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 …
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 …
Machine learning for electronically excited states of molecules
Electronically excited states of molecules are at the heart of photochemistry, photophysics,
as well as photobiology and also play a role in material science. Their theoretical description …
as well as photobiology and also play a role in material science. Their theoretical description …
Molecular excited states through a machine learning lens
Theoretical simulations of electronic excitations and associated processes in molecules are
indispensable for fundamental research and technological innovations. However, such …
indispensable for fundamental research and technological innovations. However, such …
Material evolution with nanotechnology, nanoarchitectonics, and materials informatics: what will be the next paradigm shift in nanoporous materials?
Materials science and chemistry have played a central and significant role in advancing
society. With the shift toward sustainable living, it is anticipated that the development of …
society. With the shift toward sustainable living, it is anticipated that the development of …
Experimental and computational synergistic design of Cu and Fe catalysts for the reverse water–gas shift: A review
Strategies to capture and sequester ever-increasing anthropogenic CO2 emissions include
adsorbing CO2 onto inorganic substrates and then storing it in reservoirs, changing land use …
adsorbing CO2 onto inorganic substrates and then storing it in reservoirs, changing land use …
Bioinspired angstrom-scale heterogeneous MOF-on-MOF membrane for osmotic energy harvesting
Membrane-based salinity gradient energy generation from the osmotic potential at the
interface of a river and seawater through reverse electrodialysis is a promising route for …
interface of a river and seawater through reverse electrodialysis is a promising route for …
Rapidly In Situ Cross-Linked Poly (butylene oxide) Electrolyte Interface Enabling Halide-Based All-Solid-State Lithium Metal Batteries
Halide-based solid-state halide electrolytes (SSEs) were recently revived as promising
candidates for next-generation all-solid-state batteries due to their superionic conductivity …
candidates for next-generation all-solid-state batteries due to their superionic conductivity …
Construction of high accuracy machine learning interatomic potential for surface/interface of nanomaterials—A review
The inherent discontinuity and unique dimensional attributes of nanomaterial surfaces and
interfaces bestow them with various exceptional properties. These properties, however, also …
interfaces bestow them with various exceptional properties. These properties, however, also …
Benchmark of GW Methods for Core-Level Binding Energies
The GW approximation has recently gained increasing attention as a viable method for the
computation of deep core-level binding energies as measured by X-ray photoelectron …
computation of deep core-level binding energies as measured by X-ray photoelectron …