Higher-order equivariant neural networks for charge density prediction in materials
The calculation of electron density distribution using density functional theory (DFT) in
materials and molecules is central to the study of their quantum and macro-scale properties …
materials and molecules is central to the study of their quantum and macro-scale properties …
First-Principles Investigation of Stability and Superconductivity in Ternary Yttrium–Praseodymium Hydrides under High Pressure
Recent progress on the theoretical and experimental aspects of ternary superhydrides has
confirmed their potential to synthesize the most anticipated room-temperature …
confirmed their potential to synthesize the most anticipated room-temperature …
Ab initio study of phase stability and optical properties of TiN and VN nitrides in different phases
BO Mnisi - Solid State Communications, 2024 - Elsevier
Transition metal nitrides are ceramic materials known for their remarkable physical and
mechanical characteristics, particularly their hardness. As part of this study, the structural …
mechanical characteristics, particularly their hardness. As part of this study, the structural …
Strong anisotropy of Sc 2 X 2 Se 2 (X= Cl, Br, I) monolayers contributes to high thermoelectric performance
As a novel type of anisotropic two-dimensional material, extensive attention has been paid
to the thermoelectric (TE) properties of FeOCl-type monolayers, such as Al2X2Se2 (X= Cl …
to the thermoelectric (TE) properties of FeOCl-type monolayers, such as Al2X2Se2 (X= Cl …
Doping-mediated electronic and magnetic properties of graphene-like ionic NaX (X= F and Cl) monolayers
In this work, the stability, and electronic and magnetic properties of pristine and doped
graphene-like ionic NaX (X= F and Cl) monolayers are explored using first-principles …
graphene-like ionic NaX (X= F and Cl) monolayers are explored using first-principles …
Magnetic iron-cobalt silicides discovered using machine-learning
We employ machine-learning (ML) combined with first principles calculations to discover
different rare-earth-free magnetic iron-cobalt silicide compounds. Deep machine-learning …
different rare-earth-free magnetic iron-cobalt silicide compounds. Deep machine-learning …
Machine learning accelerated discovery of superconducting two-dimensional Janus transition metal sulfhydrates
The MoSH monolayer, one of the Janus transition metal sulfhydrates synthesized by
stripping the top-layer S of MoS 2 and replacing it with H atoms [Wan, ACS Nano 15, 20319 …
stripping the top-layer S of MoS 2 and replacing it with H atoms [Wan, ACS Nano 15, 20319 …
Uncovering the phonon spectra and lattice dynamics of plastically deformable InSe van der Waals crystals
Abstract Stacking two-dimensional (2D) van der Waals (vdW) materials in a layered bulk
structure provides an appealing platform for the emergence of exotic physical properties. As …
structure provides an appealing platform for the emergence of exotic physical properties. As …
Learning from models: high-dimensional analyses on the performance of machine learning interatomic potentials
Abstract Machine learning interatomic potential (MLIP) has been widely adopted for
atomistic simulations. While errors and discrepancies for MLIPs have been reported, a …
atomistic simulations. While errors and discrepancies for MLIPs have been reported, a …
Toward an accurate equation of state and B1-B2 phase boundary for magnesium oxide up to terapascal pressures and electron-volt temperatures
By applying auxiliary-field quantum Monte Carlo, we calculate the equation of state (EOS)
and B1-B2 phase transition of magnesium oxide (MgO) up to 1 TPa. The results agree with …
and B1-B2 phase transition of magnesium oxide (MgO) up to 1 TPa. The results agree with …