most citedCritical assessment of machine-learned repulsive potentials for the Density Functional based Tight-Binding method: a case study for pure silicon

6 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2021★ 6 cited

Critical assessment of machine-learned repulsive potentials for the Density Functional based Tight-Binding method: a case study for pure silicon

Dylan Bissuel, Tristan Albaret, Thomas A. Niehaus

We investigate the feasability of improving the semi-empirical density functional based tight-binding method (DFTB) through a general and transferable many-body repulsive potential…

cond-mat.soft2014

Rheological properties vs Local Dynamics in model disordered materials at Low Temperature

C. Fusco, T. Albaret, A. Tanguy

We study the rheological response at low temperature of a sheared model disordered material as a function of the bond rigidity. We find that the flow curves follow a Herschel-Bulkl…