4 papers
Finite-Temperature Thermodynamics of Cu(100) Oxidation: Missing-Row Reconstruction, Defect States, and Order-Disorder Transition from Nested Sampling
Felix Riccius, Karsten Reuter, Hendrik H. Heenen +1
Metal surfaces undergo structural, compositional, and morphological changes in response to their chemical environment. Tuning the surfaces' function and stability for a given appli…
Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation for Training Machine-Learned Interatomic Potentials
Adam Lahouari, Jutta Rogal, Mark E. Tuckerman
Machine learning interatomic potentials (MLIPs) have become powerful tools to extend molecular simulations beyond the limits of quantum methods, offering near-quantum accuracy at m…
MXtalTools: A Toolkit for Machine Learning on Molecular Crystals
Michael Kilgour, Mark E. Tuckerman, Jutta Rogal
We present MXtalTools, a flexible Python package for the data-driven modelling of molecular crystals, facilitating machine learning studies of the molecular solid state. MXtalTools…
Multi-Type Point Cloud Autoencoder: A Complete Equivariant Embedding for Molecule Conformation and Pose
Michael Kilgour, Mark Tuckerman, Jutta Rogal
Representations are a foundational component of any modelling protocol, including on molecules and molecular solids. For tasks that depend on knowledge of both molecular conformati…