1.1k citations · 4k across the 27 of their papers we have counts for
10 papers · 1 filter
Introduction to machine learning potentials for atomistic simulations
Fabian L. Thiemann, Niamh O'Neill, Venkat Kapil +2
Machine learning potentials have revolutionised the field of atomistic simulations in recent years and are becoming a mainstay in the toolbox of computational scientists. This pape…
Understanding the anomalously low dielectric constant of confined water: an ab initio study
Thomas Dufils, Christoph Schran, Ji Chen +3
Recent experiments have shown that the out-of-plane dielectric constant of water confined in nanoslits of graphite and hexagonal boron nitride (hBN) is vanishingly small. Despite e…
Crumbling Crystals: On the Dissolution Mechanism of NaCl in Water
Niamh O'Neill, Christoph Schran, Stephen J. Cox +1
Life on Earth depends upon the dissolution of ionic salts in water, particularly NaCl. However, an atomistic scale understanding of the process remains elusive. Simulations lend th…
Machine learning potentials for complex aqueous systems made simple
Christoph Schran, Fabian L. Thiemann, Patrick Rowe +3
Simulation techniques based on accurate and efficient representations of potential energy surfaces are urgently needed for the understanding of complex aqueous systems such as soli…
The quantum nature of hydrogen
Wei Fang, Ji Chen, Yexin Feng +2
Hydrogen is the most abundant element in the universe. It is also the lightest and as such the most quantum of the elements, in the sense that quantum tunnelling, quantum delocalis…
Ice is Born in Low-Mobility Regions of Supercooled Liquid Water
Martin Fitzner, Gabriele C. Sosso, Stephen J. Cox +1
When an ice crystal is born from liquid water two key changes occur: (i) the molecules order; and (ii) the mobility of the molecules drops as they adopt their lattice positions. Mo…