZT (top) and ICCD (bottom) detectors over 5cm,
where the background for the ICCD is always higher than CZT.
For both detectors, there is a trough in the normalised counts (CZT) and normalised intensity (ICCD) at
the 2cm separation image, even though there is no physical gap between the objects; the difference is
due to the thickness of the materials being detected due to a change in the number of photons. This is a
success for both detectors. It should be noted that there is a much higher background using the ICCD
detector (about 20% of the maximum intensity compared to less than 10% for the CZT). The
68
separation of the materials was measured by the size of the trough between the two peaks was plotted
for each detector at each distance, and the results shown in Figure 4-27, giving a comparison between
the two. The high ICCD background level makes the objects stand out less than for the CZT which
follows the theory as smaller pixels give better spatial resolution but reduced sensitivity.
Figure 4-27: The separation displayed as the change in normalised intensity for both detectors
(error bars as smallest unit taken from the trough height).
This experiment showed that both detectors measure a difference in intensity where the objects begin to
overlap, which increases with the separation of the two objects. Importantly, the larger pixel size of the
CZT provides better sensitivity seen as a much lower background where no object is present, than the
ICCD detector which shows a steady 20% background (Figure 4-26 bottom).
4.3 Scintillator and SPM Experiments
Scintillator and SPM Energy Resolution Model
The model showed that coupling scintillators to SPMs would be an inefficient process with some
combinations of scintillator, SPM and γ-sources, resulting in a total loss of over 95% of optical photons
produced from the radiation photons, producing energy resolutions from around 145% to 11%.
As the photon detection efficiency is a function of wavelength, the energy resolutions possible are
dependant on the scintillator crystal used. The highest PDE for the SPMs is at a wavelength of
approximately 470nm [19], corresponding best to BGO (480nm) and worst for CsI(Tl) (565nm).
69
However, the much lower light yield of BGO compared with CsI(Tl) means that the best modelled
energy resolution still occurs using the CsI(Tl) crystal.
Figure 4-28: Results for the modelled energy resolutions for each crystal and SPM over the
energy rage to be tested. Clockwise from top left: CsI(Tl), BGO, LYSO and CdWO4.
These modelled results correspond well with knowledge of the materials and the system, as the
scintillators with the highest light yield provide better energy resolutions. The model also shows how
the energy resolution improves with increasing source energy (more light flashes are produced).
Spectroscopy is at least theoretically possible based on these calculations especially at higher energies,
as some energy resolutions are estimated to be less than 20%.
In each case the energy resolution was modelled to be best for the 3mm 35μm SPM, as from the theory
the PDE is highest with this SPM, followed by the 3mm 20μm SPM with the 1mm 20μm SPM
consistently providing the lower energy resolutions as it has the lower PDE and smallest active area.
The energy resolution was found to vary with the square root of the energy was successfully verified
for the model, and the modelled results were compared to those measured experimentally.
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Scintillator and SPM: Preliminary Test Results
Figure 4-29: The 1mm SPM pulses with no sources present seen in oscilloscope mode on the DAQ
(left) and expanded on another oscilloscope showing distinguishable dark photons (right).
Figure 4-29 (left) shows „levels‟ of pulses are present, which correspond to optical cross talk and
individual photons are clearly visible on the 1mm SPM Figure 4-29 (right).
Figure 4-30: The dark counts in the 3mm 20μm SPM (top) and 3mm 35μm SPM (bottom),
showing noise photons not as clearly defined as the 1mm SPM.
The rate of the dark photons is known to depend on the SPM size, with the 3mm SPMs having a dark
rate 9 times as high. From Figure 4-29 and Figure 4-30 the dark rate can be approximated as; 1mm
SPM at 3MHz and 3mm SPM at 6MHz, proving the 3mm SPMs have a higher dark noise rate.
LED Testing
Preliminary tests explored the pulses produced by the SPM when subjected to light from LEDs. It was
found that the circuit using transistors and capacitors instead of a 555 IC took much longer to switch on
71
(microseconds compared to nanoseconds with visible capacitor charging seen on the graphs) and
therefore the SPM response was also much slower (average of 95ns) so these results were not included
in Figure 4-32. All three SPMs respond to the LED circuits with a large negative pulse in the order of
volts (the maximum possible is 2V from the board [33]).
Figure 4-31: 3mm 35µm SPM at 32V bias using the 555 IC timer (left) and 3mm 35µm 32V
(right) for an LED pulse where the SPM response (pink) to the LED pulse (blue)
The time for the SPMs to change state from off to maximum pulse voltage (Figure 4-32) is between 10
and 15 nanoseconds which corresponds well to the 12ns stated [33]. (The errors were found using the
smallest measurable scale on the oscilloscope printouts).
Figure 4-32: The onset times of all three SPMs using pulsed LED circuits to show that the pulses
are indeed produced in around 12ns.
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Figure 4-33: A pulse caused by the pulsing of a red square LED, with black tape around the four
exposed sides on the 1mm SPM.
The SPM pulses caused by the LED photons are much slower (as they are on for µs which is similar to
the scintillator crystal decay time) compared to the dark noise photons which are present for
approximately 50ns. The amplitude of the pulses are also quite different, as the dark noise photons are
approximately 18mV at the 30V bias, whilst the LED pulse causes the SPM to produce voltages of
over 1.5V where the noise is only 1%. The SPM pulse output was measured for LED pulse durations
of 0.5, 1, 2, 4 and 12.5μs using a 3mm round red LED.
Figure 4-34: The SPM response to an LED pulse not fully recorded.
From these LED measurements, an important though unexpected result was found (Figure 4-34). The
SPM response to the LED pulse does produce the maximum pulse voltage for the whole duration of the
LED pulse. After discussions with the manufacturer this was found to be due to the Alternating
Current (AC) coupling, a feature of the pulse pre-amplifier board, which is more evident for the larger
pulse durations (>1μs), as these are not fully recorded. Using an alternative board, a „transimpedance
amplifier‟, would allow much longer light signals to be recorded. (One was received on 25/11/07.)
73
This was a useful experiment to conduct, as;
It was confirmed that the SPM produces pulses in response to optical photons;
The size and duration of the pulses was identified which helped locating the output from the
scintillators;
The AC coupling due to the preamp board was identified where the full light pulse is not
completely recorded by the SPM.
