Bandgap Engineering in the Configurational Space of Solid Solutions via Machine Learning: (Mg,Zn)O Case Study.
Saved in:
| Title: | Bandgap Engineering in the Configurational Space of Solid Solutions via Machine Learning: (Mg,Zn)O Case Study. |
|---|---|
| Authors: | Midgley SD; Department of Chemistry, University of Reading, Whiteknights, Reading RG6 6DX, United Kingdom., Hamad S; Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Ctra.de Utrera km.1, 41013 Seville, Spain., Butler KT; SciML, Scientific Computing Department, Rutherford Appleton Laboratory, Harwell OX11 0QX, United Kingdom., Grau-Crespo R; Department of Chemistry, University of Reading, Whiteknights, Reading RG6 6DX, United Kingdom. |
| Source: | The journal of physical chemistry letters [J Phys Chem Lett] 2021 Jun 03; Vol. 12 (21), pp. 5163-5168. Date of Electronic Publication: 2021 May 25. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 101526034 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1948-7185 (Electronic) Linking ISSN: 19487185 NLM ISO Abbreviation: J Phys Chem Lett Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1948-7185 |
|---|---|
| DOI: | 10.1021/acs.jpclett.1c01031 |
