Powder XRD Phase Identification

For the identification and characterization of materials using XRD data the most common method is based on pattern matching. For this method to work a large amount of reference data must be available to realize the pattern search and match algorithms. Obtained XRD powder patterns can have multiple compounds and phases present, all of which will generate peaks, and distinguishing the peaks manually is a laborious process. Computational resources and databases allow the reliable searching and matching of the varied phases and compounds patterns to the sample pattern. The formation of these patterns varies significantly enough between similarly structured materials making each unique.[1][2] Typically pattern matching will require matching at least 3 peaks to a known pattern.[2]

In principle, for a well-behaved sample the pattern search and match will be straightforward. Modern proprietary software has several automated functions for specific instrumentation and batch processing capabilities, i.e.: PANalyticals HighScore,[3] which is one of the software packages used in Aalto University. In practice, supporting data is necessary for high confidence in the analysis. Such supporting data are the lattice parameters and elemental composition. These are, at a basic level, initial criteria to run the search functions and limit the search-space, unless 100s of hits are desired. The most common refinement method used for profile matching is the Rietveld method, it is effective in matching the found peaks, with varying widths and overlaps, to a modeled profile, a key advantage over the least-squares regression methods,[4][5] this method is implemented in almost all diffraction pattern softwares.[3][6][7] After refinement, peaks are discretely defined and fed to the search and match software with the supporting data, returning possible matches for phases.

Figure 1. Illustrative figure for the most simple phase identification procedure possible. Top: An unidentified XRD pattern, only raw data, obtained from a white powder. Bottom: Steps taken to analyze the pattern including baseline correction (dark green smooth line), peak search (blue contours and vertical lines) and phase match (green and yellow vertical lines). The substance identified were Ca(OH)2 and CaO according to pattern matching. Figure: Patrik Eskelinen

Powder Pattern Databases

There are a range of databases available with crystallographic and diffraction data available. The majority of these databases are commercial or non-public, and such datasets have been kept since the early 20th century, i.e.: the Powder Diffraction File (PDF) since 1941.[8] Table 1 below is compiled to provide an overview of the best-known databases for diffraction data, most of these are also included in International Union of Crystallography (IUCr) webpage,[9] which is partially outdated. Observe that as of 2018 the ONLY well maintained open-access database available is COD, which can be implemented freely with both open-source and proprietary pattern matching software (i.e.: the free software FullProf,[6] combined with QualX2,[10] or Full Profile Search Match[7]).

Table 1. Compilation of best-known databases for crystal structures and embedded powder diffraction patterns





Single-user license cost



Relevant hyperlink






$8860 / yr

> 398 000

Highly maintained dataset and supports search and match functions, available in different tailored distributions






$8860 / 5 yr

> 298 000

Well maintained cost effective dataset, requires 3rd party software bundled with search and match software (HighScore Plus in Aalto Chem relies on this dataset as of 2018)




The community

Open access


> 394 000

New structures are constantly added, good open-access resource, well maintained, implemented in free pattern matching software



Pauling File

MPDS, JST, Tokyo Uni

3rd party apps


> 319 000

Data accessible in various 3rd party solutions, such is provided by NIMS (entry #8)




FIZ Karlsruhe


2420€ / yr

> 193 000

Only completely identified structures are provided, regularly maintained







> 900 000

CSD dataset covers organic and organometallic structures, regularly maintained





Open access


> 1 062 000

Last update Nov 2009, ONLY predicted structures, boasts the largest number of entries in any crystallography database, basis to calculate diffraction patterns (as in P2D2)





Registration required



Implements Pauling File data; part of MatNavi collection of databases; very good source


9Materials ProjectLBNLRegistration required0> 703 000Recent database based on computational results, very large and well maintained, CAVEAT: the parameters from computational studies often do not match exactly with experimental results, use appropriate experimentally verified data as a point of comparison.


