225 citations · 371 across the 4 of their papers we have counts for
4 papers
Combining genetic algorithm and compressed sensing for features and operators selection in symbolic regression
Aliaksei Mazheika, Sergey V. Levchenko, Luca M. Ghiringhelli
Symbolic-inference methods have recently found a broad application in materials science. In particular, the Sure-Independence Screening and Sparsifying Operator (SISSO) performs sy…
Data-driven design of new catalytic materials in methane oxidation based on a site isolation concept
A. Mazheika, M. Geske, M. Muller +3
The conversion of natural gas (methane) to ethane and ethylene (OCM: oxidative coupling of methane) facilitates its transportation and provides a way to synthesize higher value che…
Single-Atom Alloy Catalysts Designed by First-Principles Calculations and Artificial Intelligence
Zhong-Kang Han, Debalaya Sarker, Runhai Ouyang +2
Single-atom metal alloy catalysts (SAACs) have recently become a very active new frontier in catalysis research. The simultaneous optimization of both facile dissociation of reacta…
Artifcial-intelligence-driven discovery of catalyst \textit{genes} with application to CO2 activation on semiconductor oxides
Aliaksei Mazheika, Yanggang Wang, Rosendo Valero +5
Catalytic-materials design requires predictive modeling of the interaction between catalyst and reactants. This is challenging due to the complexity and diversity of structure-prop…