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Crystallographic computing systems

Petricek V, Dusek M (2000) The crystallographic computing system JANA2000. Institute of Physics, Praha, Czech Republic... [Pg.108]

V. Petricek and M. Dusek, A Crystallographic Computing System Institute of Physics , Academy of Sciences of the Czech Republic, Praha, 2000. [Pg.737]

Jana Jana2000. The crystallographic computing system. V. Petricek, M. Dusek, and L Palatinus, (2000) Institute of Physics, Praha, Czech Republic and Refinement of modulated structures against X ray powder diffraction data with JANA2000, M. Dusek, V. Petricek, M. Wunschel, R. E. Dinnebier and S. van Smaalen, J. Appl. Crystallogr., 2001, 34, 398 404... [Pg.529]

The Universal Crystallographic Computing System (1979). Library of Programs, Osaka University, Computing Center. [Pg.604]

Acknowledgment. We thank our TAMU colleagues Professors D.H.R. Barton, A. E. Martell and D.T. Sawyer for their comments and interest in this work. Financial support from the National Science Foundation (CHE 91-09579 to M.Y.D. CHE 88-21780 to D.H.R., and CHE-8513273 for the X-ray diffractometer and crystallographic computing system), and the National Institutes of Health (RO1GM44865-01 to M.Y.D.) is gratefully acknowledged. [Pg.222]

Cambridge Structural Database System - Crystallographic database with associated retrieval, analysis and display software, hardware supported DEC VAX and limited generic computer support, available from Cambridge Crystallographic Data Centre, University Chemical Laboratory, Lensfield Road, Cambridge CB2 lEW, U.K. [Pg.40]

UNICS(1979). The Universal Crystallographic Computing System-Osaka,... [Pg.714]

The comparison with experiment can be made at several levels. The first, and most common, is in the comparison of derived quantities that are not directly measurable, for example, a set of average crystal coordinates or a diffusion constant. A comparison at this level is convenient in that the quantities involved describe directly the structure and dynamics of the system. However, the obtainment of these quantities, from experiment and/or simulation, may require approximation and model-dependent data analysis. For example, to obtain experimentally a set of average crystallographic coordinates, a physical model to interpret an electron density map must be imposed. To avoid these problems the comparison can be made at the level of the measured quantities themselves, such as diffraction intensities or dynamic structure factors. A comparison at this level still involves some approximation. For example, background corrections have to made in the experimental data reduction. However, fewer approximations are necessary for the structure and dynamics of the sample itself, and comparison with experiment is normally more direct. This approach requires a little more work on the part of the computer simulation team, because methods for calculating experimental intensities from simulation configurations must be developed. The comparisons made here are of experimentally measurable quantities. [Pg.238]

A regularly formed crystal of reasonable size (typically >500 pm in each dimension) is required for X-ray diffraction. Samples of pure protein are screened against a matrix of buffers, additives, or precipitants for conditions under which they form crystals. This can require many thousands of trials and has benefited from increased automation over the past five years. Most large crystallographic laboratories now have robotics systems, and the most sophisticated also automate the visualization of the crystallization experiments, to monitor the appearance of crystalline material. Such developments [e.g., Ref. 1] are adding computer visualization and pattern recognition to the informatics requirements. [Pg.281]

I Site-occupatioH parameters. A complete description of a system requires detailed knowledge about the occupancy of all available sites by all die participating species. However, with K constituents and N sites, this leads to different configurations, which is computationally unrealistic. A usefid approximation is to use average site-occupation parameters, for equivalent crystallographic sites. [Pg.211]


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