1. Sample Preparation, Data Collection and Phase-ID using Powder XRD
Pamela Whitfield
National Research Council, Ottawa
9th Canadian Powder Diffraction Workshop, Saskatoon, May 2012

2. Horses for courses…
Data quality required depends on what you want to do with it
Phase-ID has less stringent requirements on both sample prep and data collection
Quantitative phase analysis, Rietveld analysis and structure solution require careful sample prep but can require different data collection regimes
I’ll mostly cover requirements for phase-ID but will touch on considerations for other techniques.

3. Questions to ask What is in your sample? How much have you got?
Organics often better collected in transmission
Fluorescence can cause problems in data quality
How much have you got?
Very small quantities
capillary or foil transmission? (not an option for many people)
smear mount?
We’ll assume conventional reflection geometry unless stated otherwise
What kind of instrument have you got access to?
If you have a choice which is the best?

4. What matters for phase-ID?
Peak positions most important
Relative intensities secondary
but very important for Rietveld, etc….
If wanting to do search-match it is useful if the phases exist in the PDF database!

5. Where to start? What errors affects peak positions?
What affects relative intensities?
Preparing the samples
Different types of sample holders

6. Peak positions – sources of error
Zero point error - is the system properly aligned?
use a NIST standard periodically to check it
Sample displacement - sample too high/low?
(0.1 mm  ~ 0.045°)
Note: convention is that –ve sample displacement = sample too high
Not an issue for parallel beam systems

7. Peak positions – sources of error
Sample transparency
if X-rays penetrate a long way into the sample can get a ‘sample displacement’ even if the height is perfect
not an issue for parallel-beam systems
if necessary use a thin sample to avoid transparency peak shifts
relative intensities will be affected
Diffraction patterns from powdered sucrose as both deep and thin samples

8. Parallel versus para-focussing
The systems don’t look that different but don’t behave the same..
Parallel-beam immune to sample displacement & transparency but has worse peak resolution – twin mirror system excepted
Divergent-beam without & with secondary graphite monochromator
Parallel-beam setups with long slits and secondary mirror

9. Relative intensities Particle statistics (grain size)
Preferential orientation
Crystal structure
Microabsorption (multiphase samples)

10. Sample-related problems
Grainy samples or ‘rocks in dust’
Microabsorption
a serious issue for quantitative analysis and could fill a talk by itself!
Preferential orientation
Extinction

11. No. of diffracting crystallites
“Grainy” samples
Issue of graininess relates to particle statistics
Particle statistics is what makes a powder a true powder!
600 mesh sieve = <20 mm
Diameter
40mm
10mm
1mm
Crystallites / 20mm3
5.97 × 105
3.82 × 107
3.82 × 1010
No. of diffracting crystallites 12
760
38000
Comparison of the particle statistics for samples with different crystallite sizes
Crystallite
size range
15-20mm
5-50mm
5-15mm
<5mm
Intensity reproducibility
18.2%
10.1%
2.1%
1.2%
Reproducibility of the intensity of the quartz (101) reflection with different crystallite sizes

12. “Seeing” particle statistics
Playing Russian roulette with a grainy sample
Stacking the odds in your favour by micronizing….

13. How to improve particle statistics
There are a number of potential ways to improve particle statistics
Increase the area illuminated by X-rays
Divergence angle
Rotate samples
Use a PSD
Reduce the particle size
(without damaging crystallites!)
McCrone mill = good 
Mortar and pestle = bad 

14. I don’t have a 2D detector – now what?
A series of phi-scans can show up problems
With a rotation stage phi is a set angle instead of full rotation
Phi-scans across 5 fingers of quartz with different samples

15. I don’t have a 2D detector – now what?
Can also run repeats after reloading sample each time (get real stats as a bonus)
Unmicronized : MgO only appears in 1 sample out of 3
periclase
Overlay of 3 repeat patterns from un-micronized cement
Overlay of 3 repeat patterns from micronized cement

16. Extreme examples… Occasionally reflections are unexpectedly split
Quartz is particularly prone….
Synchrotron data are not immune – in fact it can be worse due to the extremely parallel beam
Main 101 reflection of ~100 micron quartz with a fuller pattern inset showing spurious intensities
Capillary and rocked reflection data from LaB6 on a strip heater taken with the Australian synchrotron

