Reviewing the novel machine learning tools for materials design

Amir Mosavi, Timon Rabczuk, Annamária R. Varkonyi-Koczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

Computational materials design is a rapidly evolving field of challenges and opportunities aiming at development and application of multi-scale methods to simulate, predict and select innovative materials with high accuracy. Today the latest advancements in machine learning, deep learning, internet of things (IoT), big data, and intelligent optimization have highly revolutionized the computational methodologies used for materials design innovation. Such novelties in computation enable the development of problem-specific solvers with vast potential applications in industry and business. This paper reviews the state of the art of technological advancements that machine learning tools, in particular, have brought for materials design innovation. Further via presenting a case study the potential of such novel computational tools are discussed for the virtual design and simulation of innovative materials in modeling the fundamental properties and behavior of a wide range of multi-scale materials design problems.

Original languageEnglish
Title of host publicationRecent Advances in Technology Research and Education - Proceedings of the 16th International Conference on Global Research and Education Inter-Academia 2017
EditorsDumitru Luca, Lucel Sirghi, Claudiu Costin
PublisherSpringer Verlag
Pages50-58
Number of pages9
ISBN (Print)9783319674582
DOIs
Publication statusPublished - 2018
Event16th International Conference on Global Research and Education Inter-Academia, 2017 - Iasi, Romania
Duration: 2017 Sep 252017 Sep 28

Publication series

NameAdvances in Intelligent Systems and Computing
Volume660
ISSN (Print)2194-5357

Conference

Conference16th International Conference on Global Research and Education Inter-Academia, 2017
Country/TerritoryRomania
CityIasi
Period17/9/2517/9/28

Keywords

  • Machine learning
  • Materials design
  • Optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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