150 citations · 194 across the 3 of their papers we have counts for
3 papers
Stress and heat flux via automatic differentiation
Marcel F. Langer, J. Thorben Frank, Florian Knoop
Machine-learning potentials provide computationally efficient and accurate approximations of the Born-Oppenheimer potential energy surface. This potential determines many materials…
Heat flux for semi-local machine-learning potentials
Marcel F. Langer, Florian Knoop, Christian Carbogno +2
The Green-Kubo (GK) method is a rigorous framework for heat transport simulations in materials. However, it requires an accurate description of the potential-energy surface and car…
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning
Marcel F. Langer, Alex Goeßmann, Matthias Rupp
Computational study of molecules and materials from first principles is a cornerstone of physics, chemistry, and materials science, but limited by the cost of accurate and precise…