Components were chosen to allow the LED to pulse at the maximum speed of the IC, with the LED on
for 0.2µs and off for 5µs. As each LED pulse was clearly registered by the SPM, by producing a large
negative pulse, it is seen that the count rate of the detector is at least 2x105Hz. However, this is
severely limited by the maximum rate the circuit could pulse the LED at due to the IC used, and the
detector is able to quoted to be able to count at 10MHz [22].
Figure 4-35: The counting of the SPM to be at least 2x105Hz.
SPM Pulse Linearity
As the resistance to an LED was increased, the power was reduced, decreasing the number of photons
emitted. Figure 4-36 shows the linear (with a high goodness of fit) decrease of the SPM voltage pulse
with the increasing resistance in series with the LED.
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Figure 4-36: The effect of resistance (and therefore LED power from the 555IC timer) on the size
of the SPM pulses produced.
This confirms that the SPM response is linear with resistance (directly affecting the power which is
directly proportional to resistance) applied to the LED, which means for any future measurements,
principally spectroscopy, the SPM response the amount of light incident (energy) is directly
proportional to the SPM voltage produced.
SPM Pulse Observations
The output pulses from the SPMs were viewed on an oscilloscope and printed for many SPM, crystal
and source combinations to provide the DAQ with the correct settings required for spectroscopy.
Figure 4-37: A scintillation pulse from the 3mm 20µm SPM (at 32V bias) using CsI(Tl) with the 22
Na source.
Figure 4-37 shows the pulse from a CsI(Tl) crystal using the energy from the
22Na source with a very
clear 1μs decay time as expected from the crystal details value in Table 2-1. The SPM (for these times)
75
responds for the correct duration. There is also a trend for the voltage of the SPM pulses to reduce with
the decreasing source energy as expected from the decreased light yield produced. The exception to
this are the pulses from 22
Na, which appear higher than the other sources. The cause of this is so far
unknown.
Figure 4-38: A comparison of the voltage pulses from scintillator crystals and sources using the
3mm 20μm SPM at 32V.
LYSO pulses are not present in Figure 4-38 as the pulses from the natural radioactivity were not
distinguishable from those caused by scintillation flashes on the oscilloscope. (Background
measurements were made to confirm that the spectra obtained were from the γ-sources and not
background from Lutetium). The pulses from the CdWO4 crystal were found to have a shorter decay
time than those stated when looking at the light pulses produced by the SPM. From the previous LED
measurements, it is know that longer light pulses over about 1μs are not fully recorded due to the pulse
amplifier board used for pulses, hence the incorrect display of the longer scintillation pulses.
Figure 4-39: The CdWO4 response to 22
Na on the 3mm 20μm SPM, the decay lasting much less
than the 20µs expected.
2µs
200mV
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A transimpedance amplifier will reduce this effect, and the longer pulses will be retained. A
measurement was made using the 3mm 20μm SPM with a pulsed LED using this new amplifier (Figure
4-40).
Figure 4-40: Comparing the response of the pulse preamplifier which cuts off the full pulse
duration (left) with the transimpedance amplifier (right).
The SPM responses to the pulsed LED using the transimpedance amplifier allow the full duration of a
long (18μs) pulse to be recorded (Figure 4-40 right), where the negative „well‟ created by the SPM
does not stop until the signal from the LED pulse stops. For comparison, the original board (Figure
4-40 left) shows the cut off effect on much shorter pulses. The use of different boards will therefore
affect the energy resolution possible from the spectroscopic measurements for scintillator crystals with
a longer decay time, as only a fraction of the light will be recorded.
By measuring the size of the voltage pulses produced by the SPMs at two voltages (30 and 32V), it was
found that an increase in SNR (Equation 33) was achieved in pulses from the 1mm to the 3mm (20μm)
SPM and a further increase from the 3mm (20μm) to the 3mm (35μm) SPM. The SNR (Figure 4-41) is
not as high with the bias increase, although the much larger signal pulses (~1V) arise from the photons
from the scintillator crystal which are more easily detected by the acquisition system. (A threshold was
set such that the system records values greater than or equal to this value, which can be observed by
viewing the event rate and increasing the threshold to suppress the noise).
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Figure 4-41: The effect of bias on the SNR for each SPM.
SPM Spectroscopy
Following the modelling and characterisation experiments using LEDs, the arrival of scintillator
crystals allowed spectroscopic experiments to begin leading to dozens of measurements, the results of
which are summarised graphically and in Table 4-5. Due to the ambitious number of measurements
designed to fully test the SPM system, and the scintillator crystals and 3mm SPMs not arriving until
mid-October, spectra were limited to 30 minute integrations to allow for as many tests as possible to be
conducted. (This was in addition to the time required to trial a range of rise times and gains, and
physically setting up each experiment by coupling the detector to the power boards, coupling the
scintillator to the SPM and adjusting the bias where necessary).
The acquisition system used was primarily a way of collecting the data, rather than for complex
analysis of the spectrum. The energy of only one peak can be entered at a time (to provide the energy
resolution of, or the number of counts in, the energy peak). However, when selecting a peak as a
region of interest (ROI) it can be seen that the peak shifts left when decreasing energies are applied and
spectra collected, and approximate values for the centre of the peak are displayed based on the energy
of the one ROI.
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Figure 4-42: The energy spectrum using CsI(Tl) with the 22
Na source, providing an energy
resolution of 14% using the 3mm 35μm SPM.
An energy spectrum from the SPMs is shown in Figure 4-42 for the
22Na source and the CsI(Tl) crystal.
Following a well defined peak at 511keV, the Compton continuum continues due to portions of the
1274keV peak not being fully recorded in the scintillator until 1274keV. Better energy resolutions
were occasionally found using the 22
Na source in place of the 137
Cs source despite its lower energy,
which corresponds with the larger pulses seen when using the oscilloscope in earlier measurements.
Some of the experiments matched very well with the model, which predicted several outcomes:
One of the best energy resolutions possible was found using the 3mm 35μm SPM (with the
higher PDE) and the scintillator crystals with the highest light yield. This was measured and
an energy resolution of 11.78 0.03% was found for CsI(Tl) (predicted value 10.98%);
The best energy resolution comes from the 3mm 35μm SPM for all measurements (due to the
higher PDE), which was found to be the case for most measurements (Table 4-5);
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Figure 4-43: The modelled energy resolutions (top) and measured average energy resolutions
using CsI(Tl) for each SPM (bottom).
