Rietveld texture analysis of
SKAT diffractometer data
R.N. Vasin
STI-2011, 6-9 June, 2011, Dubna, Russia
SKAT texture diffractometer
Beamline 7a of IBR-2.
Main objectives: investigation of
crystallographic textures of rocks
and engineering materials.
Total flight path: 103.81 m.
Range of d-spacings: 0.6-4.8 Å.
Resolution Δd/d up to 0.55% (d ≈
2.2 Ǻ).
19 3He detectors on the mounting
ring, unique scattering angle of
2θ = 90.
Geometry of diffraction experiment on the SKAT
Acquisition of experimental pole figures
A
S
S
A
S
A
Schematic view of the SKAT
detector system. Usually, 19
detector modules are used.
They are named from A to S,
with S in the center of the
pole figure.
The line on the unit sphere
corresponds to scattering
vectors of the detector ring,
the line in the XY plane is its
stereographic projection.
The grid of the measured
pole figure. Small circle
corresponds to the plane
projection of the scattering
vectors, dots shown where
the data on pole density are
situated.
Data processing
Neutron diffraction spectra: 1368 (19 detectors * 72 sample positions) spectra in case of regular 5х5º PF grid
Complete experimental pole figures (measured
simultaneously - TOF-method!) in regular 5х5º grid
Recalculation of the ODF
Recalculation of non-measured
pole figures using the ODF
(absent reflections, overlapped
peaks, out of diffractometer’s
d-range)
ODF
characterization:
texture index,
entropy, construction
of the ODFhistogram and ODFspectrum
Calculation of bulk physical properties,
application in residual stress
measurements, etc.
Data processing: construction of experimental PF
We have: raw SKAT data
(1368 datafiles: binary, big-endian, 6200 bytes + SKAT protocol file: plain text, contains
monitor counts).
Front-end processing.
Conversion to little-endian (from least- to
most-significant byte) order, assortment
of files into subdirectories, extraction of
monitor counts from the protocol file,
summation/normalization of spectra are
performed.
Quartzite
Quartz, P3221
Sum of 1368 spectra
Diffraction peaks (+ background
intervals in vicinity) are selected for PF
construction.
What are those peaks?
Determination of the phase/mineral (in
case of poly-phase material) and Miller
indices for chosen diffraction peaks.
Data processing: construction of experimental PF
Quartzite
Quartz, P3221
Determination of the phase and Miller indices for chosen diffraction peaks:
comparison with the database.
In general, intensive non-overlapped peaks of the single phase are needed!
Data processing: construction of experimental PF
Biotite gneiss:
Quartz, P3221, SiO2
Biotite, С2/c, K(Mg,Fe,Ti)3(AlSi3O10)(F,OH)2
Plagioclase, P-1, (Ca,Na)(Al,Si)4O8
Intensive non-overlapped peaks of the single phase?? – maybe at d > 3.5 Å (TOF > 2100)…
Data processing: construction of experimental PF
PF visualization, rotation,
normalization, ...
Construction of
experimental PF from
chosen diffraction peaks
(in SKAT grid)
Conversion (interpolation) of
experimental pole figures
into regular 5х5° grid.
Conversion of datafiles with PF corresponding to one phase into some conventional format:
structural info is needed (Laue class, cell parameters, ratio of structure factors for overlapped
peaks of this phase). For example: short Berkeley program for conversion into standard
Berkeley-format (serves as input in BEARTEX).
Repeat for each phase.
Orientation distribution function calculation
from experimental PF + some other options
BEARTEX (WIMV method)
H.-R. Wenk & S. Matthies
http://eps.berkeley.edu/~wenk/TexturePage/beartex.htm
Operations with ODF, PF, inverse PF,
PF modeling, tensor averaging
(calculation of physical properties), …
Single license – 2000$ (academic – 1000$)
Some routines do not function in 64-bit OS!
LABOTEX (ADC method)
K. Pawlik
http://www.labosoft.com.pl/index.htm
Operations with ODF, PF, inverse PF, …
Single license – 6000$ (academic – 3000$)
Standard data processing procedure
Front-end processing
Raw SKAT
data
Selection of diffraction peaks
for use in the construction of
experimental PF
Comparison with the database
(containing model spectra)
Are these
peaks present
in database?
No
Search for the
structural info, load it
into database
ODF of each phase
Yes
No
Is there enough nonoverlapped diffraction
peaks for each phase?
