aim of this part ta+pxrd course - helsinki
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TA+PXRD coursePart 4, Phase analysis
November 2017, Mikko Heikkilä
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Aim of this part
• XRD phase analysis, can be divided to two parts
• Qualitative XRD
• data reduction, representation, search and match
• Quantitative XRD
• Traditional methods• Quantitative Rietveld refinement
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Introduction– Qualitative and quantitative XRD
Qualitative XRD
• What’s in my sample?
• Is there more than one phase?
• Is there something that wasn’t expected and if so, what’s that?
• Is it crystalline at all?
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Introduction– Qualitative and quantitative XRD
Quantitative XRD
• after the qualitative questions are solved, one might want to know
what are the amounts of different phases
• while XRD usually probes for crystalline material, there are
methods for determining the amount of amorphous (or
unidentified!) material as well
• Phase transitions during or after heat treatments are nice
playground for qualitative and especially quantitative analyses
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Introduction– Basics of phase identification
Diffractogram is a ”fingerprint” for each material
• Identification is based on positions and and intensity ratios of
observed reflections
• Position of the reflections depends on lattice dimensions (Bragg’s law)
• Intensity ratios of the reflections depend on chemical composition
(structure factor)
→ each material has a unique diffractogram
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 5 www.helsinki.fi/yliopisto
Introduction– Basics of phase identification
Identification of polymorphs is possible
• One of the more useful features of XRD is that materials with same
composition and different crystal structure can be identified
• As an example, diffractograms of three TiO2 phases
2.12.2015
from Whitfieldand Mitchell
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 6
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Phase identification
Brief history (Adapted from Snyder & Jenkins, Introduction to X-ray Powder Diffractometry, 1996, Wiley)
Year Event1917-1919 P.J.W. Debye and P. Scherrer in Europe and A.W. Hull in the USA point out the potential advantages of
powder diffraction as a tool for qualitative analysis
1927 A. N. Winchell publishes first private collection of diffraction patterns
1935 A.W. Waldo publishes patterns for 51 copper ores
1938 J.D. Hanawalt, H.W. Rinn and L. Frevel publish a file of 1000 patterns with an indexing and search system
1938 The Institute of Mines in Leningrad tabulates powder data for 142 minerals
1941 Patterns produced on 3x5 cards by the National Research Council (NRC) and Committee AmericanSociety for Testing and Materials E4 of the (ASTM)
1941-1945 Other societies join the powder committee of ASTM
1969 The Join Committee on Powder Diffraction Standards (JCPDS) is incorporated as an independent non-profit organization
1977 JCPDS changes its name to International Centre for Diffraction Data (ICDD)
1994 The ICDD Powder Diffraction File grows to 60000 patterns
2015 The current PDF4+ from ICDD contains 365877 patterns (http://www.icdd.com/products/pdf4.htm)
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 7 www.helsinki.fi/yliopisto
Phase identification
Example of a PDF card for NaCl
2.12.2015
screen capture fromPCPDFWIN software
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Phase identification
Other databases in addition to ICDD
• ICSD – Inorganic Crystal Structure Database
• http://www.fiz-karlsruhe.de/icsd.html
• ”At present (Dec 2015), the ICSD contains more than 181,000 entries,
including”
• 2,023 crystal structures of the elements
• 34,114 records for binary compounds
• 66,292 records for ternary compounds
• 62,666 records for quarternary and quintenary compounds
• About 143,500 entries (81%) have been assigned a structure type.
• There are currently 9,136 structure prototypes.
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Phase identification
Other databases
• PCD – Pearson’s Crystal Data
• http://www.crystalimpact.com/pcd/Default.htm
• “Aims to create and maintain the world's largest critically evaluated
Non-organic database”
• “The current release 2015/16 contains about 274,000 structural data
sets”
• “about 157,000 different chemical formulas, roughly 17,900 experimental powderdiffraction patterns and about 255,000 calculated patterns (interplanar spacings,intensities, Miller indices)“
• “In addition over 45,200 figure descriptions for such as cell parameters as a functionof temperature, pressure or concentration are given.”
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Phase identification
Other databases
• COD – Crystallography Open Database
• http://www.crystallography.net/
• ”>300,000 entries in crystallographic information file (CIF) format in 2014”
• Gražulis et al., Nucl. Acids Res., 40 (2012) D420
• Gražulis et al., J.Appl.Cryst., 42 (2009) 726
• as the name implies, it’s free of charge
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Phase identification
Other databases
• CSD – Cambridge Structural Database
• http://www.ccdc.cam.ac.uk/products/csd/
• ”records bibliographic, chemical and crystallographic information for
organic molecules and metal-organic compounds”
• CRYSTMET
• https://cds.dl.ac.uk/cgi-bin/news/disp?crystmet
• “entries covering metals, alloys and intermetallics.”
