webinar geosciences 2012

X-ray Expeditions into Geosciences and Mining Geosciences Applications of EDS and µ-XRF Bruker Nano GmbH, Berlin Webinar, April25th, 2012

Innovation with Integrity

Webinar Overview

Part I

Advanced EDS analysis options for geoscience applications using SDD on SEM

Part II

Geological applications of the M4 TORNADO µ-XRF spectrometer

Advanced EDS Analysis Options for Geoscience Applications using SDD

Dr. Tobias Salge, EDS Application Scientist, Bruker Nano GmbH, Berlin

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State-of-the-art XFlash® silicon drift detectors (SDD)

• Energy resolution 121 eV (FWHM Mn Kα)

• Best energy resolution range up to 100 kcps

• Multi detector option

QUANTAX EDS system for SEM, EPMA and TEM

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Overview

• Fast, high resolution mapping Display of small features

• Spectrum imaging Improved element identification Quantitative analysis of REE by peak deconvolution Modal analysis

• Computer-controlled SEM High resolution at the macroscale Particle search using feature analysis

• Application examples Earth and planetary samples Core samples of impactites at the K-Pg boundary Mining samples focussing on REE, iron oxides

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OPD leg 207 (4000 km from crater)

Chicxulub impact structure • ~Ø 180 km, ~65 Ma • Target rock:

silicate basement, 3 km sediments

• Release of SOx, CO2, H2O

K-Pg boundary Asteroid impact and mass extinction

Image of NASA Worldwind

Chicxulub crater

Yax-1 UNAM-7

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Schulte et al. 2009

Thin section

K-Pg transition at OPD leg 207 2 cm ejecta spherule deposit

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Schulte et al. 2010, Science, 327, 1214-1218

Dolomite spherule with layered clay shell indicates impact-induced mechanical and thermal stress.

ODP leg 207, High-resolution map 4072x3072 pixel, 30 min, 500 kcps

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Spectrum Imaging HyperMap

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• Synthetic spectrum of highest count level found in each spectrum channel

• Detection of trace elements present in one pixel

MaxPixSpec reveals the presence of Th, La, Ce, …

Granite 200 µm

Element Identification Maximum Pixel Spectrum vs. Sum Spectrum

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Ce

Monazite (La, Ce, Nd, Pr…)PO4

MaxPixSpec reveals the presence of Th, La, Ce, …

200 µm

wt.%

Element Identification Maximum Pixel Spectrum vs. Sum Spectrum

• Synthetic spectrum of highest count level found in each spectrum channel

• Detection of elements present in a few pixels only

Granite

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How far can we take peak deconvolution? Diagenetic monazite concretion

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Peak intensity map

Intensity map and area spectra display zonation.

Area spectra

La Gd 300 µm


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Peak intensity map

Overlapping element lines lead to wrong display of element distribution.

Gd 300 µm


Area spectra

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>5.1

4.7

3.5

2.4

1.2

0.0

wt.% Quantitative map Deconvolution result

• Overlapping peaks can be deconvolved • Quantitative map displays correct element distribution

Gd 300 µm


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• Concentration of Gd, Sm, Nd within the core • Sequential incorporation of LREE • La dominating the outermost rim

Line scan (wt.%) extracted from quantitative map:


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Salge et al. 2007

BSE

Microcrystalline breccia matrix Core: UNAM-7 381.4 m

Modal analysis Chemical phase mapping UNAM-7

Matrix

Matrix

Matrix

1 cm

Anh

80 µm

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80 µm Salge et al. 2008

Autophase result

Modal analysis Chemical phase mapping

Core: UNAM-7 381.4 m

UNAM-7

Matrix

Matrix

Matrix

1 cm

Anh

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80 µm

Modal content

Phase Area fraction (%)

Anhydrite 51.8

Dolomite 30.6

Calcite 14.9

K-feldspar 1.0

Celestine 0.7

Na-feldspar 0.5

Modal analysis Chemical phase mapping

Core: UNAM-7 381.4 m

Salge et al. 2008

UNAM-7

Matrix

Matrix

Matrix

1 cm

Anh

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Computer-controlled SEM Jobs – StageControl

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Yax-1 core: Unit 5 861.72m

Composite of 276 maps • 2 µm pixel resolution • 11,906 x 11,595 pixel • ICR: 450,000 cps • 20 kV, 18 nA, 18 h

(4 min per single map) 5 mm

Matrix Melt rock 1 cm

High resolution at the macroscale 140 megapixel map

Yax-1

Nelson et al. (in press, available online at GCA)

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5 mm

Matrix Melt rock

Next image

Yax-1 core: Unit 5 861.72m

Composite of 276 maps • 2 µm pixel resolution • 11,906 x 11,595 pixel • ICR: 450,000 cps • 20 kV, 18 nA, 18 h

(4 min per single map)

1 cm

High resolution at the macroscale 140 megapixel map

Yax-1

Nelson et al. (in print, available online at GCA)

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1 mm

• Crystallized impact melt material with hydrothermal overprint.