17. Microabsorption
Microabsorption is the thing that causes most nightmares for analysts doing quantitative phase analysis
Caused by a mixture of high and low absorbing phases
High absorbers
beam absorbed at surface
only fraction of grain diffracting
relative intensity underestimated
QPA too low
Low absorbers
beam penetrates deeper
more diffracting volume
relative intensity overestimated
QPA too high

18. What can you do about it? Change radiation? Use neutrons?
Absorption contrast changes with energy
Higher energy X-rays often less problematic
Use neutrons?
Not usually practical but a ‘gold standard’
Use the Brindley correction?
Need to know absorption of each phase
Need to know particle (not crystallite!) size for each phase
Assumes spherical particles with a monodisperse size distribution
Usually unrealistic!

19. Effect of particle size
Brindley proposed that a maximum acceptable particle size for QPA can be calculated by:
m = linear absorption coefficient (LAC)
corundum
magnetite
zircon
CuKa LAC (cm-1)
125
1167
380
tmax (mm)
0.8
0.1
0.3
CoKa LAC (cm-1)
195
240
574
0.5
0.4
0.2

20. The scale of escalating despair!
Brindley also devised a criteria for whether you should be ‘concerned’ about microabsorption
mD = linear absorption coefficient x particle diameter
Fine powders
mD < negligible m-absorption
Medium powders
0.01 < mD < m-absorption present – Brindley model applies
Coarse powders
0.1 < mD < 1 large m-absorption – Brindley model estimates the effect
Very coarse powders
mD > severe m-absorption – forget it!

21. Radiation dependence of mD CoKa (7 keV)
Size mm
corundum (Al2O3) mD
magnetite (Fe3O4)
zircon (ZrSiO4)
0.1
0.002
0.006
0.2
0.004
0.005
0.011
0.5
0.010
0.012
0.029 1
0.019
0.024
0.057 2
0.039
0.048
0.115 5
0.097
0.120
0.287 10
0.195
0.240
0.574 20
0.389
0.480
1.148
fine
mD < 0.01
medium
0.01 < mD < 0.1
coarse
0.1 < mD < 1
very coarse
mD > 1

22. Radiation dependence of mD CuKa (8 keV)
Size mm
corundum (Al2O3) mD
magnetite (Fe3O4)
zircon (ZrSiO4)
0.1
0.001
0.012
0.004
0.2
0.003
0.023
0.008
0.5
0.006
0.058
0.019 1
0.013
0.117
0.038 2
0.025
0.233
0.076 5
0.063
0.584
0.190 10
0.125
1.167
0.380 20
0.251
2.344
0.759
fine
mD < 0.01
medium
0.01 < mD < 0.1
coarse
0.1 < mD < 1
very coarse
mD > 1

23. Radiation dependence of mD MoKa (17 keV)
Size mm
corundum (Al2O3) mD
magnetite (Fe3O4)
zircon (ZrSiO4)
0.1
0.000
0.001
0.2
0.003
0.5
0.007
0.002 1
0.014
0.004 2
0.028
0.009 5
0.006
0.071
0.022 10
0.013
0.142
0.044 20
0.025
0.284
0.088 50
0.063
0.709
0.219
100
0.126
1.418
0.438 {
note new
rows!
fine
mD < 0.01
medium
0.01 < mD < 0.1
coarse
0.1 < mD < 1
very coarse
mD > 1

24. QXRD Round Robin: CPD #4 unmilled
Unmilled grain sizes: Al2O3 28mm, Fe3O4 36mm, ZrSiO4 21mm
Can’t fit intensities
very poor particle statistics? (<200 diffracting crystallites per phase)
Al2O3 mD = 0.345, Fe3O4 mD = 4.15!!, ZrSiO4 mD = 0.788
0.1 < mD < 1 large m-absorption – Brindley model estimates the effect
mD > severe m-absorption – forget it!
without Brindley
correction
with Brindley
correction
CuKa with graphite monochromator
weighed amounts
Al2O %
Fe3O %
ZrSiO %
Thanks to Ian Madsen for the data

25. CPD #4 confirming what we suspected
Large grains can be confirmed using 2D detector as before or using a series of scans with different phi angles (no rotation)
N.B. Al2O3 may still have preferential orientation C M Z
Al2O3
ZrSiO4
Fe3O4
Thanks to Arnt Kern for the data