The best energy resolution occurs at 662keV.
This was found to be the case for many measurements (see Table 4-5) as more charges are created per
event reducing the statistical broadening of the energy peak, increasing the energy resolution.
Some combinations produce values for energy resolution of over 100%.
The model predicted that there would be some experimental combinations using BGO and CdWO4 and
the lower energy γ-sources that would provide such a low light output that energy resolutions would be
as high as 145%. Poor energy resolutions were experimentally verified using these crystals such that
BGO on the 3mm 20μm SPM gave an energy resolution of 126 2% when using the 241
Am (59.keV)
source. Having an energy resolution of more than 126% at 59.5keV means that an energy range of
76.2keV either side of the energy peak is required to resolve additional peaks.
Figure 4-44: An energy spectrum from the 3mm 20μm SPM using BGO and 137
Cs.
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The linearity of the detector, in terms of number of counts received with increasing time, was explored
for the SPMs by measuring the maximum number of counts of the energy peak in two separate
experiments; using the 3mm 20μm SPM with CsI(Tl) and the 137
Cs source, and the 3mm 35μm SPM
with BGO and the 22
Na source.
Figure 4-45: Two separate SPM linearity experiments; using the 3mm 20μm SPM with 137
Cs and
CsI(Tl), and the 3mm 35μm SPM with 22
Na and BGO.
As can be seen in Figure 4-45, there is a linear increase with a high goodness of fit for the increase in
the maximum number of counts with time for two different sources and SPMs. This shows the stability
of the detector over time and that there is no measured random counting drift in the detector in this
range.
Energy (keV) 59.5 122 511 662
Average Measured Energy
Resolution (%) 126 2 82.7 0.2 25.0 0.1 19.9 0.5
Root Energy Result 118.4 88.0 40.4 22.0
Modelled 122.5 85.9 42 36.9
Table 4-4: A close match for the measured values to that expected from the model for energy
resolution measurements.
In many cases, the measured energy resolutions were a close match to those modelled and those
predicted using Equation 20, for the measured energy resolution varying with root of the energy, as
seen in Table 4-4. In this example, at 511 and 662keV the energy resolutions were better than
predicted, so the scintillation losses may not have been as poor as initially predicted.
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Plotting Equation 21 (Figure 4-46) shows a linear relationship is present when selected energy
resolutions are chosen, and therefore Equation 20, stating that energy resolution is proportional to root
energy is verified.
Figure 4-46: A ln-ln plot of energy vs. energy resolution using BGO on the 3mm 35μm SPM.
The very poor energy resolutions obtained for the CdWO4 crystal have been attributed to the pulse
amplifier which has been used in place of a transimpedance amplifier (which would be more
appropriate for the longer sized pulses). The decay time of CdWO4 is approximately 20μs where
nearly all of the light pulse from the crystal is not recorded using the pulse amplifier.
Figure 4-47: The average measured energy resolution results using BGO, LYSO and CsI(Tl)
scintillator crystals on the 3mm 20µm SPM.
Due to very poor energy resolutions measured using CdWO4, the values have been removed from
Figure 4-47 to avoid distorting the values recorded using the other scintillator crystals. For the 3mm
20µm SPM, the best energy resolutions come from the LYSO crystal providing better energy
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resolution at higher energies. This is thought to be due to the much faster decay time being better
suited to the amplifier used with the SPM for these measurements. With the transimpedance amplifier,
it is expected that the energy resolution for the CsI(Tl) crystal will provide the best energy resolutions
overall based on the better light yield, as previously modelled.
Figure 4-48: The average measured energy resolution results from several scintillator crystals
coupled to the 3mm 35µm SPM.
Figure 4-48 shows how the overall trend for the improvement in energy resolution (%) is followed with
increasing energy. LYSO provides the better energy resolution for the 3mm 35µm SPM at the two
lower energies, however, as predicted by the model, the best energy resolution on the 3mm 35µm SPM
is found using CsI(Tl) crystal at 662keV.
Comparing the 3mm 20μm and 3mm 35μm SPMs (to identify the effect of the number of microcells
changing the PDE), shows that in nearly all of the measurements the average energy resolution (from
two measurements) is improved for the 35μm SPM, which is due to the higher PDE in this SPM. The
LYSO crystal is able to offer comparable energy resolutions to CsI(Tl) at higher energies even with its
lower light yield, which has been attributed to LYSO‟s much quicker decay time.
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Figure 4-49: The average measured energy resolution results for the CsI(Tl) scintillator crystal
compared to the modelled result for the 1mm SPM.
Figure 4-49 shows the energy resolution improving with source energy for the 1mm 20µm SPM for the
modelled values and those found experimentally. The energy resolutions achieved are the poorest of
all three SPMs using the 1mm 20µm SPM (as predicted by the model). This is likely to be a
combination of the crystal size mismatch causing approximately 1 in 9 of the photons to be incident on
the SPM area, the lower PDE and lower active area. It was found that the 3mm 20μm SPM provided
better energy resolutions than the 1mm 20µm SPM (for all but the 122keV source energy).
Due to the mismatch in scintillator and SPM area for the 1mm SPM, the model estimating the energy
resolution was modified, allowing for only 1 in 9 scintillation photons reaching the SPM for the CsI(Tl)
crystal. It was found that the measured energy resolution fits between both the modelled energy
resolutions, where it is assumed that areas match completely, and the other model (labelled modelled
1/9th ER) where only 1 in 9 photons reach the SPM. As the model has been proved to work well for
other combinations of SPM and crystals, it is reasonable to assume that the mismatch has caused the
loss of some, but not as much as 1/9th of the light emitted by the crystal as seen in Figure 4-50.
Figure 4-50: The measured energy resolutions with the 1mm SPM and the modelled results based
on a complete match in areas and at a 1/9 area match.
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One of the project aims was to determine the difference in the energy resolution between the three
SPMs, therefore comparing the different pixel sizes and the two fill factors. Figure 4-51 shows how
the measured energy resolution varies for the same scintillator crystal (CsI(Tl)) using each of the three
SPMs. It is clear for each SPM that the increase in energy resolution is gained with increased energy.
