Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-12-01T01:12:23.190Z Has data issue: false hasContentIssue false
  • English
  • Français

Frontiers between crystal structure prediction and determination by powder diffractometry

Published online by Cambridge University Press:  06 March 2012

Armel Le Bail
Armel Le Bail
Affiliation:
Laboratoire des Oxydes et Fluorures, CNRS UMR 6010, Université du Maine, avenue O. Messiaen, 72085 Le Mans Cedex 9, France
Get access Rights & Permissions [Opens in a new window]

Abstract

The fuzzy frontiers between structure determination by powder diffractometry and crystal structure prediction are discussed. The application of a search-match program combined with a database of more than 60 000 predicted powder diffraction patterns is demonstrated. Immediate structure solution (before indexing) is shown to be possible by this method if the discrepancies between the predicted crystal structure cell parameters and the actual ones are <1%. Incomplete chemistry of the hypothetical models (missing interstitial cations, water molecules, etc.) is not necessarily a barrier to a successful identification (in spite of inducing large intensity errors), provided the search-match is made with chemical restrictions on the elements present in both the virtual and experimental compounds.

Keywords

crystal structure predictionpowder diffractionsearch-match
Type
Technical Articles
Information
Powder Diffraction , Volume 23 , Special Issue S1 , March 2008 , pp. S5 - S12
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allen, F.H. (2002). “The Cambridge Structural Database: A quarter of a million crystal structures and rising,” Acta Crystallogr., Sect. B: Struct. Sci.ASBSDK 58, 380–388. acl, ASBSDK CrossRefGoogle ScholarPubMed
Bergmann, J., Le Bail, A., Shirley, R., and Zlokazov, V. (2004). “Renewed interest in powder diffraction data indexing,” Z. Kristallogr.ZEKRDZ 219, 783–790. zek, ZEKRDZ CrossRefGoogle Scholar
Burla, M.C., Caliandro, R., Carrozzini, B., Cascarano, G.L., De Caro, L., Giacovazzo, C., Polidori, G., and Siliqi, D. (2006). “Use of Patterson-based methods automatically to determine the structures of heavy-atom-containing proteins with up to 6000 non-hydrogen atoms in the asymmetric unit,” J. Appl. Crystallogr.JACGAR 39, 728–734. acr, JACGAR CrossRefGoogle Scholar
Catlow, C.R. A. (1997). Computer Modelling in Inorganic Crystallography (Academic Press, London).Google Scholar
Catlow, C.R. A., Gale, J.D., and Grimes, R.W. (1993). “Recent computational studies in solid state chemistry,” J. Solid State Chem.JSSCBI 106, 13–26. jss, JSSCBI CrossRefGoogle Scholar
Černý, R. and Favre-Nicolin, V. (2007). “Direct space methods of structure determination from powder diffraction: principles, guidelines and perspectives,” Z. Kristallogr.ZEKRDZ 222, 105–113. zek, ZEKRDZ CrossRefGoogle Scholar
Dadachov, M.S. and Le Bail, A. (1997). “Structure of zeolitic K2TiSi3O9⋅H2O determined ab initio from powder diffraction data,” Eur. J. Solid State Inorg. Chem.EJSCE5 34, 381–390. ess, EJSCE5 Google Scholar
Day, G.M., Motherwell, W.D. S., Ammon, H.L., Boerrigter, S.X. M., Della Valle, R.G., Venuti, E., Dzyabchenko, A., Dunitz, J.D., Schweizer, B., van Eijck, B.P., Erk, P., Facelli, J.C., Bazterra, V.E., Ferraro, M.B., Hofmann, D.W. M., Leusen, F.J. J., Liang, C., Pantelides, C.C., Karamertzanis, P.G., Price, S.L., Lewis, T.C., Nowell, H., Torrisi, A., Scheraga, H.A., Arnautova, Y.A., Schmidt, M.U., and Verwer, P. (2005). “A third blind test of crystal structure prediction,” Acta Crystallogr., Sect. B: Struct. Sci.ASBSDK 61, 511–527. acl, ASBSDK CrossRefGoogle ScholarPubMed
Férey, G., Mellot-Draznieks, C., Serre, C., Millange, F., Dutour, J., Surblé, S., and Margiolaki, I. (2005). “A chromium terephthalate-based solid with unusually large pore volumes and surface area,” ScienceSCIEAS 309, 2040–2042. sci, SCIEAS CrossRefGoogle ScholarPubMed
