Gaussian process regression for materials and molecules
VL Deringer, AP Bartók, N Bernstein… - Chemical …, 2021 - ACS Publications
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 …
Machine learning force fields
In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …
numerous advances previously out of reach due to the computational complexity of …
Electrolyte design for Li-ion batteries under extreme operating conditions
The ideal electrolyte for the widely used LiNi0. 8Mn0. 1Co0. 1O2 (NMC811)|| graphite
lithium-ion batteries is expected to have the capability of supporting higher voltages (≥ 4.5 …
lithium-ion batteries is expected to have the capability of supporting higher voltages (≥ 4.5 …
CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling
Large-scale simulations with complex electron interactions remain one of the greatest
challenges for atomistic modelling. Although classical force fields often fail to describe the …
challenges for atomistic modelling. Although classical force fields often fail to describe the …
A universal graph deep learning interatomic potential for the periodic table
Interatomic potentials (IAPs), which describe the potential energy surface of atoms, are a
fundamental input for atomistic simulations. However, existing IAPs are either fitted to narrow …
fundamental input for atomistic simulations. However, existing IAPs are either fitted to narrow …
Spglib: a software library for crystal symmetry search
ABSTRACT A computer algorithm to search the symmetries of crystal structures, as
implemented in the spglib code, is described. An iterative algorithm is employed to robustly …
implemented in the spglib code, is described. An iterative algorithm is employed to robustly …
LAMMPS-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
Since the classical molecular dynamics simulator LAMMPS was released as an open source
code in 2004, it has become a widely-used tool for particle-based modeling of materials at …
code in 2004, it has become a widely-used tool for particle-based modeling of materials at …
Suspension electrolyte with modified Li+ solvation environment for lithium metal batteries
Designing a stable solid–electrolyte interphase on a Li anode is imperative to developing
reliable Li metal batteries. Herein, we report a suspension electrolyte design that modifies …
reliable Li metal batteries. Herein, we report a suspension electrolyte design that modifies …
Constrained C2 adsorbate orientation enables CO-to-acetate electroreduction
The carbon dioxide and carbon monoxide electroreduction reactions, when powered using
low-carbon electricity, offer pathways to the decarbonization of chemical manufacture …
low-carbon electricity, offer pathways to the decarbonization of chemical manufacture …
STING agonist delivery by tumour-penetrating PEG-lipid nanodiscs primes robust anticancer immunity
Activation of the innate immune STimulator of INterferon Genes (STING) pathway potentiates
antitumour immunity, but systemic delivery of STING agonists to tumours is challenging. We …
antitumour immunity, but systemic delivery of STING agonists to tumours is challenging. We …