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87 papers
ACEpotentials.jl: A Julia Implementation of the Atomic Cluster Expansion
William C. Witt, Cas van der Oord, Elena Gelžinytė +10
We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion (D…
Machine learning of microscopic structure-dynamics relationships in complex molecular systems
Martina Crippa, Annalisa Cardellini, Matteo Cioni +2
In many complex molecular systems, the macroscopic ensemble's properties are controlled by microscopic dynamic events (or fluctuations) that are often difficult to detect via patte…
wfl Python Toolkit for Creating Machine Learning Interatomic Potentials and Related Atomistic Simulation Workflows
Elena Gelžinytė, Simon Wengert, Tamás K. Stenczel +4
Predictive atomistic simulations are increasingly employed for data intensive high throughput studies that take advantage of constantly growing computational resources. To handle t…
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science
David Peter Kovacs, Ilyes Batatia, Eszter Sara Arany +1
The MACE architecture represents the state of the art in the field of machine learning force fields for a variety of in-domain, extrapolation and low-data regime tasks. In this pap…
Structural Dynamics Descriptors for Metal Halide Perovskites
Xia Liang, Johan Klarbring, William Baldwin +3
Metal halide perovskites have shown extraordinary performance in solar energy conversion technologies. They have been classified as "soft semiconductors" due to their flexible corn…
Dynamic Local Structure in Caesium Lead Iodide: Spatial Correlation and Transient Domains
William Baldwin, Xia Liang, Johan Klarbring +8
Metal halide perovskites are multifunctional semiconductors with tunable structures and properties. They are highly dynamic crystals with complex octahedral tilting patterns and st…