Additionally, the best energy resolution is found using the 3mm 35µm SPM, followed by the 3mm
20µm and finally the 1mm 20µm SPM (in all but 1 case) matching with the predictions.
Figure 4-51: A comparison of the measured energy resolutions for the three SPMs using all of the
sources on the CsI(Tl) crystal.
Using Equation 20, the energy resolutions of various combinations of scintillator and SPMs were
extrapolated to provide the expected energy resolution at 140keV, the energy used in SPECT imaging.
The results in Figure 4-52 show that the energy resolutions at this energy are unlikely to be better than
30% for any combination, which means that other energy peaks can be resolved above 180keV or
below 100keV. With this large dynamic range, it is seen that using SPM technology at two important
energies, 140 and 511keV, can be both simultaneously and separately recorded at a very high photon
counting rate.
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Figure 4-52: The extrapolated energy resolution (based on measured results) to 140keV for eight
scintillator and SPM combinations.
The measured SPM energy resolution never reached the current performance possible using PMTs, or
those experimentally found using a different semiconductor detector (CZT). However, the testing of
this technology has proved that spectroscopy is possible. Their size and gain make them a serious
contender for low power, light weight, fast counting passive γ-ray detectors.
3mm 20µm 59.5keV 122keV 511keV 662keV
CdWO4 343 0 175 37 38 5 36 2
BGO 126 2 82.7 0.2 25.0 0.1 19.9 0.5
LYSO 62.3 0.7 57 3 10.6 0.1 12.9 0.5
CsI(Tl) 104 1 64 3 23 2 17.3 0.8
3mm 35µm
CdWO4 0 0 0 0 25.75 0.02 35.3 0.1
BGO 0 0 72.9 0.1 34.9 0.4 18 2
LYSO 54.6 0.3 31 3 61.6 0.3 42 2
CsI(Tl) 62 16 46.7 0.4 14.0 0.2 11.78 0.03
1mm 20µm
CsI(Tl) 0 0 51.8 0.8 35 2 28 2
Table 4-5: The average measured energy resolutions (%). (Errors at the 95% confidence level).
A summary of the measured energy resolutions obtained and the corresponding error at the 95%
confidence level is displayed in Table 4-5. (A value of 0 indicates that no measurement (or repeat) was
possible for this experimental arrangement.)
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Observing Complex Spectra using SPMs
To observe complex spectra, the same experimental setup was used for the SPM spectroscopic
measurements but with an additional source near the scintillator when required. A series of
experiments was conducted to identify the effect on the energy spectrum produced when simultaneous
sources are incident on the scintillator crystals coupled to the SPMs (CsI(Tl) on the 3mm 35μm was
initially tested as it provided among the best energy resolutions in previous measurements). Integrating
briefly for two minutes using 137
Cs in the standard experimental setup (Figure 3-17) produces the
spectra in Figure 4-53 (left) and adding 241
Am (placed several cm further back from the crystal to avoid
saturation) provides Figure 4-53 (right).
Figure 4-53: A 137
Cs Spectrum for two minutes on the 3mm 35μm SPM (left) and the effect seen
when 241
Am (further back at 5cm) from the crystal is added to the experiment (right).
Higher attenuation of photons occurs at lower energies (Figure 2-20), causing many more counts to be
recorded at lower energies (photons are more easily stopped). Counts at higher energies occur less
frequently and are not visible on the energy spectrum if a low energy source is placed at a similar
distance to a higher energy source. This was found experimentally to be the case. By replacing the
241Am source by
57Co a γ-peak should be found at higher energy than the
241Am peak at 59.5keV. This
was successfully found, as is displayed in Figure 4-54.
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Figure 4-54: The 122keV peak clearly to the right of the cursors showing the position around the
59.5keV peak.
The 136keV peak from the 57
Co source is not visible in any of the SPM measurements, due to the poor
energy resolutions obtained from the experimental equipment. (An energy resolution of 50% at 122keV
means that another peak could be resolved at 122 61keV, where to resolve a peak at 136keV, an
energy resolution of 11% at 122keV (or better) is required, hence it is visible on the CZT detector).
Peaks corresponding to high and low energy sources are clearly distinguishable in the same energy
spectrum based on Figure 4-54.
When using both the low energy sources (59.5 and 122keV) together, the peaks are not as
distinguishable due to the large energy resolutions achieved (Table 4-5).
Figure 4-55: Illumination with 57
Co (left) and both 241
Am and 57
Co (right) showing a broadening
due to the 59.5keV source from 33% to 52% at 150 counts.
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An increase in the broadening of the peak (by 57%) is detected (Figure 4-55) but the energy resolutions
are so large that the peaks at 59.5 and 122keV cannot successfully be resolved. Using both high energy
sources (511 and 662keV) together allows some indication that additional peaks are present due to
better energy resolutions at higher energies (Figure 4-56 and Figure 4-57).
Figure 4-56: Both high energy sources (511 and 662keV) when integrating for two minutes.
Figure 4-57: The energy spectrum for 22
Na (511keV) without the 662keV source, the peak is
missing when integrating for two minutes.
Using BGO with 137
Cs for two minutes on the 3mm 35μm SPM provides a definite spectrum with a
clear peak at 662keV from the 137
Cs source is visible.
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Figure 4-58: BGO with 137
Cs for two minutes on the 3mm 35μm SPM.
By adding 22
Na to the experiment, after two minutes neither the 511 nor 662keV peak is well resolved
but the continuum due to the 1274keV peak continues from the 22
Na source in Figure 4-59.
Figure 4-59: The addition of 22
Na to the 137
Cs source for two minutes.
By integrating for 30 minutes, a better defined spectrum is produced (Figure 4-60) which shows the
662keV peak sitting on the 511keV peak and again the continuum present until the peak at 1274keV
from the 22
Na source.
Figure 4-60: Integrating 22
Na and 137
Cs for 30 minutes better defines the spectrum.
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Figure 4-61: The beta spectrum from LYSO taken for 30 minutes with no additional radioactive
sources using the 3mm 20μm SPM.
