Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields
We introduce a compact cluster expansion method constructed over Jacobi and Legendre
polynomials to generate highly accurate and flexible machine-learning force fields. The …
polynomials to generate highly accurate and flexible machine-learning force fields. The …
Exploring model complexity in machine learned potentials for simulated properties
Abstract Machine learning (ML) enables the development of interatomic potentials with the
accuracy of first principles methods while retaining the speed and parallel efficiency of …
accuracy of first principles methods while retaining the speed and parallel efficiency of …
Fast proper orthogonal descriptors for many-body interatomic potentials
NC Nguyen - Physical Review B, 2023 - APS
The development of differentiable invariant descriptors for accurate representations of
atomic environments plays a central role in the success of interatomic potentials for …
atomic environments plays a central role in the success of interatomic potentials for …
First-principles, machine learning and symbolic regression modelling for organic molecule adsorption on two-dimensional CaO surface
Data-driven methods are receiving significant attention in recent years for chemical and
materials researches; however, more works should be done to leverage the new paradigm …
materials researches; however, more works should be done to leverage the new paradigm …
Proper orthogonal descriptors for multi-element chemical systems
NC Nguyen - Journal of Computational Physics, 2024 - Elsevier
We introduce the proper orthogonal descriptors for efficient and accurate interatomic
potentials of multi-element chemical systems. The potential energy surface of a multi …
potentials of multi-element chemical systems. The potential energy surface of a multi …
Environment-adaptive machine learning potentials
The development of interatomic potentials that can accurately capture a wide range of phys
ical phenomena and diverse environments is of significant interest, but it presents a …
ical phenomena and diverse environments is of significant interest, but it presents a …
Transferability of interatomic potentials for germanene (2D germanium)
M Maździarz - Journal of Applied Physics, 2023 - pubs.aip.org
The capacities of various interatomic potentials available for elemental germanium, with the
scope to choose the potential suitable for the modeling of germanene (2D germanium) …
scope to choose the potential suitable for the modeling of germanene (2D germanium) …
[PDF][PDF] The Jacobi-Legendre framework for Machine Learning in Materials Investigation and Discovery
M Domina, S Sanvito - 2024 - tara.tcd.ie
Abstract Machine-learning models have rapidly become fundamental tools in the study of
materials properties. In the past few years there has been a surge of interest in the …
materials properties. In the past few years there has been a surge of interest in the …
[PDF][PDF] Data-driven magnetic materials inverse design
M Cobelli - 2024 - tara.tcd.ie
Magnetic materials have diverse applications across multiple sectors, ranging from magnetic
resonance imaging machines, used to detect diseases, to electric motors, sensors, and wind …
resonance imaging machines, used to detect diseases, to electric motors, sensors, and wind …