Fluids and electrolytes under confinement in single-digit nanopores
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 …
and chemistry that impact the mass transport and energy efficiency in many important …
Data‐driven machine learning for understanding surface structures of heterogeneous catalysts
The design of heterogeneous catalysts is necessarily surface‐focused, generally achieved
via optimization of adsorption energy and microkinetic modelling. A prerequisite is to ensure …
via optimization of adsorption energy and microkinetic modelling. A prerequisite is to ensure …
The first-principles phase diagram of monolayer nanoconfined water
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 …
in geology and biology. However, the properties of nanoscale water can be substantially …
Improving the accuracy of atomistic simulations of the electrochemical interface
Atomistic simulation of the electrochemical double layer is an ambitious undertaking,
requiring quantum mechanical description of electrons, phase space sampling of liquid …
requiring quantum mechanical description of electrons, phase space sampling of liquid …
[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 …
highly challenging due to the presence of spatial heterogeneities and complex operating …
Surface stratification determines the interfacial water structure of simple electrolyte solutions
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 …
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 …
change in the development of potential energy surfaces for atomistic simulations. By …
Liquid-liquid transition in water from first principles
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 …
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 …
through the development of efficient and accurate models of interatomic interactions. Neural …