Statistical variances of diffusional properties from ab initio molecular dynamics simulations

By Xingfeng He, Yizhou Zhu, A. R. Epstein, Yifei Mo. npj Computational Materials, 2018

412 citations recorded by the source corpus.

Ab 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.Ionic diffusion: Mapping the uncertaintyThe calculation of ionic diffusivity with ab initio molecular dynamics is often plagued by poor statistics; how accurate are the results? Due to computational limits only small systems and timescales can be modeled, limiting the number of diffusion events sampled. Here, Yifei Mo and colleagues at the University of Maryland outline best practice to obtain ionic diffusivity, as well as how to obtain statistical errors with this approach. They show linear behavior in diffusivity only happens for intermediate time intervals of the simulations. Moreover, variance of diffusivity is related to the total mean squared displacement of all ions, the statistical error reducing as the displacement increases. Accurate ionic diffusion calculations can only be performed for super-ionic conductors, or at high temperature, with implications for the reliability of calculations of diffusivity in other materials.

Subfields: Electrical and Electronic Engineering, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/637e8b634c83710bd71f30b3b97f3bc546d14627

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Qiang Bai
2. Adelaide M. Nolan
3. Xingfeng He
4. Yizhou Zhu
5. Yifei Mo
6. Gerbrand Ceder
7. W. Zeier
8. J. Janek

In Materials Chemistry

1. Qiang Bai
2. Adelaide M. Nolan
3. Xingfeng He
4. Yizhou Zhu
5. Yifei Mo

Citations in the corpus

• Computation-Accelerated Design of Materials and Interfaces for All-Solid-State Lithium-Ion Batteries (2018, methodology): “The diffusivity, ionic conductivity, and activation energy (Ea) calculated from AIMD simulations have achieved excellent agreement with the experiments for many SIC materials, including LGPS, LLZO, and LATP.(23,34,38,39,62,70) For example, a Li ionic conductivity of 10–14 mS cm 1 and an activation e”