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An open science grid implementation of the steady state genetic algorithm for crystal structure prediction

Publication ,  Journal Article
Varela, KN; Pagola, GI; Lund, AM; Ferraro, MB; Orendt, AM; Facelli, JC
Published in: Journal of Computational Science
October 1, 2024

In this paper we report the implementation and testing of algorithmic changes that have been implemented in MGAC, a crystal structure prediction system, to make it scalable and amenable to take advantage of such significant distributed resources as the Open Science Grid (OSG). The changes include the adoption of a steady state Genetic Algorithm (GA) and the adoption of a more general definition of the GA genome that eliminates the need of searching individually for each of the 230 possible space groups and the use of the Density Functional Theory with dispersion correction (DFT-D) as implemented in Quantum Espresso (QE) to calculate crystal energies. The performance of this implementation of MGAC, which in the following we label as MGAC-QE-OSG, is demonstrated for two test cases methanol and ethanol. In both cases the MGAC-QE-OSG can find the experimental structures of these compounds.

Duke Scholars

Published In

Journal of Computational Science

DOI

ISSN

1877-7503

Publication Date

October 1, 2024

Volume

82

Related Subject Headings

  • 4901 Applied mathematics
  • 4606 Distributed computing and systems software
  • 4602 Artificial intelligence
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics
 

Citation

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Varela, K. N., Pagola, G. I., Lund, A. M., Ferraro, M. B., Orendt, A. M., & Facelli, J. C. (2024). An open science grid implementation of the steady state genetic algorithm for crystal structure prediction. Journal of Computational Science, 82. https://doi.org/10.1016/j.jocs.2024.102415
Varela, K. N., G. I. Pagola, A. M. Lund, M. B. Ferraro, A. M. Orendt, and J. C. Facelli. “An open science grid implementation of the steady state genetic algorithm for crystal structure prediction.” Journal of Computational Science 82 (October 1, 2024). https://doi.org/10.1016/j.jocs.2024.102415.
Varela KN, Pagola GI, Lund AM, Ferraro MB, Orendt AM, Facelli JC. An open science grid implementation of the steady state genetic algorithm for crystal structure prediction. Journal of Computational Science. 2024 Oct 1;82.
Varela, K. N., et al. “An open science grid implementation of the steady state genetic algorithm for crystal structure prediction.” Journal of Computational Science, vol. 82, Oct. 2024. Scopus, doi:10.1016/j.jocs.2024.102415.
Varela KN, Pagola GI, Lund AM, Ferraro MB, Orendt AM, Facelli JC. An open science grid implementation of the steady state genetic algorithm for crystal structure prediction. Journal of Computational Science. 2024 Oct 1;82.
Journal cover image

Published In

Journal of Computational Science

DOI

ISSN

1877-7503

Publication Date

October 1, 2024

Volume

82

Related Subject Headings

  • 4901 Applied mathematics
  • 4606 Distributed computing and systems software
  • 4602 Artificial intelligence
  • 0806 Information Systems
  • 0802 Computation Theory and Mathematics