activity
20182022
collaborators

5 papers

cond-mat.mtrl-sci2022

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…

cond-mat.mtrl-sci2022

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…

cond-mat.dis-nn2021

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…

cond-mat.stat-mech2021

On the Excess Entropy Scaling Law: a Potential Energy Landscape View

Anthony Saliou, Philippe Jarry, Noel Jakse

The relationship between excess entropy and diffusion is revisited by means of large-scale computer simulation combined to supervised learning approach to determine the excess entr…

cond-mat.soft2018

Fast dynamics perspective on the breakdown of the Stokes-Einstein law in fragile glassformers

F. Puosi, A. Pasturel, N. Jakse +1

The breakdown of the Stokes-Einstein (SE) law in fragile glassformers is examined by Molecular-Dynamics simulations of atomic liquids and polymers and consideration of the experime…