Figure 4-61 is the naturally occurring radioactive energy spectrum from the Lutetium in the LYSO
scintillator showing a low level background always present with this crystal as predicted. The effect is
negligible compared to the peak source energies.
SPM Detection Time
In most detection applications, the faster the detection time the better. The time taken to produce an
energy spectrum using the 3mm 35μm SPM and the CsI(Tl) crystal with 57
Co (closest energy for
SPECT imaging) was explored (Figure 4-62). This verifies the uniform counting of the detector over
the time and energy ranges explored. In just 10 seconds, over one thousand counts are in present the
122keV energy peak allowing identification that the energy is present.
Figure 4-62: The linear increase of counts with integration time for the 3mm 35µm using 57
Co
and CsI(Tl).
91
Extrapolating the best fit line in Figure 4-62, an energy peak with 1000 counts at 122keV would be
present in less than 10 seconds. The closeness of the energies between 122 and 140keV allows
comparisons to be drawn to SPECT medical detection of 140keV, where rapid detection of this energy
would be possible using SPMs and scintillator crystals.
SPM Efficiency Results
For the 3mm 35μm SPM, the trend was successfully identified that as the source energy increases, the
detection efficiency decreases. This corresponds with Figure 2-20, where fewer photons are attenuated
at higher energies.
Figure 4-63: A comparison of the system efficiencies for each SPM using CsI(Tl).
Figure 4-63 displays the measured detection efficiency of the three SPMs using the CsI(Tl) crystal,
showing how the efficiency decreases with increasing source energy (as expected). The attenuation
data (curve labelled CsI Att) shows how the ideal attenuation in the crystal over the energies should
decrease with increasing energy. It is seen that the experimental observations follow the predicted
outcome where the efficiencies reduce with increasing energy. However, the measured observations
show lower efficiencies than the ideal curve. Possible reasons for this include the loss of photons from
any slight mismatch of the alignment of the scintillator crystal to the SPM, and absorption of photons
in the silicone grease between the scintillator and SPM, which would cause fewer photons to be
detected by the SPM. To improve this setup the scintillators would be coupled directly using superior
optical grease and the crystals would be perfectly matched to the SPM area to maximise the efficiency.
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Chapter 5 : Review, Conclusions and Further Work
6.1 Conclusions
Over the course of the M.Phys. placement year, research was performed mainly at the Dstl laboratory,
exploring radiation detection. Modelling the attenuation of transmission X-rays for a range of
materials was undertaken initially, showing the distinct difference between metals and organics. This
followed a review of the different detection techniques which populated a graphical model to provide
information on where the research would be useful, principally in identifying the spectroscopic
performance of radiation detectors. CZT detector preparation and characterisation experiments were
conducted to gain an understanding into detector theory and application.
The main aims of this project were to determine and quantify the performance of the CZT and SPM
detector systems as new detectors for spectroscopy and imaging. This is of great importance as
spectroscopic information provided by γ-detection and could provide the possibility for material
discrimination based on the energy of the material present. This could have an impact in medical and
security applications.
An ICCD detector was unable to provide any spectroscopic information, but was used as a basis of
comparison to the CZT detector for the backscattered X-ray images. When directly comparing the
ICCD detector to the CZT for X-ray backscatter imaging, it was seen (Figure 4-26) that the CZT
detector provides lower noise and better object to background ratios (Figure 4-20). The ICCD detector
is quite long about 0.6m, whereas the CZT detector is only 0.25m thick with the specifically produced
shielding applied. An SPM could further reduce this thickness to less than 5cm including a scintillator
crystal. An array of SPMs to cover the area of the current ICCD detector could provide a thin
lightweight alternative to both the CZT and ICCD detectors, to provide imaging and spectroscopic
information with the ability to be a fast counting passive γ-detector.
The energy resolution of the CZT array, required to identify how well close peaks can be resolved, was
quantified before and after a hardware upgrade, which identified an improvement in the energy
resolution using two different γ-sources. It was found that the CZT detector provides excellent energy
93
resolution of 4% at 122keV allowing direct application as a γ-ray detector which is very close to the
energy of the γ-line used in SPECT imaging for medical applications. The inverse square law for the
decrease in radiation with increased distance was verified for the CZT detector array when several
distances (15 to 30cm) were tested with a range of integration times (1 to 10 seconds). The linear
increase of the counts with time was also verified, proving the detector‟s stability.
To use the CZT detector array as a pinhole imager, the thickness of different Z materials was calculated
to provide shielding only allow X-rays through the pinhole. Pinhole imaging using the CZT detector to
detect X-ray backscattered photons demonstrated the concept worked for both the ICCD and CZT
detectors. The images produced from the X-ray backscatter experiments show that without image
processing (by flat fielding) the ICCD detector produces images which are initially clearer due to the
large number of smaller pixels. After flat fielding, the CZT images are made clearer, with the effect of
flat fielding being more pronounced for the CZT detector (as seen in the change in uniformity before
and after the flat field corrections were applied). Unfortunately, the graded shielding manufactured,
requires additional lead to prevent the bright spots seen in the CZT images. An optimum configuration
using extra lead required to prevent these spots was used for the measurements and will be used until
the shielding problem is fixed. From the backscatter measurements, the larger pixel size of the CZT
was found to provide better sensitivity, shown as a lower background noise (at least 10% less than the
ICCD detector where no object is present) and a better object to background ratio than the ICCD
detector when using the same experimental setup.
By determining the number of counts detected, the efficiency of the CZT detector was determined.
The highest efficiency of the CZT detector was found to be 70 1 % (at 59.5keV) which is lower than
expected based on the attenuation of the γ-ray photons over the 200keV energy range explored. This is
possibly due to attenuation in the thin carbon window on the aperture, or the 5mm thickness not fully
depleted and able to attenuate and detect radiation photons. Considering the spectroscopic energy
resolution and detection efficiency, this detector was found to have many useful application areas, and
has been shown to be successful as a high energy resolution passive γ-ray detector, and as an active
imager for X-ray backscatter measurements.
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Testing on novel SPMs initially involved modelling how the energy resolution varies when using
different sized SPMs with four scintillator crystals and four radioactive sources to activate the crystals,
to explore the possibility of spectroscopy. The model showed that energy resolutions of less than 15%
(and more than 140%) would be possible with some combinations of scintillator crystals, SPMs and
radioactive sources with improving energy resolutions at higher energies.
