Density-gradient-corrected embedded atom method

TL;DR

This paper introduces a gradient-corrected embedded atom method (EAM) that improves transferability and accuracy by addressing the limitations of the uniform density approximation in regions with large electron density gradients.

Contribution

The paper develops a new gradient-corrected EAM model based on density functional theory, enhancing the method's ability to handle large electron density gradients.

Findings

Gradient corrections significantly improve EAM transferability.

The new model captures physics missing in traditional UDA.

Application to Voter-Chen EAM shows enhanced performance.

Abstract

Through detailed comparisons between Embedded Atom Method (EAM) and first-principles calculations for Al, we find that EAM tends to fail when there are large electron density gradients present. We attribute the observed failures to the violation of the uniform density approximation (UDA) underlying EAM. To remedy the insufficiency of UDA, we propose a gradient-corrected EAM model which introduces gradient corrections to the embedding function in terms of exchange-correlation and kinetic energies. Based on the perturbation theory of "quasiatoms" and density functional theory, the new embedding function captures the essential physics missing in UDA, and paves the way for developing more transferable EAM potentials. With Voter-Chen EAM potential as an example, we show that the gradient corrections can significantly improve the transferability of the potential.