• Nowadays Implemented to CSD
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Phase identification
Historical Search and match software generations
• Alphabetic method
• Names of the substances in alphabetic order, followed by chemical
formula, d-values of the three strongest lines, PDF number and
sometimes RIR-value
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä
From Snyder and Jenkins
13 www.helsinki.fi/yliopisto
Phase identification
Historical Search and match software generations
• Hanawalt method
• Patterns are sorted according to the d-value of the 100% peak
• This list is broken into smaller groups
• First column is the strongest, but the group is sorted by the second
strongest line
• Before electric format, these were browsed manually in books
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From Snyder and Jenkins
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 14
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Phase identification
Historical Search and match software generations
• Fink method
• Problem with Hanawalt system is the dependency on intensities
• Fink method uses eight strongest lines and the creates cyclic
permutatios based on four strongest
• Example of Fink index is shown below
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From Snyder and Jenkins
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 15 www.helsinki.fi/yliopisto
Phase identification
Historical Search and match software generations
• Boolean search methods
• Search against several different index keys such as Chemistry, Strong
lines, Journal CODEN, Author and Date, Physical properties, etc.
• 1st generation, mid-60’s
• Johnson-Vann approach used computer speed comparing each
reference pattern in PDF (60000 entries then) to the unknown data and
giving FOM for the best 50
• Approach by Nicholas took Hanawalt-type approach
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 16
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Phase identification
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä
Historical Search and match software generations
• 2nd generation, 70’s
• Alfred university implemented a Hanawalt-type strategy in addition to a
Johnson-Vand or Fink-like exhaustive approach with hierarchical use of
databases
• Much better at identifying unknown multiphases
• Commercial version by Siemens used hierarchical approach
• First searched against smaller 300 phases database, then 2500 frequent
phases and finally the full PDF
• The key to success was the creation of reliable residual pattern after a
phase was found for further searching17 www.helsinki.fi/yliopisto
Phase identification
Historical Search and match software generations
• 3rd generation, late 80’s
• In this approach the whole observed pattern with its background (not just
I-d –list) is searched and candidate phases are added together to
compose, rather than decompose, an observed multiphase pattern
• The results are now heavily influenced by where peaks do not occur
instead of only by where they are present
• Much faster searches against full database
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 18
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Phase identification
Present Search and match softwares
• Modern softwares use previous or their own implementations with
different scoring (or FOM) schemes
• Hardware vendors usually provide a software for phase ID
• EVA (Bruker-AXS)
• Highscore (PANalytical)
• PDXL2 (Rigaku)
• Softwares by others
• Match! (Crystal Impact) http://www.crystalimpact.com/match/Default.htm
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 19 www.helsinki.fi/yliopisto
Phase identification
Database usage within search&match softwares
• latest version of Highscore can use multiple databases
• However, only NIST version of FIZ-ICSD
• Match! does that as well, also EVA
• although EVA don’t seem to be able to search against ICDD and free
COD database at the same time
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 20
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Phase identification
Data preprocessing
• Background determination
• Conversion from ADS to FDS if necessary
• For proper comparison of intensities
• Smoothing might help if data is noisy, but it might add artifacts to the
data
• Ka2 stripping may help in determining peak positions in multiphase
mixtures where at higher angles Ka1 and Ka2 are more separated
• Peak search
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 21 www.helsinki.fi/yliopisto
Phase identification
Data preprocessing
• Peak profile fit if possible
• More accurate peak position
• Peak shape/width can be used as a parameter in searches with some
softwares (at least with Highscore Plus)
• if unknown mixture has phases with very different crystallite sizes, the
reflections belonging to certain phase can be estimated from similar peak
widths
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 22
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Phase identification
Thin films
• No sample preparation possibility
• If large preferential orientation or texture is present, it’s useful to
use multiple measurement modes for phase identification
• In the example, only two peaks
are present in q-2q scan
making identification difficult
• When measuring in grazing
incidence, more peaks appear
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 23 www.helsinki.fi/yliopisto
Phase identification
2.12.2015
Several round robins have been conducted on this, example
below was published in 2003
• Very useful info here:
http://www.nist.gov/mml/upload/6-1_NScarlett_APD_IV.pdf
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Phase identification- CuOX example
2.12.2015
• Highscore Plus
software is used for
these examples,
since our version of
EVA is so outdated
• the example is a thin
film sample that was
supposed to be Cu2O
• first, the background
is determined
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 25 www.helsinki.fi/yliopisto
Phase identification- CuOX example
2.12.2015
• next part is the peak
search
• different parameters
can be used for
finding peaks
• closer examination
of the diffractogram
is usually in order to
add missing peaks
or remove ones that
don’t belong thereTA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 26
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Phase identification- CuOX example
2.12.2015
• after peaks are
found, database
search&match is
next
• in this case
multiphase was
preferred and small
shift was accepted
(sometimes caused
by GIXRD geometry)
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Phase identification- CuOX example
2.12.2015
• elemental restrictions
were applied, so that
Cu has to be in the
sample and O is a
possibility
• quality restricitions
may also be used
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Phase identification- CuOX example
2.12.2015
• it was found that film
consisted mainly of
copper and some
oxide in the form of
cuprite (Cu2O) was
also present
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 29 www.helsinki.fi/yliopisto
Phase identification- YSZ example
2.12.2015
• another example is a
yttrium stabilized
zirconia (YSZ)
substrate that was
delivered to us
• the diffractogram
seemed to contain
too many peaks,
what might be the
cause for that?