Férey, G., Serre, C., Mellot-Draznieks, C., Millange, F., Surblé, S., Dutour, J., and Margiolaki, I. (2004). “A hybrid solid with giant pores prepared by a combination of targeted chemistry, simulation, and powder diffraction,” Angew. Chem., Int. Ed.ACIEF5 43, 6296–6301. aqv, ACIEF5 CrossRefGoogle ScholarPubMed
Fischer, C.C., Tibbetts, K.J., Morgan, D., and Ceder, G. (2006). “Predicting crystal structure by merging data mining with quantum mechanics,” Nat. Mater.NMAACR 5, 641–646. aj5, NMAACR CrossRefGoogle ScholarPubMed
Foster, M.D., Friedrichs, O.D., Bell, R.G., Paz, F.A. A., and Klinowski, J. (2003). “Structural evaluation of systematically enumerated hypothetical uninodal zeolites,” Angew. Chem., Int. Ed.ACIEF5 42, 3896–3899. aqv, ACIEF5 CrossRefGoogle ScholarPubMed
Foster, M.D. and Treacy, M.M. J. (2003). Hypothetical Zeolites Database 〈http://www.hypotheticalzeolites.net〉.Google Scholar
Gale, J.D. (1997). “GULP: A computer program for the symmetry-adapted simulation of solids,” J. Chem. Soc., Faraday Trans.JCFTEV 93, 629–637. jcf, JCFTEV CrossRefGoogle Scholar
Gavezzotti, A. (1994). “Are crystal structures predictable?,” Acc. Chem. Res.ACHRE4 27, 309–314. ach, ACHRE4 CrossRefGoogle Scholar
Hemon, A. and Courbion, G. (1990). “The NaF-CaF2-AlF3 system: Structures of β-NaCaAlF6 and Na4Ca4Al7F33,” J. Solid State Chem.JSSCBI 84, 153–164. jss, JSSCBI CrossRefGoogle Scholar
Hofmann, D.W. M. and Kuleshova, L. (2005). “New similarity index for crystal structure determination from X-ray powder diagrams,” J. Appl. Crystallogr.JACGAR 38, 861–866. acr, JACGAR CrossRefGoogle Scholar
Le Bail, A. (2003). PCOD: Predicted Crystallography Open Database 〈http://www.crystallography.net/pcod〉.Google Scholar
Le Bail, A. (2005). “Inorganic structure prediction with GRINSP,” J. Appl. Crystallogr.JACGAR 38, 389–395. acr, JACGAR CrossRefGoogle Scholar
Le Bail, A. (2007a). “Predicted corner-sharing titanium silicates,” Z. Kristallogr. ZEKRDZSuppl. 26, 202–208. zek, ZEKRDZ Google Scholar
Le Bail, A. (2007b). “Inorganic structure prediction: Too much and not enough,” Solid State Phenom.DDBPE8 130, 1–6. ssq, DDBPE8 CrossRefGoogle Scholar
Le Bail, A. and Calvayrac, F. (2006). “Hypothetical AlF3 crystal structures,” J. Solid State Chem.JSSCBI 179, 3159–3166. jss, JSSCBI CrossRefGoogle Scholar
Le Bail, A., Fourquet, J.L., and Bentrup, U. (1992). “τ-AlF3: Crystal structure determination from X-ray powder diffraction data. A new MX3 corner-sharing octahedra 3D network,” J. Solid State Chem.JSSCBI 100, 151–159. jss, JSSCBI CrossRefGoogle Scholar
Le Meins, J.-M., Cranswick, L.M. D., and Le Bail, A. (2003). “Results and conclusions of the internet based search/match round robin 2002,” Powder Diffr.PODIE2 18, 106–113. pdj, PODIE2 CrossRefGoogle Scholar
Lufaso, M.W. and Woodward, P.M. (2001). “Prediction of the crystal structures of perovskites using the software SPuDS,” Acta Crystallogr., Sect. B: Struct. Sci. ASBSDK 57, 725–738. acl, ASBSDK CrossRefGoogle ScholarPubMed
Meden, A. (2006). “Inorganic crystal structure prediction – a dream coming true?” Acta Chim. Slov. 53, 148–152.Google Scholar
Mellot-Draznieks, C. and Férey, G. (2005). “Assembling molecular species into 3D frameworks: Computational design and structure solution of hybrid materials,” Prog. Solid State Chem.PSSTAW 33, 187–197. psc, PSSTAW CrossRefGoogle Scholar
Mellot-Draznieks, C., Girard, S., Férey, G., Schön, J.C., Cancarevic, Z., and Jansen, M. (2002). “Computational design and prediction of interesting not-yet-synthesized structures of inorganic materials by using building unit concepts,” Chem.-Eur. J.CEUJED 8, 4102–4113. cej, CEUJED 3.0.CO;2-3>CrossRefGoogle ScholarPubMed
