Electrocatalysis in alkaline media and alkaline membrane-based energy technologies

Y Yang, CR Peltier, R Zeng, R Schimmenti, Q Li… - Chemical …, 2022 - ACS Publications
Hydrogen energy-based electrochemical energy conversion technologies offer the promise
of enabling a transition of the global energy landscape from fossil fuels to renewable energy …

Four generations of high-dimensional neural network potentials

J Behler - Chemical Reviews, 2021 - ACS Publications
Since their introduction about 25 years ago, machine learning (ML) potentials have become
an important tool in the field of atomistic simulations. After the initial decade, in which neural …

Absence of CO2 electroreduction on copper, gold and silver electrodes without metal cations in solution

MCO Monteiro, F Dattila, B Hagedoorn… - Nature Catalysis, 2021 - nature.com
The electrocatalytic reduction of carbon dioxide is widely studied for the sustainable
production of fuels and chemicals. Metal ions in the electrolyte influence the reaction …

Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review

VT Sabe, T Ntombela, LA Jhamba… - European Journal of …, 2021 - Elsevier
Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-
clinical drug discovery, and various computational techniques and software programs are …

Deep potential molecular dynamics: a scalable model with the accuracy of quantum mechanics

L Zhang, J Han, H Wang, R Car, WE - Physical review letters, 2018 - APS
We introduce a scheme for molecular simulations, the deep potential molecular dynamics
(DPMD) method, based on a many-body potential and interatomic forces generated by a …

[HTML][HTML] CP2K: An electronic structure and molecular dynamics software package-Quickstep: Efficient and accurate electronic structure calculations

TD Kühne, M Iannuzzi, M Del Ben, VV Rybkin… - The Journal of …, 2020 - pubs.aip.org
CP2K is an open source electronic structure and molecular dynamics software package to
perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is …

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

H Wang, L Zhang, J Han, E Weinan - Computer Physics Communications, 2018 - Elsevier
Recent developments in many-body potential energy representation via deep learning have
brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular …

Quantum algorithms for quantum chemistry and quantum materials science

B Bauer, S Bravyi, M Motta, GKL Chan - Chemical Reviews, 2020 - ACS Publications
As we begin to reach the limits of classical computing, quantum computing has emerged as
a technology that has captured the imagination of the scientific world. While for many years …

The Role of Cation Acidity on the Competition between Hydrogen Evolution and CO2 Reduction on Gold Electrodes

MCO Monteiro, F Dattila, N López… - Journal of the American …, 2021 - ACS Publications
CO2 electroreduction (CO2RR) is a sustainable alternative for producing fuels and
chemicals. Metal cations in the electrolyte have a strong impact on the reaction, but mainly …

Perspective: Machine learning potentials for atomistic simulations

J Behler - The Journal of chemical physics, 2016 - pubs.aip.org
Nowadays, computer simulations have become a standard tool in essentially all fields of
chemistry, condensed matter physics, and materials science. In order to keep up with state …