• peak search firstTA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 30
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Phase identification- YSZ example
2.12.2015
• elemental
restrictions are
applied next
• oxygen was made
compulsory since
the material is most
likely all oxides
• in case Y and Zr
oxides are both
there, ”at least one
of” was selectedTA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 31 www.helsinki.fi/yliopisto
Phase identification- YSZ example
2.12.2015
• yttrium content of
YSZ was given by
supplied as 15 %
• pattern with that
composition fits well,
but explains only
small part of the
features
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 32
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Phase identification- YSZ example
2.12.2015
• the second
candidate on the list
was monoclinic ZrO2
which explains most
of the remaining
features
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 33 www.helsinki.fi/yliopisto
°2Theta302928272625242322
Tem
pera
ture
(°C
)
1 000900800700600500400300200100
Phase identification- non-ambient examples
Non-ambient measurements
• Peak shift due to thermal expansion has to be taken into account
• thermal expansion complicates phase identification at high
temperatures
• Reference cards are usually measured at room temperature
• Anisotropic thermal expansion makes things even worse
• In the figure, Nb2O5 crystallizes
at 575 °C, above that the
29°2q peak shifts 0.3°2q
when heated to 1075 °C
• No shift with 22.7°2q peak 2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 34
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End of qualitative part
Time for questions.
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Quantitative phase analysis- Introduction
• Quantitative phase analysis (QPA) is one of the most important
industrial applications of powder XRD, often taking place in quality
control
• most often used approach in industry quality control is to measure
the chemical composition alone (easy, accurate, often XRF)
• Even when crystal phase is used for plant optimization, it is often derived
from bulk chemical analysis
• However, the most direct method to obtain phase related
information is diffraction since the information is acquired straight
from the crystal structure instead of deriving from secondary
information2.12.2015
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 36
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Quantitative phase analysis- Introduction
• Relationships between diffracted peak intensity and the quantity of
phase in a mixture producing the peak are well established
• In industry quality control these analyses are most often very
automatized with batch measurements from sample changers
• To keep things simple, softwares often compare only single peaks
• Many factors complicate the analysis
• Experimental sample and instrument related effects, like counting errors,
preferred orientation etc.
