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

Opis bibliograficzny
1. autor: Tomacruz, Jan Goran T. (Autor)
Kolejni autorzy: Joey D. Ocon (adviser.), Padama, Allan Abraham B. (adviser.)
Format: Praca dyplomowa
Język:English
Wydane: Quezon City College of Engineering, University of the Philippines Diliman 2022.
Hasła przedmiotowe:
Density functionals.
Machine learning.
Dostęp online:Abstract