Kiran Sasikumar

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.

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 TaO_x 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/TaO_x 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 (TaO_x) as well as mixed (Ta/TaO_x 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 Ta₂O₅ polymorphs (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/TaO_x 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 TaO_x based memristors and neuromorphic devices.