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Cited by 6,834

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VESTA: a three-dimensional visualization system for electronic and structural analysis

Momma, Koichi, Izumi, Fujio·2008·Journal of Applied Crystallography

Abstract

A cross-platform program,VESTA, has been developed to visualize both structural and volumetric data in multiple windows with tabs.VESTA represents crystal structures by ball-and-stick, space-filling, polyhedral, wireframe, stick, dot-surface and thermal-ellipsoid models. A variety of crystal-chemical information is extractable from fractional coordinates, occupancies and oxidation states of sites. Volumetric data such as electron and nuclear densities, Patterson functions, and wavefunctions are displayed as isosurfaces, bird's-eye views and two-dimensional maps. Isosurfaces can be colored according to other physical quantities. Translucent isosurfaces and/or slices can be overlapped with a structural model. Collaboration with external programs enables the user to locate bonds and bond angles in the `graphics area', simulate powder diffraction patterns, and calculate site potentials and Madelung energies. Electron densities determined experimentally are convertible into their Laplacians and electronic energy densities.

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Metadata

Authors
Momma, K., & Izumi, F.
Venue
Journal of Applied Crystallography
Published
2008-05-14
Volume
41
Issue
3
Pages
653-658
ISSN
0021-8898 (ISSN-L)
OpenAlex
W2070059498
Cited by
6,834
References
1
FWCI
130.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: VESTA: a three-dimensional visualization system for electronic and structural analysis. https://app.cochat.ai/papers/10.1107/s0021889808012016
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Momma, K., & Izumi, F. (2008). VESTA: a three-dimensional visualization system for electronic and structural analysis. Journal of Applied Crystallography. https://doi.org/10.1107/s0021889808012016

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.