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

Podrobná bibliografie
Hlavní autor: Tomacruz, Jan Goran T. (Autor)
Další autoři: Joey D. Ocon (adviser.), Padama, Allan Abraham B. (adviser.)
Médium: Diplomová práce
Jazyk:English
Vydáno: Quezon City College of Engineering, University of the Philippines Diliman 2022.
Témata:
Density functionals.
Machine learning.
On-line přístup:Abstract