DFT-PBE band gap correction using machine learning with a reduced set of features-Reference-Cited by-同舟云学术

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DFT-PBE band gap correction using machine learning with a reduced set of features

Published:2024-09 Issue: Volume:244 Page:113153
ISSN:0927-0256
Container-title:Computational Materials Science
language:en
Short-container-title:Computational Materials Science

Author:

Jihad Ibnu^ORCID,Anfa Miftah Hadi S.^ORCID,Alqahtani Saad M.,Alharbi Fahhad H.^ORCID

Publisher

Elsevier BV

Reference50 articles.

1. Merging materials and data science: Opportunities, challenges, and education in materials informatics;Oweida;MRS Adv.,2020

2. Machine learning for molecular and materials science;Butler;Nature,2018

3. Perspective: Materials informatics and big data: Realization of the fourth paradigm of science in materials science;Agrawal;Apl Mater.,2016

4. Recent advances and applications of machine learning in solid-state materials science;Schmidt;npj Comput. Mater.,2019

5. Machine learning and the physical sciences;Carleo;Rev. Modern Phys.,2019

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