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Supercell program: a combinatorial structure-generation approach for the local-level modeling of atomic substitutions and partial occupancies in crystals

Overview of attention for article published in Journal of Cheminformatics, March 2016
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
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285 Mendeley
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Title
Supercell program: a combinatorial structure-generation approach for the local-level modeling of atomic substitutions and partial occupancies in crystals
Published in
Journal of Cheminformatics, March 2016
DOI 10.1186/s13321-016-0129-3
Pubmed ID
Authors

Kirill Okhotnikov, Thibault Charpentier, Sylvian Cadars

Abstract

Disordered compounds are crucially important for fundamental science and industrial applications. Yet most available methods to explore solid-state material properties require ideal periodicity, which, strictly speaking, does not exist in this type of materials. The supercell approximation is a way to imply periodicity to disordered systems while preserving "disordered" properties at the local level. Although this approach is very common, most of the reported research still uses supercells that are constructed "by hand" and ad-hoc. This paper describes a software named supercell, which has been designed to facilitate the construction of structural models for the description of vacancy or substitution defects in otherwise periodically-ordered (crystalline) materials. The presented software allows to apply the supercell approximation systematically with an all-in-one implementation of algorithms for structure manipulation, supercell generation, permutations of atoms and vacancies, charge balancing, detecting symmetry-equivalent structures, Coulomb energy calculations and sampling output configurations. The mathematical and physical backgrounds of the program are presented, along with an explanation of the main algorithms and relevant technical details of their implementation. Practical applications of the program to different types of solid-state materials are given to illustrate some of its potential fields of application. Comparisons of the various algorithms implemented within supercell with similar solutions are presented where possible. The all-in-one approach to process point disordered structures, powerful command line interface, excellent performance, flexibility and GNU GPL license make the supercell program a versatile set of tools for disordered structures manipulations.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 <1%
Korea, Republic of 1 <1%
United States 1 <1%
India 1 <1%
Unknown 281 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 23%
Researcher 50 18%
Student > Master 35 12%
Student > Doctoral Student 17 6%
Student > Bachelor 15 5%
Other 35 12%
Unknown 67 24%
Readers by discipline Count As %
Materials Science 72 25%
Chemistry 55 19%
Physics and Astronomy 27 9%
Engineering 13 5%
Chemical Engineering 9 3%
Other 23 8%
Unknown 86 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 June 2017.
All research outputs
#7,531,527
of 22,981,247 outputs
Outputs from Journal of Cheminformatics
#594
of 840 outputs
Outputs of similar age
#108,487
of 301,449 outputs
Outputs of similar age from Journal of Cheminformatics
#9
of 15 outputs
Altmetric has tracked 22,981,247 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 840 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 301,449 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.