26. Micronized CPD #4? Particle statistics no longer a problem
Al2O3 and ZrSiO4 still have some orientation – corrected
CoKa doesn’t help much as problem switches from Fe3O4 to ZrSiO4
How about an SEM?
CuKa with
graphite monochromator
CoKa with
graphite monochromator
weighed amounts
Al2O %
Fe3O %
ZrSiO %
Thanks to Ian Madsen for the data

27. Al2O3, Fe3O4, ZrSiO4 - Micronised
Corundum Magnetite Zircon
Global copyright Ian Madsen!

28. Pick a number, any number…
What value of particle size do we choose for the Brindley correction?
Wt% Corundum Magnetite Zircon
Weighed
No correction Mean Bias
Brindley model, Ø = 1m Mean Bias
Brindley model, Ø = 5 m Mean Bias
Brindley model, Ø = 10m Mean Bias
Thanks to Ian Madsen for the analysis

29. What does reality matter anyway?
Can fudge the particle size numbers and packing so the Brindley correction gives the right result for CoKa
but mD for ZrSiO4 and Al2O3 well into coarse range
CuKa not as good (and mDs are even worse)
CoKa
Al2O3 17mm 40%PD
Fe3O4 5mm 40%PD
ZrSiO4 14mm 40%PD
CuKa
Al2O3 17mm
Fe3O4 5mm
ZrSiO4 14mm
if these numbers correct send your McCrone mill and SEM back!
weighed amounts
Al2O %
Fe3O %
ZrSiO %

30. Preferential orientation (texture…)
Preferential orientation (PO) is most often seen in samples that contain crystallites with a platey or needle-like morphology.
Particular culprits
Plates
mica
clays
some carbonates, hydroxides e.g. Ca(OH)2
Needles
wollastonite
many organics
The extent of the orientation from a particular sample depends greatly on how it is mounted

31. Orientation of plate-like samples
There’s no getting away from it – they can be a real pain
Top-loading is hopeless as you make it worse….
Back-loading the usual approach but not always enough…
Breaking up the alignment of the plates by back-loading onto a rough surface such as sandpaper can help…

32. Going the extra mile…
With plate-like samples if you have a capillary stage then use it!
Background-subtracted data from micronized 40S mica in a 0.5mm capillary
If not then spray-drying the sample can be an alternative….
200
001
Top-loaded, spray-dried 40S mica
SEM of spray-dried mica

33. Just to prove the data is usable….
Micas not pleasant to deal with at the best of times and this has some messy anisotropic broadening..
However, the data from the top-loaded, spray-dried sample fits a un-refined literature biotite structure very well with no orientation correction
Rwp = 11.8%
GOF = 1.82
That’s not to say there were no corrections needed at all! 
Refinement of the top-loaded, spray-dried 40S mica using a literature biotite structure without orientation correction

34. Corrections for PO in Rietveld software
Two different corrections exist in most software to correct orientation during Rietveld analysis
March-Dollase (MD)
Single variable but an orientation direction must be supplied by the analyst
Spherical Harmonics (SH)
VERY powerful approach – can increase SH ‘order’ to fit increasingly complex behaviour
No orientation direction required
Number of variables increase with reducing cell symmetry
Be very careful in quantitative analysis with severe peak overlap (e.g. cements)
Negative peaks are very common and very meaningless!

35. Extinction
Reduction in the intensity of a Bragg reflection by re-diffraction by the successive planes back in the direction of the incident beam
Dependent on size/shape of the coherently-diffracting domains
Primary  re-diffraction within a single crystallite
Effect minimized by reducing grain size – ideally submicron
Normally seen in large, ‘perfect’ crystallites such as silicon or quartz
Secondary  mosaic crystals, not seen in powders

36. The different preparation techniques
Reflection
Top-loading
Flat plate
Back-loading
Side-loading
Transmission
Capillary
Foil transmission

37. Top-loading
Simplest but most prone to inducing preferential orientation
Special holders often in this category
Alternative holders such as cavity zero background silicon or air-sensitive often top-loading as well

38. Flat plate aka: smear mount
Used with very small samples (phase-ID , Rietveld )
Sample adhered to zero background plate using some form of binder/adhesive that doesn’t have any Bragg peaks
Vaseline, vacuum grease, hairspray (spray ~12” from holder)
Slurry with ethanol or acetone – tricky to get right consistency
N.B some quartz plates show a sharp reflection when spun
Silicon zero
background plate
Quartz zero
background plate
Gem Dugout a commonly used source for zero background plates (

