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Statistical variances of diffusional properties from ab initio molecular dynamics simulations

dc.contributor.authorHe, Xingfeng
dc.contributor.authorZhu, Yizhou
dc.contributor.authorEpstein, Alexander
dc.contributor.authorMo, Yifei
dc.identifier.citationnpj Computational Materials (2018) 4:18 ; doi:10.1038/s41524-018-0074-yen_US
dc.descriptionPartial funding for Open Access provided by the UMD Libraries' Open Access Publishing Fund.en_US
dc.description.abstractAb initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.en_US
dc.publisherNature Publishing Groupen_US
dc.titleStatistical variances of diffusional properties from ab initio molecular dynamics simulationsen_US
dc.relation.isAvailableAtA. James Clark School of Engineeringen_us
dc.relation.isAvailableAtMaterials Science & Engineeringen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us

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