Electrochemistry

Fitting empirical interatomic potentials for electrochemistry of ionic systems

Evolutionary optimization of a charge transfer ionic potential for tantalum oxide

Scientific use case: Investigating oxide growth on a tantalum (Ta) metal surface as a function of depth, time, temperature (top to bottom increasing in temperature), and oxidation type (left - natural vs. right - atomic). Maps are colored by the O/Ta stoichiometry ratio. The gas region (identified by absence of Ta atoms) is colored maroon.

Abstract: Heterostructures of tantalum and its oxide are of tremendous technological interest for myriad technological applications, including electronics, thermal management, catalysis, and biochemistry. In particular, local oxygen stoichiometry variation in TaOx memristors comprising thermodynamically stable metallic (Ta) and insulating oxide (Ta2O5) have been shown to result in fast switching on the subnanosecond time scale over a billion cycles. This rapid switching opens up the potential for advanced functional platforms such as stateful logic operations and neuromorphic computation. Despite its broad importance, an atomistic scale understanding of oxygen stoichiometry variation across Ta/TaOx heterointerfaces, such as during early stages of oxidation and oxide growth, is not well understood. This is mainly due to the lack of a unified interatomic potential model for tantalum oxides that can accurately describe metallic (Ta) and ionic (TaOx) as well as mixed (Ta/TaOx interfaces) bonding environments simultaneously. To address this challenge, we introduce a Charge Transfer Ionic Potential (CTIP) model for Ta/Ta-oxide system by training the model against lattice parameters, cohesive energies, equations of state (EOS), elastic properties, and surface energies of the various experimentally observed Ta2O5polymorphs (hexagonal, orthorhombic, and monoclinic) obtained from density functional theory (DFT) calculations. The best CTIP parameters are determined by employing a global optimization scheme driven by genetic algorithms followed by local simplex optimization. Our newly developed CTIP potential accurately predicts structure, thermodynamics, and 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 parametrized CTIP potential to investigate the early stages of oxidation and atomic scale mechanisms associated with oxide growth on the Ta surface at various temperatures. The CTIP potential developed in this work is an invaluable tool to investigate atomic-scale mechanisms and transport phenomena underlying the response of Ta/TaOx interfaces to external stimuli (e.g, temperature, pressure, strain, electric field, etc.), as well as other interesting dynamical phenomena including the physics of switching dynamics in TaOx based memristors and neuromorphic devices.

Ref: Chem. Mater., 2017, 29 (8), pp 3603–3614.