39. Back-loading

40. Side-loading I don’t have one of these! but basic principle….. plug
powder
glass
slide
holder
sample

41. Capillaries
Probably best way to reduce orientation in platey materials
Commercially either quartz, borosilicate or soda-glass
range in diameter from 2mm to 0.1mm
Or use thin-walled polymer tubing of Kapton, PET, etc
Most useful where sample absorption is low, e.g. organics
Can be extremely fiddly to fill!
0.2 mm
1 mm

42. Capillary instrument setup
Capillary setups can be quite specialized
Focussing optics specific to transmission geometry
Even q-q systems better run as q-2q in capillary mode
Transmission better for low angles
Capillary setup on q-q system at very high 2q angle using detector scan with focussing primary optic, PSD, radial Soller slits and primary slit setup to reduce low angle scatter reaching detector

43. Capillaries – highly absorbing samples
Absorption reduces the peak intensities at low angles
Corrections exist but they have limits
Smaller capillaries and/or dilution with a ‘light’ phase will help (e.g. diamond, amorphous boron, carbon black, etc)
Rietveld refinement of ~10 vol% SnO2 in diamond powder
Capillary and reflection data from pure SnO2

44. Foil transmission Another approach for small samples
Powders can be mounted between films of Kapton, Mylar, etc
Not immune to preferential orientation – the plane is just rotated 90° so the peak intensities change accordingly!
Quartz powder between Kapton
Twin-mirror system set up for foil transmission

45. Foil transmission
Sample can be very thin so highly absorbing samples possible without dilution
1/cos(q) correction required for accurate relative intensities
Rietveld refinement of SnO2 (1400cm-1)

46. Data collection strategies
Rietveld analysis guidelines published by McCusker et al in 1999
Choose beam divergence so the beam doesn’t overspill the sample at low angle
remember the under-scan when a PSD is used!
1st datapoint may be at 10° 2q but the scan may start at 8°!
(ENeqV1_0.xls very handy for working out correct divergence) (
Rule of thumb - step size of ~ FWHM/5 to FWHM/8
Too small = wasting time and producing noisy data
Too coarse = chopping intensity and peaks not modelled properly

47. Experiment optimization
‘Horses for courses’ – collect data fit for purpose
Data for phase-ID does not have to be of the same quality as for structure solution, etc
Most common mistake among users
too small step size for sample
0.01º step, 1s count
Rwp = 15.2%
0.02º step, 2s count
Rwp = 12.0%
2 different datasets from quartz stone
– both experiments took 25 seconds
Smaller Rwp corresponds to a better fit.

48. Peak-to-background A number of things affect the peak-to-background
air-scatter at low angles
use air-scatter sinks if needed
nanoparticles have lower intrinsic peak heights
not much you can do here
eventually Rietveld results are no longer meaningful
capillaries always have higher background
subtracting capillary blank can improve this but careful not to distort counting statistics
fluorescence is the main cause of poor peak-to-background…
Rietveld refinement round robin suggested a minimum P/B value of 50 for accurate structural parameters….

49. Why does background matter?
With a high background the uncertainty in the background parameters increase (often use more parameters as well)
uncertainty in the extracted peak intensities increases
→ greater uncertainty in structural parameters and quantitative phase analysis
Which line would you choose?

50. Fluorescence
Fluorescence even adversely affects phase-ID detection limits
a secondary monochromator on conventional system is an effective way to filter out fluorescence
CuKa - Li1.15Mn1.85O3.9F0.1
Lin (Counts)
100
200
300
400
500
600
700
800
900
1000
1100
1200
1300
2-Theta - Scale 15 20 30 40 50 60 70 80
No monochromator
Properly aligned
monochromator/mirror
there is a real
peak here!

51. Fluorescence – what to do about it?
With a PSD a conventional monochromator not possible – data with CoKa
CoKa - LiMn1.5Ni0.5O4
Which dataset do you prefer?

52. Fluorescence cont.
Can improve PSD data significantly by adjusting the detector’s electronic discriminator window
P/B = 13.4
Rescaled to normalize background
P/B = 4.5
Sacrifice intensity to improve P/B ratio
P/B = 4.2
P/B still along way off 50. Change radiation or instrument.