• Multiple fracturing events due to interaction of hot fluids with solidified melts.

Impact melt Matrix

Impact melt

Matrix

K-metasomatism Multiple fracturing events

Yax-1

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Particle detection and classification Feature analysis

1. Particle detection

2. Chemistry: Chemical classification

3. Review: Reclassification

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Morphological classification dialog: Binarization

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2. Chemical classification

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Discrimination of calcite and flourite Feature analysis

Class Count Area fraction (%) Fluorite CaF2 130 9.2 Ca-carbonate CaCO3 4 2.3 Unclassified 482 68.5 All 616 100

20 kV, 60 kcps, 0.5 s

Composite of 14 BSE images

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Altered laterite Classification of monazite and pyrochlore

Bariopyrochlore Ba0.3Sr0.2Ca0.1Nb1.8Ti0.2O5.6(H2O)0.8

Plumbopyrochlore Pb0.8Y0.2U0.1Ca0.1Nb1.4Si0.2Fe2+0.2Ta0.1O6.2(OH)0.5

Zirconolite Ca0.8Ce0.2ZrTi1.5Fe2+0.3Nb0.1Al0.1O7

Hollandite Ba0.8Pb0.2Na0.1Mn4+

6.1Fe3+1.3Mn2+

0.5Al0.2Si0.1O16

Composite of 64 BSE images

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Pyrochlore Deconvolution of overlapping peaks

2.90 3.00 3.10 3.20 3.30 3.40 3.50 3.60 3.703.80keV

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

cps/eV

Ca

U

Th

1.80 2.00 2.20 2.40 2.60keV

0

20

40

60

80

100

120

cps/eV

Sr Pb Zr

Nb Ta

4.2 4.4 4.6 4.8 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 6.6keV

0

2

4

6

8

10

12

14

16

18

20

22

24 cps/eV

Ti

Ba

Ce

Fe

Pyrochlore spectrum XFlash® 5030, 20 kV, 90-120 kcps, 3 s

31

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Classification Standardless quantification

Class Count Monazite Nd>8 wt.% 123 Monazite La>18 wt.% 551 Monazite 669 Baryte 32 Hollandite 22 Plumbopyrochlore 15 Bariopyrochlore 20

Zirconolite 2 Unclassified 43 All 1477

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Classification of monazite Composition

• An exchange of neodynium with lanthanum is present.

Ce versus Nd

0,00,0

3,0

1,2

5,9

2,5

8,9

3,7

11,8

4,9

14,8

6,2

17,8

7,4

20,7

8,7

23,7

9,9

26,6

11,1

29,6

12,4

Ce

Nd

Ce versus Nd 12.4

11.1

9.9

8.7

7.4

6.2

4.9

3.7

2.5

1.2

0.0

Nd

(wt.

%)

0.0 3.0 5.9 8.9 11.8

14.8 17.8 20.7 13.7 29.6

Ce (wt.%) 26.6

La versus Nd La versus Nd

0,00,0

2,3

1,2

4,5

2,5

6,8

3,7

9,0

4,9

11,3

6,2

13,5

7,4

15,8

8,7

18,0

9,9

20,3

11,1

22,5

12,4

La

Nd

0.0 2.3 4.5 6.8 9.0 11.3 13.5 15.8 18.0 22.5

La (wt.%)

12.4

11.1

9.9

8.7

7.4

6.2

4.9

3.7

2.5

1.2

0.0

Nd

(wt.

%)

20.3

La versus Nd

La-Monazite Monazite Nd-Monazite

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Iron oxides Fast quantification using a standard

Haematite Fe2O3

N=10 Expected (at.-%)

Mean (at.-%)

s (±at.-%)

O 60.0 60.0 0.5 Fe 40.0 40.0 0.5 Magnetite Fe3O4

N=10

Expected (at.-%)

Mean (at.-%)

s (±at.-%)

O 57.1 56.9 1.0 Fe 42.9 43.1 1.0

EDX detector: XFlash® 5040 QUAD HV: 15 kV Current: 142.6 nA

Haematite Fe2O3 and Magnetite Fe3O4 • Standard-based quantification is

required to obtain highest accuracy.