A vast amount of testing was then performed on novel SPM detector systems providing several key
findings:
The pulse output is directly proportional to the amount of light incident on the SPM
with direct application to radiation spectroscopy, where increased energy will
linearly produce more scintillation light;
The decay constant of the crystals can be accurately seen using the SPM when
exploring the short scintillation (< 1µs) pulses on an oscilloscope;
The pulse preamplifier board used for the SPM measurements is unsuitable for longer
(>1μs) light pulses and at the time of writing a new amplifier arrived which was
proved to work with longer light pulses;
Spectroscopy was found to be possible for various combinations of SPM and
scintillator sources over a wide range of γ-energies. There are direct comparisons
between the model predicting the energy resolutions, and with the spectroscopic
measurements made. Energy resolutions were measured to be from 11% up to
approximately 175%;
When more than one source is used on the scintillator and SPM combination, it was
found that the peaks corresponding to two sources are clearly distinguishable when
large source energy separations are used. The resolution of close peaks is more
difficult, and in some cases impossible with similar energies due to the poor energy
resolutions found previously;
The SPM detectors were shown to count linearly with increasing integration time
using two different SPMs and different scintillator crystals;
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The detection efficiency was found to decrease with the increasing source energy as
expected from the modelling of the crystal attenuation modelling. The best SPM
detection efficiency was measured to be 65 1%.
Currently the size limitation of the SPM being only several millimetres, ensures that PMTs are still the
standard for detection of light from scintillator crystals for the majority of applications. However, the
development of arrays of SPMs is underway [17].
According to [6] the energy resolutions achievable using a PMT are 8.5% at 122keV using a NaI
scintillator. Using Equation 20, this extrapolates to an energy resolution of 3.6% at 662keV. The SPM
spectroscopic measurements never matched or improved upon these values however, the best possible
energy resolution did match closely to that modelled proving the SPM detector concept.
Detector Comparison
The pixel pitch of the CZT detector used is 1.6mm which produces coarser images than the ICCD
detector (pitch is 0.5mm). An array of SPMs scaled up to the size of the CZT would have about 870
3mm pixels where the CZT has 6400, and therefore any possible images would be very pixellated
compared to the CZT reducing the spatial resolution. A single 3mm pixel of SPM can count photons at
10MHz which means the 870 pixels able to fit in the area of the CZT would be able to count at about
9GHz, where the same area of CZT is able to currently count at only 100kHz. However, saturation
occurs at fewer counts per pixel on the SPM as this is limited to the number of microcells. Based on
the number of microcells in the 3mm 35μm SPM (providing the best energy resolution), an array of
these SPMs made to the same area as the fully populated CZT detector would be able to detect just
over 3 million simultaneous photon interactions; thirty times more than the CZT detector currently can.
The energy range of the CZT detector used is currently limited from 0-200keV, whereas the SPM has
so far successfully detected from 59.5keV up to 1274keV providing a much larger dynamic range.
However a comparison between the best obtainable energy resolutions (Table 5-1) for two energies
shows that the CZT is far superior (Table 5-1) to the SPMs at both energies.
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Detector Best Energy Resolution at
59.5keV (%)
Best Energy Resolution
at 122keV (%)
SPM 55 32
CZT 8 4
Table 5-1: The best obtainable spectroscopic energy resolutions (nearest %) for the two detectors
at the same energies.
The detection efficiency of the CZT detector (Table 5-2) was found to be 6% above the value obtained
for the SPM using CsI(Tl) at the using the same 59.5keV source, showing that both detectors are able
to successfully attenuate photons in the 59.5-122keV energy range. This was predicted from the
attenuation curves, where CsI is able to attenuate slightly less over the energy range with comparable
detection efficiencies.
Detector Best Efficiency at
59.5keV (%)
SPM 65
CZT 71
Table 5-2: The best obtainable detection efficiencies (nearest %) for the two detectors at the same
energies.
Creating an array of 1mm SPMs could provide better spatial resolution that the current CZT provides
are smaller pixels would be used, however, as seen from the spectroscopic results, this would be at the
expense of energy resolution, as the 1mm SPM provided the poorer energy resolutions.
6.2 Further Research
Many measurements were made using both the CZT and SPM detector systems. Due to time
constraints with the equipment, it was not possible to explore as many combinations for spectroscopy
as planned earlier in the year. With more time, a complete comparison with the modelled results
(particularly with the 1mm SPM) would be possible, as with any imaging device, the smaller the pixel
size, used the more coarse the image will be as seen in the images between CZT and ICCD.
Experimentation with a newly available 16 3mm pixel SPM array (Figure 5-1) will allow a small area
imaging device to be tested (to be connected to the 16-channel acquisition system) to determine the
spatial resolution and sensitivity of a new spectroscopic imaging detector. This array would allow a
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wider area detector, capable of imaging to be tested for sensitivity for comparison to the CZT and
ICCD for image quality.
Figure 5-1: An array of 16 3mm pixel SPMs [34].
Obtaining an LED pulser should allow the single photoelectron spectrum for each SPM to be collected
to determine the SPM gain. This will provide a direct comparison with PMTs which have well
researched gain of the order of 106.
Repeating all of the spectroscopic experiments with the new transimpedance amplifier (in place of the
pulse preamplifier supplied) should improve the energy resolution for the slower scintillator crystals
(CsI(Tl) and especially CdWO4) and provide another comparison to the PMT energy resolutions.
Further exploration of the lower than expected CZT detector efficiency is required to identify if the full
5mm thickness of the CZT detector is able to detect photons. Additionally, calculating the attenuation
in a carbon window protecting the CZT, to identify if this is the cause of the efficiency loss.
In conclusion to this research project, characterisation experiments of the CZT and the SPM detector
systems was conducted providing key findings to the department. This research project has been
exceptionally interesting to explore over the placement, and it is hoped that the research conducted will
continue to be of use to both the department and the wider physics community.
98
References The sources, including books, papers and technical data sheets, which have been referred to throughout
the research project are listed below.
