1 citations · 2 across the 7 of their papers we have counts for
8 papers
Homogeneous Nucleation of Undercooled Al-Ni melts via a Machine-Learned Interaction Potential
Johannes Sandberg, Thomas Voigtmann, Emilie Devijver +1
Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describin…
Feature Selection for High-Dimensional Neural Network Potentials with the Adaptive Group Lasso
Johannes Sandberg, Thomas Voigtmann, Emilie Devijver +1
Neural network potentials are a powerful tool for atomistic simulations, allowing to accurately reproduce \textit{ab initio} potential energy surfaces with computational performanc…
An Artificial Neural Network-based Density Functional Approach for Adiabatic Energy Differences in Transition Metal Complexes
Joao Paulo Almeida de Mendonca, Lorenzo A. Mariano, Emilie Devijver +2
During the past decades, approximate Kohn-Sham density-functional theory schemes garnered many successes in computational chemistry and physics; yet the performance in the predicti…
Crystal Nucleation in Al-Ni Alloys: an Unsupervised Chemical and Topological Learning Approach
Sébastien Becker, Emilie Devijver, Rémi Molinier +1
Crystallization represents a fundamental process engendering solidification of a material and determines its microstructure. Driven by complex phenomena at the atomic scale, its un…
Unsupervised topological learning approach of crystal nucleation in pure Tantalum
Sébastien Becker, Emilie Devijver, Rémi Molinier +1
Nucleation phenomena commonly observed in our every day life are of fundamental, technological and societal importance in many areas, but some of their most intimate mechanisms rem…
Interatomic machine learning potentials for aluminium: application to solidification phenomena
Noel Jakse, Johannes Sandberg, Leon F. Granz +6
In studying solidification process by simulations on the atomic scale, the modeling of crystal nucleation or amorphisation requires the construction of interatomic interactions tha…
Unsupervised topological learning approach of crystal nucleation
Sébastien Becker, Emilie Devijver, Rémi Molinier +1
Nucleation phenomena commonly observed in our every day life are of fundamental, technological and societal importance in many areas, but some of their most intimate mechanisms rem…
Unsupervised topological learning for identification of atomic structures
Sébastien Becker, Emilie Devijver, Rémi Molinier +1
We propose an unsupervised learning methodology with descriptors based on Topological Data Analysis (TDA) concepts to describe the local structural properties of materials at the a…