53. Problematic sample: quant analysis
FeS + Mg(OH)2 + SiO2
CuKa
Ground or unground?
particle statistics
Microabsorption (FeS)
ideally switch to CoKa
Fluorescence (FeS)
high background
monochromator, energy-discriminating detector, switch to CoKa
Preferential orientation (Mg(OH)2)
Extinction? (SiO2)
Micronize!!!!
All of these problems are reduced by micronizing to sub-micron particle/crystallite size

54. Problematic sample: Rietveld analysis
LiMn1.4Ti0.1Ni0.5O4 (lithium battery cathode material)
Mn fluoresces with both CuKa and CoKa !
Use a monochromator or energy discriminating detector
Good peak-to-background, but...
Fluorescence is still there even if you can’t see it
Very high absorption impacts particle statistics (X-rays only penetrate a few 10s of microns)
Solution by changing tube?
CrKa 2.29Å (unusual, high air scatter/attenuation and limits lower d-spacings attainable)
FeKa 1.94Å (very unusual and low power tubes)
MoKa 0.71Å (unusual and beta-filter artefacts visible)

55. LiMn1.4Ti0.1Ni0.5O4 Cu Co Mo Cr P/B = 9.4 P/B = 4.5 P/B = 84 P/B = 87
A primary monochromator would get rid of this high angle tail
P/B = 84 Cr
P/B = 87
(P/B = 54 without air-scatter sink to reach angles >100)

56. Variable counting time (VCT)
The physics of XRD dictate that intensities drop with angle
Most of the information (reflections) is at higher angles
Can regain much of the information by counting for longer at higher angles
Constant Counting Time
I ~ LP * thermal vibration * f2
Variable Counting Time
Boehmite (Madsen, 1992)

57. VCT data - quantitative analysis
Also possible to improve detection limits in quant analysis by counting for longer where minor phases expected
Fixed count time
Variable count time (normalized)
Example from presentation by Lachlan Cranswick

58. VCT data - structure refinement
Extract more structural details if reflections still visible at high angles
Using a PSD split pattern into sections
can also increase step size with angle as well to save some time…
Jadarite structure with thermal ellipsoids

59. Phase-ID
Phase-ID usually undertaken using vendor-supplied software with the ICDD Database (PDF2 or PDF4)
The database is not free so budget accordingly
PDF4 requires yearly renewal but has more features
PDF2 good enough for search-match and OK for 10 years
A free database called the Crystallographic Open Database (COD) exists but there is no quality checking – user beware…
The Powder Diffraction File uses XRD ‘fingerprints’ – if they haven’t been deposited they won’t show up
Database entries are allocated a ‘quality mark’ but occasionally the newer ones are actually worse!
Experimental quality marks ‘*’ > ‘I’ > ‘A’ > ‘N’ > ‘D’
Calculated from ICSD, etc ‘C’
Background subtraction recommended before search-match if it is high but don’t bother with Ka2 stripping, etc

60. Phase-ID Improve your odds in the search-match
make a sensible guess as to the likely elements
does your sample really have plutonium in it?!
if you have elemental analysis results then use them
but consider possibility of amorphous phases
Search-match in EVA on a sample of zircon

61. Be sensible… Use common/chemical sense
don’t believe results just because the computer tells you
even oxygen has entries in the PDF2!
Where software supports it ‘residue’ searches can be very helpful in identifying minor phases

62. Don’t be led astray…
Minor peaks - make sure they aren’t Kb or tungsten lines
vendor software can often identify these (e.g. EVA below)
WLa
CrKa
CrKb

63. No luck – what next? Do you have a large systematic error in the data?
your diffractometer alignment should be checked regularly with a standard
modern search-match software can cope with a reasonable error but it has limits
Look for possible analogues which may appear in the PDF2
LaCoO3 similar to LaNiO3 with slightly different lattice parameters
analogues may have significantly different relative intensities
however: LiMnO2 (Pmmn) completely different from LiCrO2 (R-3m)
LaCoO3, R-3c
a = 5.449, c = Å
LiMnO2
LaNiO3, R-3c
a = 5.456, c = Å
LiCrO2

64. Getting desperate yet? Put the sample under optical microscope
does it seem to have the number of phases you expect?
If it contains Fe or Co try a magnet!
Possible contamination
mortar and pestle not clean
material from micronizer grinding elements (newer corundum elements not as good as the older ones – use agate)
Last possibility to consider….
maybe you have found a new phase
then the fun really starts!