• Haematite was used for reference.

• Using high count rates, iron oxides can be discriminated in a short time.

Count rate (In/Out): 900/675 kcps Time reference/sample: 120/30 ms Counts per spectrum: 20000 – 25000

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BSE image of iron ore pellet Area spectra

Spectrum imaging of iron oxides Advanced analysis options

Silicate

Haematite Magnetite

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Autophase result

Spectrum Imaging of Iron Oxides Autophase

Magnetite / Haematite = 9.4

Class Area fraction (%) Magnetite 86.3 Haematite 9.2 Silicate 3.3 Unassigned 1.2 Total 100.0

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Magnetite

Classification of iron oxides Feature analysis

Haematite

Ti-Haematite Ti-Magnetite

BSE image of iron ore pellet 15 kV, ~450 kcps, 0.5 s

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Quantification with hybrid method Standardless with reference for Fe and O

Magnetite / Haematite = 9.6 (Autophase 9.4)

Class Count Area fraction (%) Ti-Magnetite 2 0,1 Magnetite 540 79,7 Ti-Haematite 2 0,1 Haematite 57 8,3 Quartz 3 0,6 Olivine 11 1,6 Na-feldspar 4 5,6 Alumosilicate 3 0,1 Calcium pyroxene 1 0,1 Apatite 2 2,1 Calcium carbonate 2 0,3 Unclassified 26 1,4 All 653 100,0

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Summary

• State-of-the-art XFlash® SDD technology enables fast mapping

• Spectrum imaging significantly enhances EDS analysis

• Deconvolution is an important tool for element identification and quantification

• Computer-controlled acquisition provides high resolution at the macroscale

• Feature analysis combines morphological and chemical classification

• Hybrid method combines standardless and standard-based quantification

Geological Applications of the M4 TORNADO µ-XRF Spectrometer

Dr. Roald Tagle, µ-XRF Application Scientist, Bruker Nano GmbH, Berlin

A technological alliance From electron to X-ray excitation

µ-XRF ARTAX EDS QUANTAX

High speed µ-XRF spectrometer

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The M4 TORNADO Spatially resolved µ-X-ray spectroscopy

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The M4 TORNADO Focusing X-rays with a polycapillary lens

10 mm

23 µm for 17,5 keV

Poly-capillary lens collects large angle of tube radiation and concentrates it into a small spot on the sample

Focusing X-rays

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The M4 TORNADO Instrument specifications

SDD 30 mm2, <145 eV FWHM

Key Features

• High brilliance X-ray source with small spot

• Video microscope for sample positioning with 10X and 100X magnification

• SDD technology offering high count rate capability in combination with optimum energy resolution

• Large vacuum chamber, 20 mbar in 120 s

• Powerful high speed servo motors, for samples up to 5 kg

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Comparison µ-XRF & electron excitation High sensitivity for heavy elements

• Spectra of NIST 612 with approx. 500 ppm of more than 20 elements, EPMA (blue) and µ-XRF (red)

• Different excitation probability, therefore higher sensitivity for heavy elements

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Features and applications examples of the M4 Tornado in geology

• Qualitative and quantitative analyses of large samples, up to 30 X 15 cm and 5 kg, without previous preparation

Element distribution in sediments (K/Pg-boundary)

Documenting thin sections (large area scan)

Composition of the unique Dermbach meteorite

(HyperMap quantification)

• Quantitative analysis for mayor and trace elements, down to the low ppm range

Composition of volcanic glasses

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Raton Basin continental K/Pg sites

Chicxulub impact structure • ~Ø 180 km, ~65 Ma • Target rock:

silicate basement, 3 km sediments

K-Pg boundary Asteroid impact and mass extinction

Image of NASA Worldwind

Chicxulub crater

Yax-1 UNAM-7

Scan of the Cretaceous / Paleogene boundary in Raton Basin US

Optimized for trace elements Overview measurement

5 mm

Ca Al Cr Cr Cr/Si Zr/Si Ni/Si

Pg K

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Scanning thin sections

Conditions: 35 keV 800 µA, 5 ms per pixel 100 µm step size

Document thin sections or samples in a short time e.g. ~ 30 minutes per section up to 18 at the same time!