Is there a good agreement
between experimental and
recalculated PF?
Yes
No
Yes
Construction of experimental PF,
PF conversion into conventional
format, ODF reconstruction
Standard data processing procedure: drawbacks
• Evident problems with the selection of non-overlapped intensive peaks from
diffraction patterns in case of multiphase sample (especially if several low-symmetry
phases are present). Usually in this case diffraction peaks are selected at high-d
region, where counting statistics are not so good.
• Only a small part of acquired diffraction patterns is used (≤ 6 peaks for each phase).
And, for example, for Ni (space group Fm-3m) in SKAT d-range at least 12 peaks are
easily available, for oligoclase An16 (space group P-1) in interval d > 1.5 Å – more
than 400 peaks.
• The result of the standard data processing is the ODF, no additional information is
retrieved (like cell parameters, phase volume fractions, etc.)
• New detector rings for SKAT (at different scattering angles) may add some
complexities.
Solution: it is possible to use Rietveld method for simultaneous processing of all (e.g.,
1368) SKAT spectra with account for crystallographic texture (this is requirement!).
No need for manual peak selection, most part of available data is used, additional info
about crystal structure of the sample is received.
MAUD
http://www.ing.unitn.it/~maud/
L. Lutterotti, "Total pattern fitting for the combined sizestrain-stress-texture determination in thin film
diffraction“, Nuclear Inst. and Methods in Physics
Research, B, 268, 334-340, 2010.
Freeware!
Java-based, needs JVM to work, but
this exists for very much every system.
Versions for Windows, Mac OS,
Linux, Unix (x86 и x64) are available.
User-friendly (fine GUI).
It’s possible to work with X-ray
/synchrotron, electron, neutron diffraction
patterns (TOF is included).
Great options for texture evaluation:
ODF calculation from the set
of diffraction spectra
(several methods are available).
MAUD
And what about TOF spectra?
SKAT data analysis by MAUD: what do we need?
• SKAT instrument parameter file (TOF channel to d conversion: scattering angle, delay,
DIFC constant ~ L·sinθ; effective spectrum; peak shape) in GSAS format (.prm).
Calibrations have been made for each of 19 detectors of the SKAT (different
calibrations for different reactor cycles!); vanadium spectrum have been fitted
by FitSpec routine of GSAS, function №4 has been used (MAUD uses
functions № 0…5): Maxvellian term + first 10 Chebyshev polynomials of the
first kind; peak shape have been approximated by function №1 TOF (the only
one available in MAUD???): Gaussian convoluted with two exponentials,
accounts only for the instrument-dependent peak broadening in MAUD.
• SKAT datafiles in standard GSAS format (.gda)
It’s not a problem to convert binary file to the formatted ASCII with the proper
header. But it’s too complicated and time consuming to perform manually for
each of 1368 spectra.
• Load all the datafiles into MAUD taking into account the position on the pole figure
(two angles!) and monitor counts.
It’s too complicated and time consuming to perform manually for each of 1368
spectra.
The fit is not perfect due to some peculiarities
of the vanadium spectrum, its better to use
“point-to-point” normalization.
SKAT2MAUD
«Mass transformation» of
spectra and construction
of the special script file to
automatically load all the
data into MAUD.
C++ based.
Ease to use GUI.
Tested in WinXP Pro x86
& Win7 HP x64.
File access is made
through Win API
functions → it is fast.
Conversion +
normalization + script
creation for 1368 files
takes ≈ 15 sec.
A possibility to easily add
some other IBR-2
diffractometers.
SKAT2MAUD
Selection of parameters for
the data conversion
Spectra selection
Monitor counts extraction
from the SKAT protocol file
Construction of
the script file for
MAUD and of
the protocol.
Options for
point-to-point
data
normalization
Data type
selection
Ni powder
The refinement of diffractometer parameters and peak shapes
(to get unique parameters for each detector!)
Different (most of the time slightly different) parameters for different reactor cycles!
Sum spectrum (detectors from A to S)
Ni powder
Detector E
Detector D
Detector C
Detector B
Detector А
Ni powder
S
(111) peak
Detectors:
A
(222) & (311) peaks
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Sample: Outokumpu borehole (Finland), 676 m depth. Mineral composition: quartz –
42.6 vol.%, plagioclase – 37.6 vol.%, biotite – 19.8 vol.% (thin sections analysis, Kern,
Mengel, Strauss et al. // PEPI, 175, 2009. 151-166). Volume of the sample is > 100 cm3.