65. Conclusions…
Use the appropriate sample mounting technique for the sample and the data requirements
Graininess, microabsorption and preferential orientation are all related to particle and crystallite size
Do yourself a big favour by micronizing your sample if possible!
Preferential orientation can be corrected during analysis but the others can’t……
Assumptions of the Brindley correction never met in real life
Poor application of Brindley correction worse than no correction

66. Yet more conclusions….
There are times when the newest diffractometer (PSD, etc) isn’t the best one for the job
fluorescence can be your #1 enemy!
secondary optics can be your friend 
No such thing as the perfect configuration for everyone
VCT data can help in a number of ways
improve the detection limit for minor phases
significantly improve the quality of a structure refinement
If you don’t remember anything else remember this..
think about your samples
a one size fits all approach doesn’t work!

67. Acknowledgements Ian Madsen (CSIRO)
I couldn’t improve on his explanation of microabsorption so I used it!
Responsible for the CPD QPA round robin sample 4 which still give people nightmares
Mati Raudsepp (UBC) for spray drying the mica sample and the SEM

68. References
G.W. Brindley, “The effect of grain and particle size on X-ray reflections from mixed powders and alloys….”, Philosophical Magazine, 3 (1945),
Commission on Powder Diffraction webpage
links to all the round-robin information, guidelines and papers (freely available)

69. Questions?

70. OK so you found a new phase….
Before getting to the refinement step you have to figure out a rough idea of the structure
There are some different steps in the process
Peak fitting (most of the time)
Indexing
Space group determination
Structure determination

71. Indexing….
You need to know whether cubic, monoclinic, etc and what are the lattice parameters
The instrument should be as good as you can get it
lab data more difficult than synchrotron
In the lab it may require a special high resolution dataset over a limited range (usually only use the first lines)
Accurate peak positions the main goal
Software packages
TOPAS (LSI and LP Search), Crysfire (Dicvol, Treor, etc), MacMaille, etc

72. Space group determination….
This is where you often need to know a little crystallography….
Conventional way to do this is to study systematic absences (International Tables necessary and Chekcell software useful)
Maximum likelihood software Extsym can give a list of probable extinction symbols from a Pawley refinement (not same as SG!)
TOPAS makes a guess at extinction symbol and often correct
Sample density very useful (buy a pycnometer!)
Can then calculate ‘volume per formula unit’
Allows easy exclusion of space groups where the multiplicities are too high
With organics a rough guide of 18Å3 per non-H atom can help

73. Solution…. A number of approaches possible
Conventional direct methods (EXPO, SXTL software)
Real space methods (DASH, TOPAS, FOX, etc)
Charge flipping (Superflip, TOPAS, etc)
Real space methods tend to be more reliable with poor resolution data
Powder diffraction data often regarded as ‘poor’ by default
Charge-flipping a powerful method with higher resolution powder data
has been know to work with iffy data, but not mine…..!

74. Example…. aspirin Aspirin tablets usually very pure
Done with capillary transmission but…
Highly crystalline organic with reflections to high 2q angles
Easily indexed to a monoclinic cell
Charge flipping does need a space group to work
Basic structure solves in a matter of minutes…

75. Example... sucrose Even easier to get hold of than aspirin
Also highly crystalline
Simulated annealing with a z-matrix works with normal data, charge flipping with VCT data

76. Example... wollastonite
An inorganic reflection example…. but a difficult one
Wollastonite needles show severe preferential orientation when top-loaded
Normally I would say ‘make a better sample’ but sometimes it will still works
The basic simulated annealing approach still the same with some tweaks
SEM of wollastonite

77. Wollastonite – SA strategy
TOPAS input file setup
Space group P-1
SiO4 always tetrahedral – safe to use simple z-matrix
Anti-bump for Ca-Ca, Ca-O and Si-Si
Octahedrally coordinated Ca-O
Too many oxygens with SiO4 z-matrices
Need to merge oxygens to get correct unit cell contents
Use “occ_merge O* occ_merge_radius 0.9”

78. Wollastonite – SA strategy
TOPAS lets you to use a ‘trick’ to solve badly orientated data
for details read the paper!
The structure from simulated annealing matches the literature
Literature structure
Raw structure from SA with 4th order SH – blue atoms are merging oxygens

79. Wollastonite – SA strategy
Just a couple of plots to prove the sample was orientated!
Simulated powder pattern from the SA structure without PO correction
Fit to the data for the raw SA structure with 4th order SH