International
Tables for Crystallography Volume H Powder diffraction Edited by C. J. Gilmore, J. A. Kaduk and H. Schenk © International Union of Crystallography 2018 |
International Tables for Crystallography (2018). Vol. H, ch. 3.4, p. 276
Section 3.4.4.1. Traditional indexing programs^{a}Institute of Crystallography – CNR, Via Amendola 122/o, Bari, I-70126, Italy |
This program is based on the zone-indexing strategy and uses the Runge–Ito–de Wolff–Visser method of decomposition of the reciprocal space into zones, as described in Section 3.4.3.1.1.
The following steps are executed by the program:
ITO is very efficient at indexing patterns with low symmetry and is only weakly sensitive to impurity peaks, if they occur at high angles. The most frequent causes of failure are inaccuracy or incompleteness of the input data.
Classified by Shirley (1980, 2003) as semi-exhaustive, TREOR90 is based on the index-heuristics strategy (see Section 3.4.3.1.3) and uses a trial-and-error approach. It performs the following steps:
The success of the program is related to the use of some suitable standard sets of parameter values (maximum unit-cell volume, maximum cell axis, tolerance of values etc.) arising from the accumulated experience of the authors; they can be easily changed by the user via suitable keywords in the input file.
This program works in direct space (down to the monoclinic system) by using the successive-dichotomy search method (see Section 3.4.3.1.5), which was introduced for the automatic indexing of powder diffraction patterns by Louër & Louër (1972). DICVOL91 has been defined as exhaustive by Shirley (1980, 2003). Its main steps are:
The program is fast at performing exhaustive searches in parameter space (except for the triclinic case); on the other hand, its efficiency is strongly related to the quality of the data and to the presence of impurities (in fact, impurities are not permitted).
References
Boultif, A. & Louër, D. (1991). Indexing of powder diffraction patterns for low-symmetry lattices by the successive dichotomy method. J. Appl. Cryst. 24, 987–993.Google ScholarLouër, D. & Louër, M. (1972). Méthode d'essais et erreurs pour l'indexation automatique des diagrammes de poudre. J. Appl. Cryst. 5, 271–275.Google Scholar
Pecharsky, V. K. & Zavalij, P. Y. (2009). Determination and refinement of the unit cell. In Fundamentals of Powder Diffraction and Structural Characterization of Materials, 2nd ed., pp. 407–495. New York: Springer.Google Scholar
Shirley, R. (1980). Data accuracy for powder indexing. In Accuracy in Powder Diffraction, edited by S. Block & C. R. Hubbard, NBS Spec. Publ. 567, 361–382.Google Scholar
Shirley, R. (2003). Overview of powder-indexing program algorithms (history and strengths and weaknesses). IUCr Comput. Comm. Newsl. 2, 48–54. http://www.iucr.org/resources/commissions/crystallographic-computing/newsletters/2 .Google Scholar
Smith, G. S. (1977). Estimating the unit-cell volume from one line in a powder diffraction pattern: the triclinic case. J. Appl. Cryst. 10, 252–255.Google Scholar
Visser, J. W. (1969). A fully automatic program for finding the unit cell from powder data. J. Appl. Cryst. 2, 89–95.Google Scholar
Werner, P.-E., Eriksson, L. & Westdahl, M. (1985). TREOR, a semi-exhaustive trial-and-error powder indexing program for all symmetries. J. Appl. Cryst. 18, 367–370.Google Scholar