1. www.dstl.gov.uk, January 2007
2. Explosive detection systems (EDS) for aviation security, Sameer Singh et al., Maneesha, 2002
3. Introductory Nuclear Physics, Kenneth Krane, 0-471-80553-X
4. Fundamentals of Physics, 6th Edition, Halliday / Resnick / Walker, 0-471-39222-7
5. Oxford Dictionary of Physics, 2003, Oxford University Press, 0-19-860759-8
6. Radiation Detection and Measurement, 3rd Edition, G. F. Knoll, 0-471-07338-5
7. http://bioeng.berkeley.edu/budinger/xraytransmission.html, October 2007
8. Principles of Physics, M. Nelkon, 8th Edition, 0-582-05416-8
9. Properties of Narrow Gap Cadmium-based Compounds, Inspect publication, IEE, 1994, p589 10. Evaluation of a CdZnTe pixel array for X- and γ-ray spectroscopic imaging, F. Quarati et al., 2006
11. Digital Camera Fundamentals, www.andor.com , December 2007
12. http://www.hilger-crystals.co.uk/properties.asp?material=7, December 2007
13. Physical properties of Common Inorganic Scintillators, Saint-Gobain Crystals,
(http://www.detectors.saint-
gobain.com/Media/Documents/S0000000000000001004/SGC_Scintillation_Properties_Chart.
pdf)
14. High-Energy Photon Detection with LYSO Crystals, R.W. Novotny et al., 2006
15. Scintillation: mechanisms and new crystals, M.J. Weber, 2004
16. The quest for the ideal inorganic scintillator, S.E. Derenzo et al., 2003
17. Tiled Silicon Photomultipliers for large area, low light sensing applications, P J Hughes et al.,
SensL, 2007
18. First Results of Scintillator Readout With Silicon Photomultiplier, Deborah J. Herbert et al.,
2006
19. SPM Photon Detection Efficiency Technical Note Rev 1.3, SensL, August 2007
20. http://www.sensl.com/Products/03Silicon_Photomultipliers_-_High_Gain_APDs--
SPMScint_High_Performance_SPM_for_Radiation_Detection.html, November 2007
21. Study of the Properties of New SPM Detectors, A G Stewart et al., 2006
22. Introduction to the Silicon Photomultiplier Technical Note, SensL, Rev1.0 August 2007
23. The Silicon Photomultiplier for application to high-resolution Positron Emission Tomography,
D.J. Herbert et al, 2006
24. The Expression of Uncertainty in Testing UKAS Publication ref: LAB 12, Edition 1, October
2000
25. TCT characterization of different semiconductor materials for particle detection, J. Fink et al.,
2006
26. Email, 04/10/07
27. Email, 09/10/07
28. http://www.britannica.com/eb/topic-529015/scintillation-efficiency, November 2007
29. Email, 20/11/07
30. Industrial Electronics, Noel Morris, 2nd Edition, 0070842256
31. NE555 precision timer datasheet, Texas Instruments, SLFS022, Revised Feb 1992,
http://docs-europe.electrocomponents.com/webdocs/002b/0900766b8002b5d8.pdf, October
2007
32. http://www.kpsec.freeuk.com/555timer.htm, October 2007
33. SPM Pulse Preamplifier Technical Note, SensL, Rev 1.3, August 2007
34. http://www.sensl.com/Products/05Silicon_Photomultipliers_-_High_Gain_APDs--
SPMArray_Position_Sensitive_Multi_Anode_High_Gain_APD.html, October 2007
35. http://www.shinpoly.co.jp/business/connector/english/product/category/detail/af.html, April
2007
36. http://www.xia.com/DGF_Pixie-4.html, November 2007
37. Email, 22/10/07
38. Study of Cadmium Zinc Telluride (CZT) Radiation Detector Modules under Moderate and
Long-Term Variations of Temperature and Humidity, Gunnar Mæhlum, November 2007
99
Chapter 6 : Appendices
APPENDIX I: OBTAINING A SPECTRUM
Due to the novelty of the acquisition system, a certain amount of “feet-finding” was required, and after
much manual reading, contact with the product manufacturer and general trial and error, the best
procedure for setting up the system was found and can be seen below.
One ‘Quick Start’ method is to load a pre-existing experiment, such as those on the desktop and load the settings (from the ‘Load’ menu on the ‘Settings’ tab). The spectrum can then be refined for the new device by adjusting key parameters. When starting a new series of experiments from a new SPM: 1. Explore the pulses from the detector using an oscilloscope and note the rise time and the decay time.
2. Once logged into the computer, open the "Shortcut to Pixie4" from the desktop. The following screen will appear, and click on 'Start Up System'.
Figure 6-1: The system start-up screen.
3. Once started, the Pixie4 Run Control menu will be displayed, which contains the four tabs (circled in Figure 6-2) to setup the system, and to take and analyse the data.
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Figure 6-2: The Pixie4 Run Control menu.
Settings Tab
Note: If these options are not all visible, you should press the 'More' button on the bottom of the menu. As the SPM produces negative pulses, it is necessary to ensure that the 'Trigger positive button' in the channel menu of the settings tab is unselected. The trigger filter is particularly important and should be set a value such that the MCA is not triggered on the noise pulses. (From the oscilloscope the number of real light pulses can be estimated (<50 per second) whilst the noise pulses are in the MHz region). Calibrate Tab Here, the gain can be adjusted to utilise the full 14-bit dynamic range of the instrument. Values of 1.1-1.3 seem best for SPM spectra. Run Tab
The integration time is set here and after a few minutes, a good indication of the general shape of the spectrum should be produced. Whilst running, you can periodically ‘Update’ the MCA view to view the event rate (in the Analyse tab) and see how the energy spectrum progresses. Analyse Tab Here the number of counts per second is displayed, if this is in the hundreds or higher, for a detector which is known not to produce this number of pulses, the trigger and threshold need to be increased. The rise time value and gain should be adjusted and short (10 minute) runs in MCA mode should be obtained to ensure the peak can be distinguished above the noise. Once these values are optimised, take a longer run (30 minutes) to reduce statistical fluctuations, as more counts will be received. Peak Fitting
On a peak of the observed spectrum, a Gaussian curve can be fitted to an energy peak, from which the energy resolution can be found, select a cursor (a square or a circle) and drag it to
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the left of the peak, and drag the remaining cursor to the right of the peak. Click on the 'Fit’ down arrow and select the channel holding the data (0 or 1 usually). This will provide values for FWHM% and FWHM abs. The FWHM% is the energy resolution. (An automatic should be available in a newer version of the software.)
