Fluids and electrolytes under confinement in single-digit nanopores

NR Aluru, F Aydin, MZ Bazant, D Blankschtein… - Chemical …, 2023 - ACS Publications
Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics
and chemistry that impact the mass transport and energy efficiency in many important …

Data‐driven machine learning for understanding surface structures of heterogeneous catalysts

H Li, Y Jiao, K Davey, SZ Qiao - … Chemie International Edition, 2023 - Wiley Online Library
The design of heterogeneous catalysts is necessarily surface‐focused, generally achieved
via optimization of adsorption energy and microkinetic modelling. A prerequisite is to ensure …

The first-principles phase diagram of monolayer nanoconfined water

V Kapil, C Schran, A Zen, J Chen, CJ Pickard… - Nature, 2022 - nature.com
Water in nanoscale cavities is ubiquitous and of central importance to everyday phenomena
in geology and biology. However, the properties of nanoscale water can be substantially …

Improving the accuracy of atomistic simulations of the electrochemical interface

R Sundararaman, D Vigil-Fowler, K Schwarz - Chemical reviews, 2022 - ACS Publications
Atomistic simulation of the electrochemical double layer is an ambitious undertaking,
requiring quantum mechanical description of electrons, phase space sampling of liquid …

How water attacks MXene

T Wu, PRC Kent, Y Gogotsi, D Jiang - Chemistry of Materials, 2022 - ACS Publications
Two-dimensional (2D) transition metal carbides and nitrides (MXenes) have shown
outstanding performances in electrochemical energy storage and many other applications …

[HTML][HTML] Machine learning potentials for metal-organic frameworks using an incremental learning approach

S Vandenhaute, M Cools-Ceuppens… - npj Computational …, 2023 - nature.com
Computational modeling of physical processes in metal-organic frameworks (MOFs) is
highly challenging due to the presence of spatial heterogeneities and complex operating …

Surface stratification determines the interfacial water structure of simple electrolyte solutions

Y Litman, KY Chiang, T Seki, Y Nagata, M Bonn - Nature Chemistry, 2024 - nature.com
The distribution of ions at the air/water interface plays a decisive role in many natural
processes. Several studies have reported that larger ions tend to be surface-active, implying …

How to train a neural network potential

AM Tokita, J Behler - The Journal of Chemical Physics, 2023 - pubs.aip.org
The introduction of modern Machine Learning Potentials (MLPs) has led to a paradigm
change in the development of potential energy surfaces for atomistic simulations. By …

Liquid-liquid transition in water from first principles

TE Gartner III, PM Piaggi, R Car, AZ Panagiotopoulos… - Physical review …, 2022 - APS
A long-standing question in water research is the possibility that supercooled liquid water
can undergo a liquid-liquid phase transition (LLT) into high-and low-density liquids. We …

Self-consistent determination of long-range electrostatics in neural network potentials

A Gao, RC Remsing - Nature communications, 2022 - nature.com
Abstract Machine learning has the potential to revolutionize the field of molecular simulation
through the development of efficient and accurate models of interatomic interactions. Neural …