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Abstract

For a long time, design of new materials was implemented on the basis of costly and time-consuming experimental approach. Nowadays machine learning, data mining and Big Data techniques allow to develop a new approach, a so-called data-driven design of new materials. In this paper, we consider an approach to alloy discovery that is based on a synergy of deep learning and fuzzy logic methods. The approach allows to design materials with predefined characteristics by computer-aided generation of the underlying crystal structures and optimization of their parameters. An example is provided to illustrate the approach.

Keywords

Crystal structure Material properties Fuzzy logic \( \underline{\underline{\text{D}}} {\text{eep}}\; {\text{learning}} \) Big data 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Azerbaijan State University of Oil and IndustryBakuAzerbaijan

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