integration of sipm in a high-pressure noble gas scintillation detector for homeland security

Romualdo Santoro

Università dell’Insubria

Integration of SiPM in a high-pressure noble gas scintillation detector for homeland

security

M. Caccia, V. Chmill, S. Martemiyanov – Insubria

R. Chandra, G. Davatz, U. Gendotti – Arktis

13th Topical Seminar on Innovative Particle and Radiation Detectors (IPRD13) 7-10 Oct. 2013, Siena, Italy

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MODES_SNM

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Modular Detector System for Special Nuclear Material

Approved by the European Commission within the Framework Program 7

The Main Goal is the development of a system with detection capabilities of “difficult to detect radioactive sources and special nuclear materials” Neutron detection with high γ rejection power γ-rays spectrometry

Other requirements Mobile system Scalability and flexibility to match a specific

monitoring scenario Remote control, to be used in covert operations


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Baseline technology

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The Arktis technologies is based on the use of 4He for the neutrons detection

The main key features of 4He Reasonably high cross section for n elastic scattering Good scintillating properties Two component decays, with τ at the ns and μs levels Cheaper and easier to be procured wrt 3He

44 cm diameter x 47 cm sensitive length 180 bar 4He sealed system maintaining

gas purity

R. Chandra et al., 2012 JINST 7 C03035


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MODES_SNM System overview

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Modular system optimized for: Fast neutron (4He) Thermal neutron (4He with Li

converter) Gamma (Xe)

All components are being integrated, we are approaching the

commissioning and qualification phase

With γ-ray spectroscopy

capability


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MODES_SNM R&D

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The project baseline is based on PMTs coupled with scintillating material R&D activities was planned since the beginning to investigate the possibility of

using SiPM as light detector

Why SiPM is so appealing? high sensitivity (single photon discrimination) compactness, robustness, low operating voltage and power consumption low cost


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SiPM

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SiPM is a High density (~103/mm2 ) matrix of diodes with a common output, working in Geiger-Müller regime

Common bias is applied to all cells (few % over breakdown voltage) Each cell has its own quenching resistor (from 100kΩto several MΩ) When a cell is fired an avalanche starts with a multiplicative factor of

about 105-106

The output is a fast signal (Trise~ ns; Tfall ~ 50 ns) sum of signals produced by individual cells

SiPM works as an analog photon detector

Signals from SiPM


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SiPM

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SiPM is a High density (~103/mm2 ) matrix of diodes with a common output, working in Geiger-Müller regime

Common bias is applied to all cells (few % over breakdown voltage) Each cell has its own quenching resistor (from 100kΩto several MΩ) When a cell is fired an avalanche starts with a multiplicative factor of

about 105-106

The output is a fast signal (Trise~ ns; Tfall ~ 50 ns) sum of signals produced by individual cells

SiPM works as an analog photon detector

The selected device is a large area (13.6 x 14.3 mm2) monolithic array of SiPM units produced by Hamamatsu:

S11829-3344M


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Lab charcterization to fullfill the simulation hints

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Minimum detectable light Detector sensitivity (i.e. S/N or capability to

discriminate an “event” against noise )

Model developed by Arktis

We expect 255 photons / matrix for 100 keV deposited energy assuming the 95% of reflectivity


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Lab charcterization to fullfill the simulation hints

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Firing the matrix with a calibrated photon flux, we measured the minimum detectable light a two different temperatures (different performances due to a combined effect of increased noise and gain drift)

≈ 250 ph @ 25°C ≈ 60 ph @ 21.6°C

We expect 255 photons / matrix for 100 keV deposited energy assuming the 95% of reflectivity


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Experimental set-up for proof of principle

A short tube (19 cm) used for the proof of principle

Filled with 4He at 140 bar, an integrated wavelength shifter and two SiPMs mounted along the wall (by ARKTIS)

Two SIPMs read-out through the Hamamatsu electronic board (C11206-0404FB)

2-channels 3-stage amplification with leading edge discrimination (SP5600A – CAEN)

Digitizer with a sampling rate of 250 Ms/s 12 bit digitization (V720 – CAEN)

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Counting measurements

Test performed measuring: Background, n and γ counting rate using 252Cf and 60Co source in

contact

Two triggering scheme: Trailing edge discrimination in coincidence Trailing edge and delayed gate of each single SiPM in

coincidence Few parameters to be optimized:

Leading and trailing threshold Delay time (ΔT) Gate aperture

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1st Trigger Scheme

2nd Trigger Scheme

typical γ event typical n event

Romualdo Santoro


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Counting measurements

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An amazing result, corresponding to a γ rejection power at the 106 level

[ 10 counts in 1000s, for a number of γ given by acceptance*activity*time = 1/3 * 3 * 104 * 103 ~ 107 ]

Result for the different trigger scheme @ 28°C

Romualdo Santoro


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Off-line data analysis

Data recorded with a minimum bias trigger Low threshold on the pulse height discrimination No coincidence between the two SiPMs

For each triggered events we digitize signal of both SiPMs with sample rate of 125 MS/s and a total duration of 4μs.

