Smart energy models for atomistic simulations using a DFT-driven multifidelity approach

21 Aug 2018Luca MessinaAlessio QuaglinoAlexandra GoryaevaMihai-Cosmin MarinicaChristophe DomainNicolas CastinGiovanni BonnyRolf Krause

The reliability of atomistic simulations depends on the quality of the underlying energy models providing the source of physical information, for instance for the calculation of migration barriers in atomistic Kinetic Monte Carlo simulations. Accurate (high-fidelity) methods are often available, but since they are usually computationally expensive, they must be replaced by less accurate (low-fidelity) models that introduce some degrees of approximation... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.