Results can be saved in independent files.

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Independently saved section results

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Qualitative and quantitative analysis of the unique Dermbach iron meteorite

The HyperMap feature allows an optimal “data mining”! Not only compositional overview for recognition of characteristic areas but also quantification of selected regions

The Dermbach meteorite was found in Germany in 1924.The Fe-Ni phase contains one of the highest Ni-concentrations described in literature

Bartoschewitz et al (2012). LPSC. Abs 1292

Conditions: 50 keV 200 µA, 5 ms per pixel 60 µm step size 974 x 883 Pixel 2 h measuring time

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Results • The high Ni concentrations were

confirmed. A strong fractionation of the Fe-Ni-metal with a low-Ni rim could be found in the sample

• The Ni increase correlates with the Cu increase in the Fe-Ni metal

Qualitative and quantitative analysis of the unique Dermbach iron meteorite

Fe Co Ni Cu Ni-low 1 70.2 1.11 28.5 0.22 Ni-low 2 65.0 1.08 33.6 0.29 Ni-high 1 58.8 0.96 40.4 0.44 Ni-high 2 55.8 0.95 42.7 0.48

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Quantitative analysis of major and trace elements in volcanic glass

The quantification was performed using the M4 standardless quantification routine. 35 kV, 750 µA, 60 s Al/Ti/Cu-filter

Ga ~20 ppm Sr from 30 to 120 ppm

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Summary

• Unique speed and performance in the determination of the element distribution in large sample with measurement times per pixel of 0.3 ms and up to 4 Million pixels in a single HyperMap

• High spatial resolution down to 25 µm X-ray spot size, motors steps of 4 µm

• Optimal for the analysis of inhomogeneous samples, due to better identification of the representative location of interest

• Non-destructive, fast analysis of large samples without preparation, including solid, powder or liquid samples

• Qualitative and quantitative analysis of all elements from Na upwards, due to vacuum chamber, detection limit for heavy trace elements in the low ppm range

• Standardless Fundamental Parameter quantification with type calibration option

• Powerful software with multiple tools for optimal data mining

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Geozentrum Nordbayern P. Schulte

Museum of Natural History, HU Berlin

D. Stöffler, P. Claeys, L. Hecht

Universidad Nacional Autónoma

de México J. Urrutia- Fucugauchi

Institute of Meteoritics, University of New Mexico H. Newsom

Institute for Planetology,

WWU Münster A. Deutsch

Natural History Museum London

A. Kearsley

International Continental Scientific

Drilling Program

Ocean Drilling Program

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Sample Classification

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BSE Ca Si Fe Na

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BSE Ca Si Fe Na

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2 mm BSE Ca Si Fe Na

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Automated particle search • Binarization of BSE image

(Grayscale thresholds: 180-255)

• Morphological filtering (>3µm lengths, >2 µm widths)

• Chemical classification (Zr >55 wt.%%)

2 mm

Feature analysis Baddeleyite (ZrO2) at lunar meteorite

Composite BSE image of Dhofar 287A (9x5 mm)

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• 90 images scanned

• 997 grains analyzed in 86 min

• 11 baddeleyite grains were detected

6 µm

Feature analysis Baddeleyite (ZrO2) at lunar meteorite

Automated particle search • Binarization of BSE image

(Grayscale thresholds: 180-255)

• Morphological filtering (>3µm lengths, >2 µm widths)

• Chemical classification (Zr >55 wt.%%)

Composite BSE image of Dhofar 287A (9x5 mm)

2 mm

Measurement on a fish fossil from Solnhofen limestone

Conditions 50 keV 600 µA 1618x462 pixels 40 ms per pixel 40 µm step size 10h meas. Time 747516 single spectra

Mosaic image of the sample

Total x-ray intensity 03.05.2012 65

Measurement on a fish fossil from Solnhofen limestone

Fe P 1 cm

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M4 TORNADO High-end µ-XRF spectrometer

580

mm

Additional options • Second tube with

collimator e.g. W-anode for optimal detection heavy elements in trace concentration like Ag, Cd or Pd.

• Second detector for faster data acquisition

Complete instrument

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webinar geosciences 2012

Technology

pixel resolution

spectrum imaginghypermap

pixel icr

best energy resolution

particle detection2

eds application scientist

kpg boundaryasteroid

correct element distribution03