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 …
Automated reaction kinetics of gas-phase organic species over multiwell potential energy surfaces
Automation of rate-coefficient calculations for gas-phase organic species became possible
in recent years and has transformed how we explore these complicated systems …
in recent years and has transformed how we explore these complicated systems …
The mechanism for acetate formation in electrochemical CO (2) reduction on Cu: selectivity with potential, pH, and nanostructuring
Nanostructured Cu catalysts have increased the selectivities and geometric activities for
high value C–C coupled (C2) products (ethylene, ethanol, and acetate) in the …
high value C–C coupled (C2) products (ethylene, ethanol, and acetate) in the …
Unified graph neural network force-field for the periodic table: solid state applications
Classical force fields (FFs) based on machine learning (ML) methods show great potential
for large scale simulations of solids. MLFFs have hitherto largely been designed and fitted …
for large scale simulations of solids. MLFFs have hitherto largely been designed and fitted …
Assessment and optimization of the fast inertial relaxation engine (fire) for energy minimization in atomistic simulations and its implementation in lammps
In atomistic simulations, pseudo-dynamical relaxation schemes often exhibit better
performance and accuracy in finding local minima than line-search-based descent …
performance and accuracy in finding local minima than line-search-based descent …
Fast and accurate machine learning strategy for calculating partial atomic charges in metal–organic frameworks
Computational high-throughput screening using molecular simulations is a powerful tool for
identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation …
identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation …
Understanding activity trends in furfural hydrogenation on transition metal surfaces
Furfural hydrogenation to furfuryl alcohol is an industrially significant reaction for biomass
valorization. The hydrogenation process has been mainly catalyzed by chromite-based …
valorization. The hydrogenation process has been mainly catalyzed by chromite-based …
Solvation at metal/water interfaces: An ab initio molecular dynamics benchmark of common computational approaches
Determining the influence of the solvent on electrochemical reaction energetics is a central
challenge in our understanding of electrochemical interfaces. To date, it is unclear how well …
challenge in our understanding of electrochemical interfaces. To date, it is unclear how well …
Dipole-Field Interactions Determine the CO2 Reduction Activity of 2D Fe–N–C Single-Atom Catalysts
Iron–nitrogen-doped graphene (FeNC) has emerged as an exciting earth-abundant catalyst
for electrochemical CO2 reduction (CO2R). However, standard theoretical approaches …
for electrochemical CO2 reduction (CO2R). However, standard theoretical approaches …
The Role of Roughening to Enhance Selectivity to C2+ Products during CO2 Electroreduction on Copper
Roughened copper electrodes, including those derived from cuprous oxide, have long been
known to exhibit an enhanced Faradaic efficiency to C2+ products during CO2 …
known to exhibit an enhanced Faradaic efficiency to C2+ products during CO2 …