• Largest errors most likely caused by the operator…
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Quantitative phase analysis- Introduction
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä
Quantification of powder diffraction data can be divided in two
different methods
• Single peak methods
• measurement of a certain peak(s) for each phase of interest and
assumes that the intensity of the peaks are representative of their
amount in the mixture
• Whole pattern methods
• comparison of diffraction data with a calculated pattern formed
from the summation of individual phases that have been either (i)
measured from pure phase samples or (ii) calculated from crystal
structure38
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Quantitative phase analysis- Introduction
Some dates worth mentioning (Adapted from Snyder and Jenkins)
)Year Event1919 Hull suggested the possibility of quantitative phase analysis using powder
XRD
1925 Navias quantified the amount of mullite in fired ceramics
1936 Clark and Reynolds used fluorite as internal standard for determining quartzin mine dusts
1948 Alexander and Klug described the theoretical background for the absorptioneffects on diffraction intensities in quantitative analysis
1978 The practice of quantitative analysis was described in comprehensive bookon X-ray powder diffraction by Klug & Alexander
A lot has happened later, most importantly the rise of Rietveldrefinement as the most used method for quantitative phase analysis
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 39 www.helsinki.fi/yliopisto
Quantitative phase analysis
Mathematical background for single peak methods
• The integrated intensity I of reflection hkl for phase a in a multi-
phase mixture measured on a flat-plate sample of infinite
thickness can be calculated from
• The first square bracket is constant for used experimental setup
and the second a constant for reflection hkl for phase a
( ) ( ) ( )3 4 2 22
02 4 2 2 *
1 cos 2 cos 2 132 2 sin cos
hkl mhkl hkl
e m
I e M XI Frm c V
aa a
a a
l q qp q q r m
é ùé ù é ùæ ö+= ´ ´ê úç ÷ê ú ê ú
è øë û ë ûë û
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 40
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Quantitative phase analysis
2.12.2015
Mathematical background for single peak methods
• The Eq.1 can now be presented in simplified form:
where Cia = constant for reflection i of phase a
• The fundamental problem lies in the mass absorption coefficient
of the mixture
• Since there are two unknowns in single equation
• It is possible to estimate the mass absorption coefficient of the mixture by
either calculating or measuring it
( )* 2i im
XI C aa a
ar m=
* *
1m m
=
= ån
m i ii
X
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Quantitative phase analysis– Absorption – diffraction method
• equation (2) is written twice, once for the line i of phase a in the
unknown and again for the same line of a pure sample of phase a
• This simplification applies if the mass attenuation coefficients of the
mixture and the phase to be analyzed are the same
• useful for a mixture of polymorphs, e.g. TiO2 or ZrO2
( )*
0 * 3i
m
mi
XCI X XXI C
aa
a a aa a
aaa
a a
r m mm
r m
= = »
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Quantitative phase analysis– Spiking method
Method of standard additions, a.k.a. spiking method
• Based on adding known amounts of phase a which has a
diffraction line not overlapping by any line in the mixture and similar
mass absorption as the mixture
• Phase β is not analyzed and does not even need to be an identified
phase
• For a mixture containing phases a and β, the ratio of intensities
becomes
2.12.2015
( )4i
ii
j jj
XCC XI
XI C XC
aa
a b aa a a
bb b a bb
b b
rr mr
r m
= »
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 43 www.helsinki.fi/yliopisto
Quantitative phase analysis– Spiking method
Method of standard additions, a.k.a. spiking method
• After adding mass Ya to the mixture containing an unknown
amount of a, the equation can be written
• plotting Ia/Iβ vs.Ya will produce a straight-line, where the slope is K
and Xa is the negative x-axis intercept
( ) ( ) ( )5ii
j j
C X YI K X YI C X
a b a aaa a
b b a b
rr
+= = +
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 44
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Quantitative phase analysis– Spiking method
• Example shown below
• Problems will occur if addition of the phase a significantly changes
the mass absorption of the sample
• Because of tedious sample preparation and data errors
encountered at low concentrations of
both phases, this is seldom
applied in quantitative
analysis. From Snyder & Jenkins
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 45 www.helsinki.fi/yliopisto
Quantitative phase analysis– Internal standard method
2.12.2015
• the problems caused by µm* can be eliminated by adding a known
amount of Xs of internal standard s to the mixture
• K is a calibration constant determined by plotting Iia/Ijs vs. Xa/Xs
• to avoid microabsorption effects, the mass absorption coefficients
and the particle size of the internal standard should be a close
match to the mixture
( )*
*
6i
i m
sjs sjs
s m
XCI XKXI XC
aa
a a ar m
r m
= »
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Quantitative phase analysis– Internal standard method
• After the calibration of K, the concentration of phase a can be
obtained using the equation
and the weight fraction of phase a if the original sample using
equation
2.12.2015
( )7i s
js
I XXI K
aa
´=
´
( ). 81
orig
s
XXXa
a =-
