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A genetic algorithm for first principles global structure optimization of supported nano structures
Abstract
We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA’s with a description of optimal parameters to use. New results for the adsorption of M8 clusters (M = Ru, Rh, Pd, Ag, Pt, Au) on the stoichiometric rutile TiO2(110) surface are presented showing the power of automated structure prediction and highlighting the diversity of metal cluster geometries at the atomic scale.
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Crystal structure prediction using ab initio evolutionary techniques: Principles and applications
Oganov, A. R., & Glass, C. W. (2006) · The Journal of Chemical Physics · doi:10.1063/1.2210932 · Cited by 2,596
Cited by
Physics-Inspired Structural Representations for Molecules and Materials
Musil, F., Grisafi, A., Bartók, A. P., Ortner, C., Csányi, G., & Ceriotti, M. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00021 · Cited by 523
Wan, C., Zhang, Z., Dong, J., Xu, M., Pu, H., Baumann, D., Lin, Z., Wang, S., Huang, J., Shah, A. H., et al. (2023) · Nature Materials · doi:10.1038/s41563-023-01584-3 · Cited by 404
Machine learning for renewable energy materials
Gu, G. H., Noh, J., Kim, I., & Jung, Y. (2019) · Journal of Materials Chemistry A · doi:10.1039/c9ta02356a · Cited by 311
Catalysis Applications of Size-Selected Cluster Deposition
Vajda, S., & White, M. G. (2015) · ACS Catalysis · doi:10.1021/acscatal.5b01816 · Cited by 293
Metadata
- Authors
- Vilhelmsen, L. B., & Hammer, B.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2014-07-28
- Volume
- 141
- Issue
- 4
- Pages
- 044711-044711
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W2038642329
- Cited by
- 233
- References
- 1
- FWCI
- 5.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Vilhelmsen, L. B., & Hammer, B. (2014). A genetic algorithm for first principles global structure optimization of supported nano structures. The Journal of Chemical Physics. https://doi.org/10.1063/1.4886337
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