Bandgap Engineering in the Configurational Space of Solid Solutions via Machine Learning: (Mg,Zn)O Case Study-Reference-Cited by-同舟云学术

Bandgap Engineering in the Configurational Space of Solid Solutions via Machine Learning: (Mg,Zn)O Case Study

Author:

Midgley Scott D.¹,Hamad Said²^ORCID,Butler Keith T.³^ORCID,Grau-Crespo Ricardo¹^ORCID

Affiliation:

1. Department of Chemistry, University of Reading, Whiteknights, Reading RG6 6DX, United Kingdom

2. Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Ctra.de Utrera km.1, 41013 Seville, Spain

3. SciML, Scientific Computing Department, Rutherford Appleton Laboratory, Harwell OX11 0QX, United Kingdom

Funder

Engineering and Physical Sciences Research Council

Ministerio de Ciencia, Innovaci?n y Universidades

European Regional Development Fund

Agencia Estatal de Investigaci?n

Consejer?a de Conocimiento, Investigaci?n y Universidad of the Andalusian Government

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

Reference40 articles.

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