402 citations · 1.7k across the 26 of their papers we have counts for
4 papers · 1 filter
Statistics makes a difference: Machine learning adsorption dynamics of functionalized cyclooctine on Si(001) at DFT accuracy
Hendrik Weiske, Rhyan Barrett, Ralf Tonner-Zech +2
The interpretation of experiments on reactive semiconductor surfaces requires statistically significant sampling of molecular dynamics, but conventional ab initio methods are limit…
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…
Machine learning for accelerated bandgap prediction in strain-engineered quaternary III-V semiconductors
Badal Mondal, Julia Westermayr, Ralf Tonner-Zech
Quaternary III-V semiconductors are one of the major promising material classes in optoelectronics. The bandgap and its character, direct or indirect, are the most important fundam…
Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic-inorganic interfaces
Julia Westermayr, Shayantan Chaudhuri, Andreas Jeindl +2
The computational prediction of the structure and stability of hybrid organic-inorganic interfaces provides important insights into the measurable properties of electronic thin fil…