Lattice spacing range: d = 1.51…4.31 Å → about 700 diffraction peaks/pole figures.
Getting prepared for intensive calculations: MAUD command file is altered – now
MAUD exclusively allocates 3 Gb of RAM (should be working on x64 OS or x86 with
enabled PAE).
Free parameters: phase volume fractions, individual background for each spectrum
(3·1386 parameters), cell parameters of each phase, 1 thermal factor for all atoms
(isotropic approximation), crystallite size and microdeformation for each phase (isotropic
approximation) – in total 4145 parameters. + ODF calculation for each phase, E-WIMV
method, 5° ODF resolution, peaks with intensity less than 1% of maximum for the given
phase were not used for the ODF calculation.
1 iteration took ≈ 3 h. 40 min. (Intel Core i5-430M, 4 Gb DDR3-1066(CL7), Win7 HP
x64, x64 Java Virtual Machine).
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
First 12 spectra, detector A, point-to-point normalized in SKAT2MAUD.
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Q(100) + Pl(030)
Pl(-201)
Q(101) + Q(011) +
Bi(600) + Bi(402) +
Pl(-112) + Pl(-221)
Bi(-411) + Pl(-210)
Pl(002) + Pl(-220) +
Pl(-1-22) + Pl(040) +
Pl(-202)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
SKAT pole figure coverage for the
676 gneiss sample (different colors
correspond to different number of
counts of the beam monitor).
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Biotite rec. PF, log scale, MAUD (ODF: texture index F2=5.67)
2M1 polymorph
(space group C2/c).
Setting 1 is used for
the monoclinic biotite
here and further.
Biotite rec. PF, log scale, conventional PF analysis (ODF: texture index F2=3.30)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Plagioclase rec. PF, MAUD (ODF: texture index F2=1.27)
Plagioclase rec. PF, conventional PF analysis (ODF: texture index F2=1.23)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Quartz rec. PF, MAUD (ODF: texture index F2=1.24)
Quartz rec. PF, conventional PF analysis (ODF: texture index F2=1.30)
Are indistinguishable in conventional PF analysis because overlapped PF
of rombs – (h0l) + (0hl) – have not been selected for ODF calculation.
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Is it possible to use less data and get
the ODF with acceptable resolution?
PF coverage (1/20 from the available
data).
ODF resolution of 7.5° has been
chosen in E-WIMV (instead of 5° as
it was in the case of full dataset) to
account for the decrease in the
quantity of data.
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Biotite rec. PF, log scale, full coverage (ODF: texture index F2=5.67)
Biotite rec. PF, log scale, reduced coverage, ODF resolution 7.5° (ODF: texture index F2=8.99)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Plagioclase rec. PF, full coverage (ODF: texture index F2=1.27)
Plagioclase rec. PF, reduced coverage, ODF resolution 7.5° (ODF: texture index F2=1.39)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 676
Quartz rec. PF, full coverage (ODF: texture index F2=1.24)
Quartz rec. PF, reduced coverage, ODF resolution 7.5° (ODF: texture index F2=1.37)
Outokumpu 676 (a comparison of cell parameters with the
American Mineralogist crystal structure database)
Phase
Biotite,
C2/c
Quartz,
P3221
Data
from:
SKAT
(MAUD)
Database
(Mg/Fe+Mg
+Mn+Ti)
SKAT
(MAUD)
a, Å
20.2269(1)
19.976
/20.196
b, Å
5.3599(1)
c, Å
Database
Plagioclase,
P-1
SKAT
(MAUD)
Database
An16/28/48
4.91285(2) 4.91343
8.1533(1)
8.154/8.169
/8.179
5.3175
/5.339
4.91285(2) 4.91343
12.8468(2)
12.823/12.851
/12.880
9.2108(2)
9.212
/9.249
5.40451(4) 5.40512
7.1235(1)
7.139/7.124
/7.112
α, °
90
90
90
90
93.88(1)
94.06/93.63/
93.44
β, °
90
90
90
90
116.36(1)
116.50/116.40/
116.21
γ, °
94.99(1)
95.09/95.06
120
120
89.25(1)
88.59/89.46
/90.23
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
Sample: Outokumpu borehole (Finland), 818 m depth. Mineral composition: quartz – 39.9
vol.%, plagioclase – 37.4 vol.%, biotite – 22.6 vol.% (thin sections analysis). Volume of the
sample is ≈ 100 cm3.
