Artificial Intelligence-Based New Material Design

被引:0
|
作者
Babanli, M. B. [1 ]
机构
[1] Azerbaijan State Univ Oil & Ind, Azadlig Ave 20, AZ-1010 Baku, Azerbaijan
来源
10TH INTERNATIONAL CONFERENCE ON THEORY AND APPLICATION OF SOFT COMPUTING, COMPUTING WITH WORDS AND PERCEPTIONS - ICSCCW-2019 | 2020年 / 1095卷
关键词
Crystal structure; Material properties; Fuzzy logic; Deep learning; Big data; STRUCTURE-PROPERTY LINKAGES; YIELD STRENGTH; EXTRACTION;
D O I
10.1007/978-3-030-35249-3_2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:24 / 32
页数:9
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