Gaussian process regression for materials and molecules
We provide an introduction to Gaussian process regression (GPR) machine-learning
methods in computational materials science and chemistry. The focus of the present review …
methods in computational materials science and chemistry. The focus of the present review …
Borates: A rich source for optical materials
The primary goal of this review is to present a clear chemical perspective of borates in order
to stimulate and facilitate the discovery of new borate-based optical materials. These …
to stimulate and facilitate the discovery of new borate-based optical materials. These …
VASPKIT: A user-friendly interface facilitating high-throughput computing and analysis using VASP code
We present the VASPKIT, a command-line program that aims at providing a robust and user-
friendly interface to perform high-throughput analysis of a variety of material properties from …
friendly interface to perform high-throughput analysis of a variety of material properties from …
Achieving the full-wavelength phase-matching for efficient nonlinear optical frequency conversion in C(NH2)3BF4
Phase-matching of light waves is a critical condition for maximizing the efficiency of
nonlinear frequency conversion processes in nonlinear optical crystals; however, phase …
nonlinear frequency conversion processes in nonlinear optical crystals; however, phase …
Physics-inspired structural representations for molecules and materials
The first step in the construction of a regression model or a data-driven analysis, aiming to
predict or elucidate the relationship between the atomic-scale structure of matter and its …
predict or elucidate the relationship between the atomic-scale structure of matter and its …
Phase transitions in 2D materials
The discovery and control of new phases of matter is a central endeavour in materials
research. The emergence of atomically thin 2D materials, such as transition-metal …
research. The emergence of atomically thin 2D materials, such as transition-metal …
Mattergen: a generative model for inorganic materials design
The design of functional materials with desired properties is essential in driving
technological advances in areas like energy storage, catalysis, and carbon capture …
technological advances in areas like energy storage, catalysis, and carbon capture …
First‐principles multiscale modeling of mechanical properties in graphene/borophene heterostructures empowered by machine‐learning interatomic potentials
Density functional theory calculations are robust tools to explore the mechanical properties
of pristine structures at their ground state but become exceedingly expensive for large …
of pristine structures at their ground state but become exceedingly expensive for large …
Design principles for high-temperature superconductors with a hydrogen-based alloy backbone at moderate pressure
Hydrogen-based superconductors provide a route to the long-sought goal of room-
temperature superconductivity, but the high pressures required to metallize these materials …
temperature superconductivity, but the high pressures required to metallize these materials …
Synthesis of yttrium superhydride superconductor with a transition temperature up to 262 K by catalytic hydrogenation at high pressures
The recent observation of room-temperature superconductivity will undoubtedly lead to a
surge in the discovery of new, dense, hydrogen-rich materials. The rare earth metal …
surge in the discovery of new, dense, hydrogen-rich materials. The rare earth metal …