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Indium tin oxide (Sn-doped In$_2$O$_{3-\delta}$ or ITO) is an interesting and technologically important transparent conducting oxide. This class of material has been extensively studied for decades, with research efforts focusing on the…
Chemical segregation and structural transitions at interfaces are important nanoscale phenomena, making them natural targets for atomistic modeling, yet interatomic potentials must be fit to secondary physical properties. To isolate the…
Thin film synthesis methods developed over the past decades have unlocked emergent interface properties ranging from conductivity to ferroelectricity. However, our attempts to exercise precise control over interfaces are constrained by a…
We introduce an open-source, fully atomistic second-principles interatomic potential for lead titanate (PbTiO3), a benchmark ferroelectric material known for its strong polarization and hightemperature phase transitions. While density…
An analysis of the network defined by the potential energy minima of multi-atomic systems and their connectivity via reaction pathways that go through transition states allows to understand important characteristics like thermodynamic,…
We demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with…
Oxide interfaces feature unique two-dimensional (2D) electronic systems with diverse electronic properties such as tunable spin-orbit interaction and superconductivity. Conductivity emerges in these interfaces when the thickness of an…
Compared to the widely investigated crystalline polymorphs of gallium oxide (Ga2O3), knowledge about its amorphous state is still limited. With the help of a machine-learning interatomic potential, we conducted large-scale atomistic…
Solving combinatorial optimization problems (COPs) is a promising application of quantum computation, with the Quantum Approximate Optimization Algorithm (QAOA) being one of the most studied quantum algorithms for solving them. However,…
Compound-tunable embedding potential (CTEP) method is proposed. A fragment of some chemical compound, "main cluster" in the present paper, is limited by boundary anions such that the nearest environmental atoms are cations. The CTEP method…
Precise control of lattice mismatch accommodation and cation interdiffusion across the interface is critical to modulate correlated functionalities in epitaxial heterostructures, particularly when the interface composition is positioned…
Tactile perception is indispensable for robots to implement various manipulations dexterously, especially in contact-rich scenarios. However, alongside the development of deep learning techniques, it meanwhile suffers from training data…
We provide a methodology for generating interatomic potentials for use in classical molecular dynamics simulations of atomistic phenomena occurring at energy scales ranging from lattice vibrations to crystal defects to high energy…
Epitaxial strain offers an effective route to tune the physical parameters in transition metal oxides. So far, most studies have focused on the effects of strain on the bandwidths and crystal field splitting, but recent experimental and…
A novel defect control approach based on laminated HfO$_2$/ZrO$_2$ with multifunctional TiN/Mo/TiOxNy electrode is proposed to significantly improve the endurance and data retention in HZO-based ferroelectric capacitor. The O-rich interface…
Using isothermal and temperature-dependent electrical measurements, we investigated the resistive switching mechanism of amorphous titanium oxide thin films deposited by a plasma-enhanced atomic layer deposition method between two aluminum…
Reducible oxides are widely used catalyst supports that can increase oxidation reaction rates by transferring their lattice oxygen at the metal-support interface. The interfacial oxidation process is typically described in terms of a…
Universal machine-learned interatomic potentials (uMLIPs) offer a promising approach to performing atomistic simulations at near-DFT accuracy with greatly reduced computational cost. Here, we present a new high-temperature benchmarking…
An efficient method of interpretation of the crystal field effect in non-metallic f-electron systems, the {\it enhanced angular overlap model} (EAOM), is presented. The method is established on the ground of perturbation expansion of the…
Accurate and effective discrete image tokenization is crucial for long image sequence processing. However, current methods rigidly compress all content at a fixed rate, ignoring the variable information density of images and leading to…