15 citations · 36 across the 5 of their papers we have counts for
5 papers
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…
Decoding Energy Decomposition Analysis: Machine-Learned Insights on the Impact of the Density Functional on the Bonding Analysis
Toni Oestereich, Ralf Tonner-Zech, Julia Westermayr
The concept of chemical bonding is a crucial aspect of chemistry that aids in understanding the complexity and reactivity of molecules and materials. However, the interpretation of…
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…
Accurate first-principle bandgap predictions in strain-engineered ternary III-V semiconductors
Badal Mondal, Marcel Kröner, Thilo Hepp +2
Tuning the bandgap in ternary III-V semiconductors via modification of the composition or the strain in the material is a major approach for the design of optoelectronic materials.…
Systematic strain-induced bandgap tuning in binary III-V semiconductors from density functional theory
Badal Mondal, Ralf Tonner-Zech
The modification of the nature and size of bandgaps for III-V semiconductors is of strong interest for optoelectronic applications. Strain can be used to systematically tune the ba…