From the 1 of 4 linked papers with an AI index.
4 papers
Self-organized defect clustering and concentration-dependent vacancy diffusion in MoS
Aaron Flötotto, Benjamin Spetzler, Martin Ziegler +2
The paper uses kinetic Monte‑Carlo simulations, informed by machine‑learning interatomic potentials, to study how sulfur vacancies in MoS₂ cluster and diffuse, revealing concentrat…
Large-scale cooperative sulfur vacancy dynamics in two-dimensional MoS2 from machine learning interatomic potentials
Aaron Flötotto, Benjamin Spetzler, Rose von Stackelberg +3
The formation of extended sulfur vacancies in MoS2 monolayers is closely associated with catalytic activity and may also be the basis for its memristive behavior. Nanosecond-scale…
Optimizing Machine Learning Potentials for Hydroxide Transport: Surprising Efficiency of Single-Concentration Training
Jonas Hänseroth, Christian DreÃler
We investigate the transferability of machine learning interatomic potentials across concentration variations in chemically similar systems, using aqueous potassium hydroxide solut…
Modelling complex proton transport phenomena -- Exploring the limits of fine-tuning and transferability of foundational machine-learned force fields
Malte Grunert, Max GroÃmann, Jonas Hänseroth +5
The solid acids CsHPO and Cs(HPO)(HPO) pose significant challenges for the simulation of proton transport phenomena. In this work, we use the recent…