Related papers: Modeling refractory high-entropy alloys with effic…
High-entropy alloys (HEAs) with multiple constituent elements have been extensively studied in the past 20 years due to their promising engineering application. Previous experimental and computational studies of HEAs focused mainly on…
Vanadium dioxide is one of the most studied strongly correlated materials. Nonetheless, the intertwining between electronic correlation and lattice effects has precluded a comprehensive description of the rutile metal to monoclinic…
Machine learning interatomic potentials have revolutionized complex materials design by enabling rapid exploration of material configurational spaces via crystal structure prediction with ab initio accuracy. However, critical challenges…
Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…
We describe implementation and analysis of a first-principles theory, derived in an earlier work, for the leading terms in an expansion of a Gibbs free energy of a multi-component alloy in terms of order parameters that characterize…
Magnesium (Mg) has the lowest density of all structural metals and has excellent potential for wide use in structural applications. While pure Mg has inferior mechanical properties; the addition of further elements at various concentrations…
Building a modular architecture with superconducting quantum computing chips is one of the means to achieve qubit scalability, allowing the screening, selection, replacement, and integration of individual qubit modules into large quantum…
In this study, we employ the Wien2k code to conduct ab-initio study of a novel potential all-d-metal Heusler alloy Co$_2$MnNb. The analysis utilizes the comparison of local spin density approximations (LDA) with Perdew-Burke-Ernzerh…
Neutron irradiation produces, within a few picoseconds, displacement cascades that are sequences of atomic collisions generating point and extended defects which subsequently affects the long-term evolution of materials. The diversity of…
CrCoNi medium-entropy alloys exhibit exceptional mechanical properties arising from pronounced chemical complexity, including short-range order (SRO), and low stacking fault energy, posing challenges for large-scale atomistic simulations.…
Materials that undergo reversible metal-insulator transitions are obvious candidates for new generations of devices. For such potential to be realised, the underlying microscopic mechanisms of such transitions must be fully determined. In…
We search for new superhard B-N-O compounds with an iterative machine learning (ML) procedure, where ML models are trained using sample crystal structures from evolutionary algorithm. We first use cohesive energy to evaluate the…
Multi-principal element alloys open large composition spaces for alloy development. The large compositional space necessitates rapid synthesis and characterization to identify promising materials, as well as predictive strategies for alloy…
Ab initio calculations have been performed to clarify the primary behaviors of He atoms in vanadium and to generate the database for the development of the interatomic potential for V-He system within the framework of the"s-band"model.The…
The growing need for structural materials with strength, mechanical stability, and durability in extreme environments is driving the development of high entropy alloys. These are materials with near equiatomic mixing of five or more…
The alleged existence of sluggish diffusion in high entropy alloys has drawn controversy. In high entropy alloys, and in general in all solids, transport properties are controlled by point defect concentration, which must be known before…
Alloy-based perovskite solar cells offer tunable properties and improved stability, but their complexity has impeded accurate modeling, hindering development. We present a machine-learning (ML) accelerated atomistic modeling approach for…
We report on the discovery of a high-entropy alloy with a hexagonal crystal structure. Equiatomic samples in the alloy system Ho-Dy-Y-Gd-Tb were found to solidify as homogeneous single-phase high-entropy alloys. The results of our electron…
New monoclinic ($P2$/$c$) tungstates - a medium-entropy tungstate, (Mn,Ni,Cu,Zn)WO$_4$, and a high-entropy tungstate, (Mn,Co,Ni,Cu,Zn)WO$_4$ - were synthesized and characterized. Their phase purity and solid solution nature were confirmed…
Many rotational invariants for crystal structure representations have been used to describe the structure-property relationship by machine learning. The machine learning interatomic potential (MLIP) is one of the applications of rotational…