On the Technologies of Artificial Intelligence and Machine Learning for 2D Materials

Nowadays, an important area of research in the field of two-dimensional (2 D ) materials and their surface characteristics is acceleration of the process of searching for synthesis parameters for new structures with unique properties. The achieved level of development of artificial intelligence and...

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Bibliographic Details
Published in:Surface investigation, x-ray, synchrotron and neutron techniques x-ray, synchrotron and neutron techniques, 2021-05, Vol.15 (3), p.485-494
Main Authors: Kirsanova, D. Yu, Soldatov, M. A., Gadzhimagomedova, Z. M., Pashkov, D. M., Chernov, A. V., Butakova, M. A., Soldatov, A. V.
Format: Article
Language:English
Subjects:
Artificial intelligence
Chemical synthesis
Chemistry and Materials Science
Computer design
Literature reviews
Machine learning
Materials Science
Nanomaterials
Problem solving
Surface properties
Surfaces and Interfaces
Thin Films
Two dimensional materials
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Summary:Nowadays, an important area of research in the field of two-dimensional (2 D ) materials and their surface characteristics is acceleration of the process of searching for synthesis parameters for new structures with unique properties. The achieved level of development of artificial intelligence and especially machine learning makes it possible to use these techniques to solve a wide range of problems, including in the field of 2 D -materials science. This article describes the current state of technologies of artificial intelligence and its subset, machine learning. The presented literature review describes the capabilities of machine-learning technologies for solving problems in the field of 2 D -nanomaterials both at the stages of computer design and chemical synthesis and diagnostics of the obtained 2 D -nanostructures and their surfaces. Much attention is given to the application of machine-learning technologies to find new 2 D materials with specified characteristics that can be successfully used in a number of promising areas of application.
ISSN:1027-4510
1819-7094
DOI:10.1134/S1027451021030113