Evolutionary optimization of a charge transfer ionic potential model for Ta/Ta-oxide hetero-interfaces

TL;DR

This paper develops a new charge transfer ionic potential model for Ta/Ta-oxide interfaces, enabling atomistic simulations of oxidation processes and interface properties with high accuracy, validated against experiments and DFT data.

Contribution

The paper introduces a novel CTIP model for Ta/Ta-oxide systems, optimized via genetic algorithms, to accurately simulate interface and oxidation phenomena at the atomic level.

Findings

The CTIP model accurately predicts structural and thermodynamic properties of Ta and Ta2O5.

The model reproduces elastic and surface properties consistent with experiments.

Simulations reveal insights into early oxidation stages of tantalum.

Abstract

Tantalum, tantalum oxide and their hetero-interfaces are of tremendous technological interest in several applications spanning electronics, thermal management, catalysis and biochemistry. For example, local oxygen stoichiometry variation in TaOx memristors comprising of metallic (Ta) and insulating oxide (Ta2O5) have been shown to result in fast switching on the sub-nanosecond timescale over a billion cycles, relevant to neuromorphic computation. Despite its broad importance, an atomistic scale understanding of oxygen stoichiometry variation across Ta/TaOx hetero-interfaces, such as during early stages of oxidation and oxide growth, is not well understood. This is mainly due to the lack of a variable charge interatomic potential model for tantalum oxides that can accurately describe the ionic interactions in the metallic (Ta) and oxide (TaOx) environment as well as at their interfaces. To address this challenge, we introduce a charge transfer ionic potential (CTIP) model for Ta/Ta-oxide system by training against lattice parameters, cohesive energies, equations of state, and elastic properties of various experimentally observed Ta2O5 polymorphs. The best set of CTIP parameters are determined by employing a single-objective global optimization scheme driven by genetic algorithms followed by local Simplex optimization. Our newly developed CTIP potential accurately predicts structure, thermodynamics, energetic ordering of polymorphs, as well as elastic and surface properties of both Ta and Ta2O5, in excellent agreement with DFT calculations and experiments. We employ our newly parameterized CTIP potential to investigate the early stages of oxidation of Ta at different temperatures and atomic/molecular nature of the oxidizing species.