Three data set:1. 400 events without radioactive sources

2. 6000 events with 60Co source in contact

3. 10000 events with 252Cf source in contact

Analysis strategies: Identify an observable allowing to measure the ratio between noise & particle induced

triggers in samples 2 & 3 Filter noise from particle induced events through a multivariate analysis Identify the ratio between γ and n events in sample 3 Filter γ from n through a multivariate analysis Measure the rejection power of interacting γ and the selection efficiency of interacting

neutronsR. Santoro


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Sample composition: (% of Background and signal)

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Each signal is baseline subtracted in the integrated time windows

FAST and SLOW component is calculated as the integral of the signal to the left / right side of the peakDefinition of Fast and

Slow Component

BKG

Co60

Cf252 The areas underneath the fits are used

to measure sample composition These numbers are used to estimate

the selection efficiency and bkg rejection power


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A multivariate Bayesian analysis

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The strategy:

Select 4 no-correlated variables where bkg, γ and n appear to be “reasonably” different TOT_Diff, Charge Diff, Charge Skewness, Full_charge

Bkg data-set is used to build the experimental probability density functions (p.d.f.)

The corresponding cumulative distributions function (c.d.f.) Ii is then constructed:

The four Ii’s are combined to get the final distribution:

Two step procedure:

1st step: the selection criteria based on P is used to remove the background from n and γ induced events

2nd step: the procedure is reiterated to define the n/γ selection criteria (60Co sample used to build the p.d.f.)

∫∞−= ix

iiiii dxxhxI~

)()~( : signal over noise distributions)( ii xh

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P = Π⋅(−logΠ)i

i!i=0

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∑ ,Π = I1⋅ I2⋅ I3⋅ I4


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1st Step

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c.d.f. obtained for one of the selected variables (total charge), based on the bkg data-set

bkg data-set

As expected we have a random quantity with a flat distribution


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1st Step

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c.d.f. obtained for one of the selected variables (total charge), based on the bkg data-set

Moving towards a different p.d.f (60Co or 252Cf), we have an accumulation of events on the right part of the histogram which allows as to separate the signal form bkg


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1st step: bkg rejection

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Selection for the 2nd step

Selection for the 2nd step

These two plots show that almost all the signal is on the right part of the histograms (peak) while the bkg is a flat component on the left

The bin at P>0.995 contains ~78% of the γ events

The bin at P>0.995 contains ~99% of the γ +n events for Cf

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P = Π⋅(−logΠ)i

i!i=0

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∑ ,Π = I1⋅ I2⋅ I3⋅ I4

Repeat the exercise for all the quantities and combine the c.d.f. as follow


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2nd step

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after the Bkg has been filtered out, the ratio between γ and n events in 252Cf can be measured:

γ- events in the 60Co data-set

n and γ composition in the

252Cf data-set


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2nd step: γ rejection

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The procedure is reiterated using the 60Co data-set to build the cumulative distributions to identify γ over n in the 252Cf data-set

Results for a P cut of 0.995

Results are well beyond the expectation which are pushing us to continue with Further test to measure the neutron

detection efficiency and to qualify the γ/n separation using TOF technique

Tube layout optimization Improved electronics (see next slide)


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Customized electronics

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Adjustable bias voltage for each of 16 channels SiPM temperature readout and gain compensation

The thermo-chip placed onto the SiPM generates a digital pickup noise which cannot be removed

The frequency of the temperature readout is settable The board include a lemo connector that can be used

for veto trigger Improved minimum detectable light and dynamic

range


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Customized electronics

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≈ 60 ph @ 19.6°C

≈ 30 ph @ 19.6°C

Pedestal

Adjustable bias voltage for each of 16 channels SiPM temperature readout and gain compensation

The thermo-chip placed onto the SiPM generates a digital pickup noise which cannot be removed

The frequency of the temperature readout is settable The board include a lemo connector that can be used

for veto trigger Improved minimum detectable light and dynamic

range


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Conclusion

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The Proof of Concept of SiPM arrays in the tube has been successfully completed

The tube design optimization is certainly required A new front-end electronics (designed at Uni. Insubria) has

been characterized in the lab and fulfils the requirements New test campaign is on the way to optimize the on-line and

off-line analysis


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Spares

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Typical events with PMTs

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Neutron/γ discrimination is based on the difference between the fast/slow component of the scintillation light

Typical neutron and gamma events

Typical plot from the 4He detectors showing the discrimination between neutrons (Am-Be) and gamma (60Co)


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Bkg_rejection

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Bkg flat distribution (1st selection)

Co60 flat distribution (2nd selection)


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2nd step

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Distributions of the four discriminant variables used in the second step of the procedure after having filtered the noise induced events


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2nd step: γ rejection

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εn _ select =Ncf _ sig _ sel −ε bkg _ rej * Ncf _ total _ bkg

Ncf _ total _ signal

P_value=0.995Neutron eff = 94%γ rejection power= 92%

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γrej _ power =1 −ε bkg _ rej

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εbkg _ rej =Nco60 _ sel

Nco60 _ total _ signal

measured with a data-set with pure bkg


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Few spectra used in the linearity plot

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integration of sipm in a high-pressure noble gas scintillation detector for homeland security

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