activity
20162025
most citedThe kinetics of the ice-water interface from ab initio machine learning simulations

27 citations · 58 across the 13 of their papers we have counts for

collaborators
Showing 2024Show all

7 papers · 1 filter

cond-mat.mtrl-sci2024

Towards decoding the structure of water-magnetite interface

Salvatore Romano, Harsharan Kaur, Moritz Zelenka +9

The molecular structure of water at iron-oxide interfaces is determined by the protonation state, orientation and population of interfacial OH species. These microscopic features c…

cond-mat.mes-hall2024

Electron-beam-induced adatom-vacancy-complexes in mono- and bilayer phosphorene

Carsten Speckmann, Andrea Angeletti, Lukáš Kývala +7

Phosphorene, a puckered two-dimensional allotrope of phosphorus, has sparked considerable interest in recent years due to its potential especially for optoelectronic applications w…

physics.comp-ph2024★ 1 cited

Structure and dynamics of the magnetite(001)/water interface from molecular dynamics simulations based on a neural network potential

Salvatore Romano, Pablo Montero de Hijes, Matthias Meier +3

The magnetite/water interface is commonly found in nature and plays a crucial role in various technological applications. However, our understanding of its structural and dynamical…

cond-mat.mtrl-sci2024

Thermodynamics of alkali feldspar solid solutions with varying Al-Si order: atomistic simulations using a neural network potential

Alexander Gorfer, David Heuser, Rainer Abart +1

The thermodynamic mixing properties of alkali feldspar solid solutions between the Na and K end members were computed through atomistic simulations using a neural network potential…

cond-mat.mtrl-sci2024

Mechanism and kinetics of sodium diffusion in Na-feldspar from neural network based atomistic simulations

Alexander Gorfer, Rainer Abart, Christoph Dellago

Alkali diffusion is a first-order control for microstructure and compositional evolution of feldspar during cooling from high temperatures of primary magmatic or metamorphic crysta…

cond-mat.mtrl-sci2024

Unsupervised identification of crystal defects from atomistic potential descriptors

Lukáš Kývala, Pablo Montero De Hijes, Christoph Dellago

Identifying crystal defects is vital for unraveling the origins of many physical phenomena. Traditionally used order parameters are system-dependent and can be computationally expe…

cond-mat.mtrl-sci2024★ 3 cited

Structure and thermodynamics of defects in Na-feldspar from a neural network potential

Alexander Gorfer, Rainer Abart, Christoph Dellago

The diffusive phase transformations occurring in feldspar, a common mineral in the crust of the Earth, are essential for reconstructing the thermal histories of magmatic and metamo…