Figure 6-3: The positions of the cursors to find the energy resolution.
Figure 6-4: The cursors around the peak to provide the energy resolution and value of the peak.
To calibrate the system, the value for this peak can be entered into the ‘Peak’ box (shown in black) for that channel. Attenuation
Jumper settings on the each channel can be used to provide an attenuation of 7.5x if required (for larger voltage pulses) by changing jumper combinations seen in Figure 6-5.
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Figure 6-5: The attenuation jumpers for each channel of the acquisition system.
A jumper on the 50 pins
keeps the input at 50Ohms
(else 5kOhms).
A jumper on the „Attn‟
pins removes 7.5x
attenuation (else there is
7.5x attenuation).
[39]
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APPENDIX II: GMS
GMS allows easily identifiable links between „nodes‟ so the items that are linked can be instantly
identified. When the mouse pointer is held over a box (or node), the box and any links with that box
are illuminated easily showing the links. This makes things easy to see when the screen gets busy with
lots of information. Figure 6-6 and Figure 6-7 are screenshots from a GMS tutorial highlighting the
effect of linking, showing nothing highlighted and then with the mathematics students shown.
Similarly, it can be seen which subjects Mark takes by moving the mouse over his name.
Figure 6-6: GMS with no object selected.
Figure 6-7: Identifying who takes Mathematics by moving the mouse over Mathematics.
Weld View is a piece of software which can easily show the relationships between the quantities in the
GMS model such that they can be read from a grid (Figure 6-8).
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Figure 6-8: The ‘Weld View’ of the Students Tutorial.
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APPENDIX III: Initial Research: Introduction and CZT Resistivity
The following section is based on reports produced during the initial part of the research program.
Gold contacting a CZT sample is performed to connect the sample to a circuit to determine the
characteristics and for practical use of the device (applied voltage required for detector operation). An
experiment explored the use of conducting foam in place of / before gold contacting CZT. It would be
very useful to be able to find the resistivity of a detector sample before the contacting process as
contacting is a costly procedure in both time (taking hours to obtain the correct vacuum for each
contact, where two or three contacts are required in total) and financial benefits (cost of pure gold).
Finding if a sample has a good enough resistivity to continue with experiments before contacting would
therefore be very useful.
Figure 6-9: A schematic of the conducting foam used [35].
A non-contacted CZT sample (about 5x5x1mm) was sandwiched between two separate pieces of
conducting foam, and the current through the sample was measured by applying four voltage ranges in
varying step sizes (Figure 6-10). Resistance was found using the inverse gradient of an IV graph.
With known sample dimensions, the resistivity can be found from Equation 16 to find values shown in
Table 6-1.
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Figure 6-10: The experimental arrangement to find the CZT sample resistivity.
Voltage Range
(V)
Step Size
(V)
Readings
/ Sample
Gradient
(1/Ω)
Resistivity
(Ωcm)
-1010 1 Default 7.44E-12 3.05 0.02E+11
-1010 0.1 Default 8.85E-12 2.57 0.02E+11
-11 0.01 10 1.69E-12 1.34 0.01E+12
-11 0.01 40 1.76E-12 1.29 0.01E+12
Table 6-1: Resistivity values and results from the conducting foam experiment.
Higher than expected values of resistivity were found using the non-contacted CZT sample and
conducting foam. The increase in the resistivity is thought to come from a larger than true value being
used for the area in contact with the needle, as the area of the sample was used in calculations, when
only the area in contact with the foam should have been used. Using a smaller value for the area based
on the size of the needle rather than the whole detector sample in Equation 16 will reduce the
resistivity. The experiments are being performed again based on a known value for contact area of a
larger needle, and a more reasonable (lower than previously found) value for resistivity should be
found. This looks like it may be a promising way to find the resistivity of a sample without the need
for gold contacting providing several key benefits, including the potential for money saving, by making
faster resistivity measurements.
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APPENDIX IV: Experimental Equipment List
The research project required many of the items to be procured by the author taking time for the
ordering (obtaining the specific requirements, specifications and quotations where necessary), in
waiting for the equipment to arrive, and checking the correct equipment arrived. The testing required
different SPMs, radioactive sources, scintillator crystals and an acquisition system to record the pulses
produced.
Silicon Photomultipliers: These were the main emphasis of the testing and three were ordered to
compare both the physical area and the effect of the fill factor in the detector. These were available as
single pixel detectors, in 1mm SPM 20µm fill factor, 3mm SPM 20µm fill factor and 3mm SPM 35µm
fill factor. The SPM detectors of 1mm pixel size provide an area of 1mm2 and for the 3mm the area is
9mm2.
Scintillator Crystals: Four different scintillator crystals were provided as cubes (3x3x3mm) to provide a
range of light yields from 9,000 to 52,000 photons/Mev in decay times from 0.04 to 1µs to fully test the
response of the SPMs.
Data Acquisition System / MCA: The Digital Gamma Finder (DGF) Pixie-4 is a 14-bit digitising
module allowing 4 simultaneous acquisition and analysis of pulse height for each channel. The system
fits in a standard PCI crate and more modules were added together for acquisition of 16 inputs. “Pixie-
4 Viewer is a graphical user interface written using IGOR from Wavemetrics” operating in the
Windows XP (TM) environment makes the easier to use [36].
There are various settings required so an MCA run can be started, which include the signal rise time,
decay time, gain, run time and signal thresholds. Some of these can be found by first exploring the
pulses on a standard oscilloscope. APPENDIX I provides the details to allow an energy spectrum to be
found.
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APPENDIX V: Varying Spectra with Energy
The following figures are the spectra produced from the CsI(Tl) crystal using the 3mm 35µm SPM
using decreasing energies from 662keV (as the main source energy) down to 59.5keV.
Figure 6-11: The change of source energy from 662keV (top) to 59.5keV (bottom).
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These figures clearly show the energy spectra changing with the source energy. As the peak γ-energy
is reduced, the energy peak moves left to reflect this, whilst the decrease in energy causes the peak to
broaden, decreasing the energy resolution.