Outokumpu 676
Outokumpu 818
Two biotite peaks
almost disappear
from the sum
diffraction pattern of
the 818 sample. The
reason for this is
higher crystal
symmetry of biotite
in 818 sample:
in 676 → C2/c
in 818 → C2/m
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
SKAT pole figure coverage for the
818 gneiss sample.
Full coverage (72 sample positions).
Measurement time: 36 hours.
ODF resolution of 5° has been used
¼ coverage (18 sample positions).
Measurement time: 9 hours.
ODF resolution of 7.5° has been used
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
Biotite rec. PF, log scale, full coverage (ODF: texture index F2=4.69)
1M polymorph (space
group C2/m).
Setting 1 is used for
the monoclinic biotite.
Biotite rec. PF, log scale, ¼ coverage (ODF: texture index F2=6.19)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
Plagioclase rec. PF, full coverage (ODF: texture index F2=1.23)
Plagioclase rec. PF, ¼ coverage (ODF: texture index F2=1.20)
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
Quartz rec. PF, full coverage (ODF: texture index F2=1.16)
Quartz rec. PF, ¼ coverage (ODF: texture index F2=1.20)
GEOMixSelf elastic properties calculation of the Outokumpu
biotite gneiss 818 (spherical grains, no pores)
Full coverage
VP
VS splitting
¼ coverage,
VP velocities
change by
about 30 m/s
≈ 0.5%, max
VS split
increase by
≈ 8%
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818: ODF spectra
Biotite
Full coverage
Biotite
¼ coverage
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818: ODF spectra
Biotite
Full coverage
Biotite
¼ coverage
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818: ODF spectra
Plagioclase
Full coverage
Plagioclase
¼ coverage
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818: ODF spectra
Quartz
Full coverage
Quartz
¼ coverage
Neutron diffraction texture analysis of the Outokumpu
biotite gneiss 818
Phase
Quartz
Biotite
Plagioclase
Volume fraction,%
38.65(4) / 38.94(7) / 39.9 23.96(5) / 23.55(9) / 22.6 37.39(5) / 37.51(10) / 37.4
Texture index F2
1.16 / 1.20
4.69 / 6.19
1.23 / 1.20
Rb index (texture
11.95 / 11.92
refinement quality), %
a, Å
4.91237(2) / 4.91246(4)
17.54 / 16.12
15.93 / 16.12
10.2347(1) / 10.2363(2)
8.1498(1) / 8.1500(1)
b, Å
4.91237(2) / 4.91246(4)
5.3236(1) / 5.3260(3)
12.8366(1) / 12.8366(3)
c, Å
5.40422(5) / 5.40414(8)
9.2580(2) / 9.2545(4)
7.1299(1) / 7.1297(2)
α, °
90
90
93.926(5) / 93.920(4)
β, °
90
90
116.428(1) / 116.427(2)
γ, °
120
100.068(5) / 100.117(4)
89.073(1) / 89.077(3)
Full coverage
¼ coverage
Phase analysis via thin sections
(Kern, Mengel, Strauss et al. //
PEPI, 175, 2009. 151-166)
Only notable changes are in cell parameters and
texture index of the biotite. This may be due to:
1) Biotite peaks are the least intensive and they are
“lost” in the noisy pattern.
2) Should account for 1M and 2M1 polymorphs
coexistence in the sample?
Outokumpu 818: comparison with the HIPPO data
HIPPO PF coverage (includes different
detectors on different scattering angles) –
by courtesy of Prof. H.-R. Wenk.
HIPPO diffractometer
(Los-Alamos)
Volume of the sample is about 1 cm3!
4 sample positions have been measured, 2
hours per position, in total 8 hours of
measurements.
