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Metals
Volume 12
Issue 5
10.3390/met12050836
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Editorial

Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides

by
Alexey Mikhaylov
1,* and
Maria Luisa Grilli
2
1
Financial Faculty, Financial University under the Government of the Russian Federation, 124167 Moscow, Russia
2
Energy Technologies and Renewable Sources Department, Italian National Agency for New Technologies Energy and Sustainable Economic Development-ENEA, Casaccia Research Center, Via Anguillarese 301, 00123 Rome, Italy
*
Author to whom correspondence should be addressed.
Metals 2022, 12(5), 836; https://doi.org/10.3390/met12050836
Submission received: 29 April 2022 / Accepted: 6 May 2022 / Published: 13 May 2022
(This article belongs to the Special Issue Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal-Oxides)
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The development of nanotechnologies and new methods of machine learning are responsible for the significant attention and demand for metal oxides and multilayer metal-oxide nanostructures [...]

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MDPI and ACS Style

Mikhaylov, A.; Grilli, M.L. Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides. Metals 2022, 12, 836. https://doi.org/10.3390/met12050836

AMA Style

Mikhaylov A, Grilli ML. Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides. Metals. 2022; 12(5):836. https://doi.org/10.3390/met12050836

Chicago/Turabian Style

Mikhaylov, Alexey, and Maria Luisa Grilli. 2022. "Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides" Metals 12, no. 5: 836. https://doi.org/10.3390/met12050836

APA Style

Mikhaylov, A., & Grilli, M. L. (2022). Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides. Metals, 12(5), 836. https://doi.org/10.3390/met12050836

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