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

Bibliographische Detailangaben
1. Verfasser: Tomacruz, Jan Goran T. (VerfasserIn)
Weitere Verfasser: Joey D. Ocon (adviser.), Padama, Allan Abraham B. (adviser.)
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Quezon City College of Engineering, University of the Philippines Diliman 2022.
Schlagworte:
Density functionals.
Machine learning.
Online Zugang:Abstract