Machine Learning-accelerated Density Functional Theory (ML-DFT) screening of bimetallic transition metal surfaces based on single-atom adsorption energy predictions

Machine Learning-accelerated Density Functional Theory (ML-DFT) screening of bimetallic transition metal surfaces based on single-atom adsorption energy predictions

Detalles Bibliográficos
Autor principal: Tomacruz, Jan Goran T. (Autor)
Otros Autores: Joey D. Ocon (adviser.), Padama, Allan Abraham B. (adviser.)
Formato: Tesis
Lenguaje:English
Publicado: Quezon City College of Engineering, University of the Philippines Diliman 2022.
Materias:
Density functionals.
Machine learning.
Acceso en línea:Abstract