Abbreviations; ICDD – International Center for Diffraction Data, NIST – National Institute of Standards & Technology, ICDS – Inorganic Crystal Structure Database, COD – Crystallography Open Database, MPDS – Materials Phases Data System, JST – Japan Science Technology Corp, NIMS – National Institute for Materials Science , P2D2 – Predicted Powder Diffraction Database, CSD – Cambridge Structural Database, LBNL – Lawrence Berkeley National Laboratory


1. 1

J. R. Davis, “X-Ray Diffraction for Bulk Structural Analysis,” in Metals Handbook, Desk Edition, 2nd Editio., 1998.

2. 1 2

“DoITPoMS - TLP Library X-ray Diffraction Techniques - Phase identification.” [Online]. Available: https://www.doitpoms.ac.uk/tlplib/xray-diffraction/phase_identification.php. [Accessed: 30-Mar-2018].

3. 1 2

“PANalytical - HighScore Features.” [Online]. Available: http://www.panalytical.com/Xray-diffraction-software/HighScore/Features.htm. [Accessed: 10-Apr-2018].

4. 1

H. M. Rietveld, “Line profiles of neutron powder-diffraction peaks for structure refinement,” Acta Crystallogr., vol. 22, no. 1, pp. 151–152, 1967.

5. 1

D. Simeone, G. Baldinozzi, D. Gosset, S. Le Caer, and J. F. Bérar, “Grazing incidence X-ray diffraction for the study of polycrystalline layers,” Thin Solid Films, vol. 530, pp. 9–13, 2013.

6. 1 2

“FullProf Suite Homepage.” [Online]. Available: https://www.ill.eu/sites/fullprof/index.html. [Accessed: 07-Apr-2018].

7. 1 2

“Full Profile Search Match of Diffraction Patterns using the Crystallography Open Database of Structures.” [Online]. Available: http://cod.iutcaen.unicaen.fr/. [Accessed: 10-Apr-2018].

8. 1

“ICDD Profile - History.” [Online]. Available: http://www.icdd.com/profile/history.htm. [Accessed: 07-Apr-2018].

9. 1

“(IUCr) Data activities in crystallography.” [Online]. Available: https://www.iucr.org/resources/data. [Accessed: 30-Mar-2018].

10. 1

“Introduction – Qualx2.” [Online]. Available: http://www.ba.ic.cnr.it/softwareic/qualx/introduction/. [Accessed: 10-Apr-2018].

11. 1 2

International Centre for Diffraction Data, “Which Icdd Database Is Right for You?” 2017.

12. 1 2

International Centre for Diffraction Data, “ICDD Pricing.” pp. 1–7, 2011.

13. 1

S. Gražulis, A. Daškevič, A. Merkys, D. Chateigner, L. Lutterotti, M. Quirós, N. R. Serebryanaya, P. Moeck, R. T. Downs, and A. Le Bail, “Crystallography Open Database (COD): an open-access collection of crystal structures and platform for world-wide collaboration,” Nucleic Acids Res., vol. 40, no. D1, pp. D420–D427, 2012.

14. 1

“Crystallography Open Database.” [Online]. Available: http://www.crystallography.net/cod/index.php. [Accessed: 30-Mar-2018].

15. 1

“Pauling File project.” [Online]. Available: http://paulingfile.com/index.php?p=scope#thePAULING FILE project. [Accessed: 07-Apr-2018].

16. 1

“ICSD: Price List.” [Online]. Available: http://www2.fiz-karlsruhe.de/icsd_price_list.html. [Accessed: 07-Apr-2018].

17. 1

“Introduction to ICSD Web.” [Online]. Available: https://icsd.fiz-karlsruhe.de/search/index.xhtml. [Accessed: 07-Apr-2018].

18. 1

“The Cambridge Structural Database (CSD) - The Cambridge Crystallographic Data Centre (CCDC).” [Online]. Available: https://www.ccdc.cam.ac.uk/solutions/csd-system/components/csd/. [Accessed: 02-Apr-2018].

19. 1

“CrystalWorks.” [Online]. Available: http://cds.rsc.org/crystalworks.asp. [Accessed: 08-Apr-2018].

20. 1

A. Le Bail, “Inorganic structure prediction with GRINSP,” J. Appl. Crystallogr., vol. 38, no. 2, pp. 389–395, 2005.

21. 1

“Inorganic Material Database (AtomWork).” [Online]. Available: http://crystdb.nims.go.jp/index_en.html. [Accessed: 07-Apr-2018].

22. 1

“Materials Project :: About.” [Online]. Available: https://materialsproject.org/about. [Accessed: 17-Apr-2018].

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