Outokumpu 818: comparison with the HIPPO data
Spectra from 90° detectors of SKAT
Spectra from 144° detectors of HIPPO
Outokumpu 818: comparison with the HIPPO data
Biotite rec. PF, log scale, full coverage (ODF: texture index F2=4.69)
Biotite rec. PF, log scale, HIPPO, 10° resolution (ODF: texture index F2=8.90)
Outokumpu 818: comparison with the HIPPO data
Quartz rec. PF, full coverage (ODF: texture index F2=1.16)
Quartz rec. PF, HIPPO, 10° resolution (ODF: texture index F2=1.18)
Outokumpu 818: comparison with the HIPPO data
Plagioclase rec. PF, full coverage (ODF: texture index F2=1.16)
Plagioclase rec. PF, HIPPO, 10° resolution (ODF: texture index F2=1.22)
Neutron diffraction texture analysis of the quartzite
sample 26а
PF coverage used. Only 114 spectra
(1/12 of the full coverage), sample
positions 00 = 0°, 12 = 60°, 24 = 120°,
36 = 180°, 48 = 240°, 60 = 360°.
Range of lattice spacings d = 0.6-3.4 Å
(≈ 310 diffraction peaks, i.e., 310 pole
figures).
ODF was recalculated by the E-WIMV
method, 5° resolution, exp. pole figures
(100), (110), (012+102).
Complete PF measurements took 15 h.
36 min.
1/12 of full coverage was possible to
measure in 1 h. 18 min.
Neutron diffraction texture analysis of the quartzite
sample 26а
Single spectrum, detector A, sample position 12.
(012+102)
(100)
(110)
Neutron diffraction texture analysis of the quartzite
sample 26а
Quartz rec. PF, MAUD, 1/12 coverage (ODF: texture index F2=2.24)
Quartz rec. PF, conventional PF analysis, exp. pole figures (100), (110), (012+102) &
WIMV method via BEARTEX (ODF: texture index F2=2.35)
Neutron diffraction texture analysis of the quartzite
sample 26а: ODF spectra
Quartz
1/12 coverage
MAUD
E-WIMV
Quartz
Conventional
PF analysis, 4 PF
WIMV via BEARTEX
Quartzite sample 26а: a comparison of cell parameters
26a,
SKAT
(MAUD)
Quartz
powder,
X-ray
26a,
SKAT(MRIA,
sum spectrum,
old calibration)
a, Å
4.91288(2)
4.91343
4.91572(3)
b, Å
4.91288(2) 4.91343
4.91572(3)
c, Å
5.40442(4)
5.40512
5.40639 (7)
α, °
90
90
90
β, °
90
90
90
γ, °
120
120
120
Quartz: space group P3221.
X-ray data after:
Antao SM, Hassan I, Wang J, Lee PL,
Toby BH. State-of-the-art highresolution powder x-ray diffraction
(HRPXRD) illustrated with Rietveld
structure refinement of quartz, sodalite,
tremolite, and meionite. // The
Canadian Mineralogist. 46 (2008)
1501-1509.
Zr alloy E-110 samples
Cylindrical plugs of fuel elements of the VVER-1000 reactor,
Zr+1%Nb, space group P63/mmc.
d-range used = 0.89-2.89 Å (1 iteration in MAUD ≈ 40 min.).
Sample
coordinate
system KA
ZA, σ3
YA, σ2
XA, σ1
002
110
Zr alloy E-110 samples: texture analysis of the coldworked sample
PF exp.
PF rec. (WIMV, 6 peaks). F2=3.38.
PF rec. (MAUD, E-WIMV, 22 peaks in the d-range). F2=3.60.
Zr alloy E-110 samples: texture analysis of the coldworked sample
Let’s use ¼ coverage:
, and even a smaller number of diffraction peaks.
Can we still get the ODF with 5° resolution?
PF rec. (MAUD, ¼ coverage, E-WIMV, only 6 peaks! in d-range 1.43-2.89 Å,
axial sample symmetry has not been applied!). F2=3.76. G-space cell hits min. = 10.
PF rec. (MAUD, E-WIMV, 22 peaks in the d-range). F2=3.60.
Zr alloy E-110 samples: cold-worked sample
(110) peak
(101) & (002) peaks
Peak position depends on the angle between the corresponding plane normal and the
axis of the cylindrical sample, all the peaks are shifted in the direction of smaller dvalues with the decrease of this angle.
Zr alloy E-110 samples: cold-worked sample
(110) peak
(101) & (002) peaks
Taking into account residual stresses of the 1st order. BulkPathGEOmethod has been
applied for the calculation of diffraction elastic moduli using the ODF and single-crystal
elastic constants (Voigt coding): C11 = 143.5 GPa, С12 = 72.5 GPa, С13 = 65.4 GPa, С33 =
164.9 GPa, С44 = 32.1 GPa, С66 = 0.5(C11 – С12) = 35.5 GPa.
Zr alloy E-110 samples: annealed sample
(110) peak
After the annealing process:
macroscopic residual stresses → 0;
crystallite size: 1490 → 930 Å;
microdeformation: 2·10-3 → 5·10-5.
