An \emph{ab initio} method for locating characteristic potential energy minima of liquids

TL;DR

This paper introduces an efficient ab initio method using density functional theory to locate potential energy minima in liquids, enabling better understanding of atomic interactions through stochastic configuration quenches.

Contribution

The paper presents a novel technique for identifying potential energy minima in liquids using DFT and stochastic configurations, reducing computational effort and improving analysis.

Findings

Quenches from stochastic configurations match those from MD configurations.

DFT quenches provide parameters to calibrate the Hamiltonian.

Method applicable to metallic Na with pair potential interactions.

Abstract

It is possible in principle to probe the many--atom potential surface using density functional theory (DFT). This will allow us to apply DFT to the Hamiltonian formulation of atomic motion in monatomic liquids [\textit{Phys. Rev. E} {\bf 56}, 4179 (1997)]. For a monatomic system, analysis of the potential surface is facilitated by the random and symmetric classification of potential energy valleys. Since the random valleys are numerically dominant and uniform in their macroscopic potential properties, only a few quenches are necessary to establish these properties. Here we describe an efficient technique for doing this. Quenches are done from easily generated "stochastic" configurations, in which the nuclei are distributed uniformly within a constraint limiting the closeness of approach. For metallic Na with atomic pair potential interactions, it is shown that quenches from stochastic configurations and quenches from equilibrium liquid Molecular Dynamics (MD) configurations produce statistically identical distributions of the structural potential energy. Again for metallic Na, it is shown that DFT quenches from stochastic configurations provide the parameters which calibrate the Hamiltonian. A statistical mechanical analysis shows how the underlying potential properties can be extracted from the distributions found in quenches from stochastic configurations.