Mellot-Draznieks, C., Newsam, J.M., Gorman, A.M., Freeman, C.M., and Férey, G. (2000). “De novo prediction of inorganic structures developed through automated assembly of secondary building units (AASBU method),” Angew. Chem., Int. Ed.ACIEF5 39, 2270–2275. aqv, ACIEF5 3.0.CO;2-A>CrossRefGoogle Scholar
Milman, V. and Winkler, B. (1999). “Ab initio modeling in crystallography,” Int. J. Inorg. Mater.IJIMCR 1, 273–279. a83, IJIMCR CrossRefGoogle Scholar
Molecular Simulations (2000). Cerius2, Version 4.2 (Computer Software), Accelrys Software Inc., Cambridge, United Kingdom.Google Scholar
Motherwell, W.D. S., Ammon, H.L., Dunitz, J.D., Dzyabchenko, A., Erk, P., Gavezzotti, A., Hofmann, D.W. M., Leusen, F.J. J., Lommerse, J.P. M., Mooij, W.T. M., Price, S.L., Scheraga, H., Schweizer, B., Schmidt, M.U., van Eijck, B.P., Verwer, P., and Williams, D.E. (2002). “Crystal structure prediction of small organic molecules: A second blind test,” Acta Crystallogr., Sect. B: Struct. Sci.ASBSDK 58, 647–661. acl, ASBSDK CrossRefGoogle ScholarPubMed
Panina, N., Leusen, F.J. J., Janssen, F.F. B. J., Verwer, P., Meekes, H., Vlieg, E., and Deroover, G. (2007). “Crystal structure prediction of organic pigments: Quinacridone as an example,” J. Appl. Crystallogr.JACGAR 40, 105–114. acr, JACGAR CrossRefGoogle ScholarPubMed
Pauling, L. (1929). “The principles determining the structure of complex ionic crystals,” J. Am. Chem. Soc.JACSAT 51, 1010–1026. acs, JACSAT CrossRefGoogle Scholar
Payne, M.C., Teter, M.P., Allan, D.C., Arias, T.A., and Joannopoulos, J.D. (1992). “Iterative minimization techniques for ab initio total-energy calculations: Molecular dynamics and conjugate gradients,” Rev. Mod. Phys.RMPHAT 64, 1045–1097. rmp, RMPHAT CrossRefGoogle Scholar
Rietveld, H.M. (1969). “A profile refinement method for nuclear and magnetic structures,” J. Appl. Crystallogr.JACGAR 2, 65–71. acr, JACGAR CrossRefGoogle Scholar
Schmidt, M.U., Ermrich, M., and Dinnebier, R.E. (2005). “Determination of the structure of the violet pigment C22H12Cl2N6O4 from a non-indexed X-ray powder diagram,” Acta Crystallogr., Sect. B: Struct. Sci.ASBSDK 61, 37–45. acl, ASBSDK CrossRefGoogle ScholarPubMed
Schmidt, M.U., Hofmann, D.W. M., Buchsbaum, C., and Metz, H.J. (2006). “Crystal structure of pigment Red 170 and derivatives, as determined by X-ray powder diffraction,” Angew. Chem., Int. Ed.ACIEF5 45, 1313–1317. aqv, ACIEF5 CrossRefGoogle ScholarPubMed
Schön, J.C. and Jansen, M. (2001a). “Determination, prediction, and understanding of structures, using the energy landscapes of chemical systems – Part I,” Z. Kristallogr.ZEKRDZ 216, 307–325. zek, ZEKRDZ CrossRefGoogle Scholar
Schön, J.C. and Jansen, M. (2001b). “Determination, prediction, and understanding of structures, using the energy landscapes of chemical systems – Part II,” Z. Kristallogr.ZEKRDZ 216, 361–383. zek, ZEKRDZ CrossRefGoogle Scholar
Treacy, M.M. J., Rivin, I., Balkovsky, E., Randall, K.H., and Foster, M.D. (2004). “Enumeration of periodic tetrahedral frameworks. II. Polynodal graphs,” Microporous Mesoporous Mater.MIMMFJ 74, 121–132. a9k, MIMMFJ CrossRefGoogle Scholar
Wevers, M.A. C., Schön, J.C., and Jansen, M. (1998). “Determination of structure candidates of simple crystalline AB2 systems,” J. Solid State Chem.JSSCBI 136, 233–246. jss, JSSCBI CrossRefGoogle Scholar
Winkler, B., Knorr, K., and Milman, V. (2003). “Prediction of the structure of LaF3 at high pressures,” J. Alloys Compd. JALCEU 349, 111–113. jal, JALCEU 0925-8388CrossRefGoogle Scholar
Woodley, S.M. (2004). “Prediction of crystal structures using evolutionary algorithms and related techniques,” in Application of Evolutionary Computation in Chemistry, edited by Mingos, D. M. P. and Johnston, R. L. (Springer-Verlag, Berlin), Vol. 110, pp. 95–132.Google Scholar
Yaghi, O.M., O’Keeffe, M., Ockwig, N.W., Chae, H.K., Eddaoudi, M., and Kim, J. (2003). “Reticular synthesis and the design of new materials,” Nature (London)NATUAS 423, 705–714. nat, NATUAS CrossRefGoogle ScholarPubMed