(101) & (002) peaks
Zr alloy E-110 samples: texture analysis of the annealed
sample
PF rec. (WIMV, 6 peaks). F2=4.04.
PF rec. (MAUD, E-WIMV, 20 peaks in the d-range). F2=4.08.
Zr alloy E-110 samples: macroscopic residual stresses
Taking into account axial symmetry of the sample: σ1 = σ2, σ4 = σ5, σ6 = 0 MPa.
Sample
Diffractometer
σ1, MPa
σ3, MPa
σ4, MPa
a0, Å
c0, Å
Number of
meas.^1
Coldworked
E7, Berlin
166.0
0
-43.0
3.2342
5.1386
23
SKAT, Dubna
141.7(3)
-5.2(1)
-1.4(1)
3.2340
5.1338
19x21=399
HRFD, Dubna
136.0
0
-5.0
3.2340
5.1367
17
E7, Berlin
0
0
0
3.2295
5.1463
21
SKAT, Dubna
0
0
0
3.2285
5.1467
19x19=361^2
Annealed
^1 Number of measurements = number of diffraction peaks * number of physically
distinguishable directions of the scattering vector in the sample coordinate system KA
(taking into account axial symmetry of the sample).
^2 Two peaks at d > 2.5 Å were not used due to poor counting statistics.
Current results
• The analysis of the SKAT diffractometer data using the Rietveld method (MAUD
software) is possible, and now it is easily available. All 1368 spectra could be analyzed in
wide d-range even in case of very complex samples (e.g., > 1000 spectra and > 7∙105
diffraction peaks in total…). A number of very different samples measured during
different reactor cycles from February 1998 till December 2006 have been processed
with MAUD with no problems.
• Only 2 programs are needed to get the ODF out of diffraction patterns (SKAT2MAUD
→ MAUD) instead of 4 (e.g., GeoTOF → AutoIndex → Berkeley → Beartex).
• The d-range and the resolution of SKAT are enough to get necessary information for the
ODF reconstruction in case of rocks containing several low-symmetry and/or large-cell
minerals, e.g. monoclinic 2M1 biotite polymorph (20.2 x 5.4 x 9.2 Å) + triclinic feldspar.
But counting statistics should be increased (especially at d > 3.5 Å) due to modernized
reactor, new neutron guide, new (cold) moderator or …
• by using less sample positions (e.g., 1/6 of full coverage), but increasing the
measurement time per position (e.g., 6 times). In some cases utilization of partial
experimental PF coverage may drastically (~ 10 times) reduce total measurement time
while the ODF reconstruction with 5° resolution will still be possible.
• From the SKAT data now its possible to easily get not only ODF but also cell
parameters, phase volume fractions, 1st order residual stresses, etc.
Some things to do and suggestions
• Still there is a lot of space for the method testing/development…
• Add a few options to SKAT2MAUD.
• In future, it will be great to measure some standard sample with diffraction peaks in
wide d-range – e.g., Al2O3 – during each reactor cycle (and also the vanadium standard).
• Make a few special test experiments to verify MAUD-processed SKAT data on texture,
cell parameters, stresses, crystallite sizes, etc.
• Some more experiments, tests and discussions concerning the possibility to measure
incomplete PF & reduce measurement time per sample.
Acknowledgements
I would like to thank
Creators of SKAT and MAUD for the great instrument and the great software
Dr. Tatiana Ivankina (JINR) for the data on ODF of biotite, plagioclase and quartz for
the 676 Outokumpu sample (results of the conventional PF analysis of the SKAT data)
Yuri Kovalev (JINR) for the reminder about the GetLastError() function
Prof. Siegfried Matthies (JINR) for the software he made to convert MAUD format
ODF into conventional STD format
Dr. Vyacheslav Sumin (JINR) for HRFD and E7 data on E-110 zirconium alloy
samples and discussion of the results on these samples
Prof. Hans-Rudolf Wenk (Berkeley university) for the data on the 818 Outokumpu
sample measured on HIPPO diffractometer, and his help with the analysis of
incomplete PF of 676 Outokumpu sample measured on SKAT
Thank you!