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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Published on: September 17, 2021

An adaptive finite-element method for large-scale ab initio molecular dynamics simulations.

Eiji Tsuchida¹, Yoong-Kee Choe¹, Takahiro Ohkubo²

¹Nanomaterials Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan. eiji.tsuchida@aist.go.jp.

Physical Chemistry Chemical Physics : PCCP

|April 21, 2015

Summary

This study details the finite-element method for large-scale atomistic simulations using density-functional theory. It introduces advancements for efficient ground-state calculations and addresses the eggbox effect in polymer electrolyte membrane simulations.

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Area of Science:

Computational Physics
Materials Science

Background:

Density-functional theory (DFT) is crucial for atomistic simulations.
Large-scale simulations require efficient computational methods.
Polymer electrolyte membranes (PEMs) are vital for fuel cells.

Purpose of the Study:

To present the current status of the finite-element method (FEM) for large-scale DFT simulations.
To describe recent developments in FEM for enhanced accuracy and efficiency.
To apply the FEM formulation to ab initio molecular dynamics simulations of PEMs.

Main Methods:

Overview of the FEM formulation for DFT.
Optimal selection of adaptive coordinates.
Efficient implementation of ground-state calculations.
Remedy for the eggbox effect in simulations.

Main Results:

Demonstration of an efficient FEM approach for large-scale DFT.
Successful application to ab initio molecular dynamics simulations.
Analysis of sulfonated poly(4-phenoxybenzoyl-1,4-phenylene) (SPPBP) behavior.

Conclusions:

The presented FEM formulation offers an efficient and accurate approach for large-scale atomistic simulations.
The method is suitable for studying complex materials like polymer electrolyte membranes.
Advancements improve the reliability and applicability of DFT-based simulations for materials science.