688 citations
- University of ViennaAT22 papers
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18 papers · 1 filter
Machine Learning Study of Surface Reconstructions of the CuO(111) Surface
Payal Wadhwa, Michael Schmid, Georg Kresse
The atomic structure of the most stable reconstructed surface of cuprous oxide (CuO)(111) surface has been a longstanding topic of debate. In this study, we develop on-the-fl…
Density-Based Long-Range Electrostatic Descriptors for Machine Learning Force Fields
Carolin Faller, Merzuk Kaltak, Georg Kresse
This study presents a long-range descriptor for machine learning force fields (MLFFs) that maintains translational and rotational symmetry, similar to short-range descriptors while…
Machine learning density functionals from the random-phase approximation
Stefan Riemelmoser, Carla Verdi, Merzuk Kaltak +1
Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as…
How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
Emanuele Bosoni, Louis Beal, Marnik Bercx +42
In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter phys…
Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111)
Peitao Liu, Jiantao Wang, Noah Avargues +5
Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges t…
Efficient and improved prediction of the band offsets at semiconductor heterojunctions from meta-GGA density functionals
Arghya Ghosh, Subrata Jana, Tomáš Rauch +6
Accurate theoretical prediction of the band offsets at interfaces of semiconductor heterostructures can often be quite challenging. Although density functional theory has been reas…