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Quantitative phase analysis– Internal standard method
Notes on internal standard method
• the use of peak heights instead of integrated intensities can be
unreliable
• Since the internal standard is often very crystalline, the ratio of peak
intensities will be affected by possible peak broadening behaviour if
sample crystallinity is low
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Quantitative phase analysis– Internal standard method
Notes on internal standard method
• Peak overlap between the standard and the sample should be
avoided
• Chosen standard should have strong reflections to avoid the need
to add large quantities of it
• e.g. NIST SRM674 was designed for this purpose
• 10g of each ZnO, TiO2, Cr2O3 and CeO2 packed under argon
• 714 $
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Reference intensity ratios (RIR)
• The concept behind the most common RIR method is to provide a
intensity ratio of the 100% intensity peak of a phase a to the 100%
(113) peak of corundum in a 50:50 mixture
and defining K as RIR
• PDF2 database contains RIR-values for many materials, but unfortunately in most
cases only peak intensity instead of integrated area is used
Quantitative phase analysis– Reference Intensity Ratios (RIR)
2.12.2015
( )9cor cor
I XKI X
a a=
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• This can be generalized for other reference materials as well:
• The Irel term ratios the relative intensities of the peaks used
• if the 100% peaks of both phases are used, the value of this term is 1
• RIR is still the slope of the calibration curve for phase a with
internal standard β but now has been normalized so that it may be
computed from any pair of diffraction lines in a mixture
Quantitative phase analysis– Reference Intensity Ratios (RIR)
2.12.2015
( ), 10relji irel
j i j
I X XI IRIRI I X I X
b b ba aa b
b a a b a
æ ö æ öæ öæ ö æ ö= =ç ÷ ç ÷ç ÷ç ÷ ç ÷ç ÷ç ÷ ç ÷è ø è øè øè ø è ø
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 51 www.helsinki.fi/yliopisto
• Rearranging the previous equation one gets
• The RIR value in this equation can be obtained through careful
calibration, by determining the slope of the internal standard plot,
or by derivation from other RIR values via
Quantitative phase analysis– Reference Intensity Ratios (RIR)
2.12.2015
( ),
11i
j
XIXI RIR
baa
b a b
æ öæ ö= ç ÷ç ÷ç ÷ç ÷
è øè ø
( ),,
,
12RIR
RIRRIR
a ga b
b g
=
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Quantitative phase analysis– Reference Intensity Ratios (RIR)
• For a system consisting of n phases in which all components are
crystalline and included in the analysis, the following constraint can
be used:
• The effects of sample attenuation can be removed by applying this so-
called matrix flushing (or normalized RIR) method
• Using this in combination with equation (11) one gets
and the weight fraction of phase a is
2.12.2015
( )1
1 13n
kk
X=
=å
1
1
ns ik
kjs ks
X II RIR
-
=
æ ö= ç ÷
è øå
( )1
114
nik
ks ks
I IXRIR RIR
aa
a
-
=
æ ö= ´ç ÷
è øå
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Quantitative phase analysis– Reference Intensity Ratios (RIR)
• The application of equation (14) assumes that all phases are
crystalline
• By adding internal standard allows calculation of the absolute
amount of each phase:
• Then for the unknown part:
2.12.2015
( )( )
( )( )15std known
absstd meas
XX X
Xaa = ´
( ) ( ) ( )1
1 16n
unknown k absk
X X=
= - å
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Quantitative phase analysis– Rietveld methods
Rietveld methods
• more accurate than conventional single line methods because
• all of the peaks in the pattern contribute to the analysis, regardless
of the degree of overlap
• some sample effects, such as preferred orientation, are minimized
(or at least can be taken into account) when using all reflections
• Elemental analysis (e.g. XRF data) can be used as a restriction
in quantitative analysis
• mineral samples with >10 phases quantified surprisingly well
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 55 www.helsinki.fi/yliopisto
Quantitative phase analysis– Rietveld methods
• originally developed for structure solution
• in addition, one can get useful, non-structural information from
observed and calculated patterns
• peak width and shape contain information about microstructure
• scale factor (in multiphase mixture) relates to the amount of the phase
present
• gets a bit more complicated, enough to talk for some hours
→ I’ll skip it now
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 56
www.helsinki.fi/yliopisto
Phase identification
2.12.2015
Interesting newcomer in this field is Full Profile Search Match
(FPSM) by Luca Lutterotti
• http://cod.iutcaen.unicaen.fr
• ” The "FPSM method" uses a Rietveld like fitting procedure to test all
possible crystal structures from a Database, rank them and find the more
probable in your diffraction pattern. In the end a Rietveld phase
quantification is done with the phases identified. Be aware that if a phase is
not present in the database (COD is used here), it cannot be found nor
quantify”
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 57 www.helsinki.fi/yliopisto
Phase identification
2.12.2015
Example test data below
• You just give the data and elemental
composition, software does quantitative
Rietveld refinement automatically
TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 58
www.helsinki.fi/yliopisto
End of quantitative part
Questions, comments?
2.12.2015TA+PXRD course - Part 4, Phase analysisNovember 2017, Mikko Heikkilä 59