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Artificial intelligence-aided materials design: AI-algorithms and case studies on alloys and metallurgical processes

Rajesh Jha, Bimal Kumar Jha

2022enartificial intelligencematerials designmachine learningalloysmetallurgy

Abstract

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This book describes the application of artificial intelligence (AI) and machine learning (ML) concepts to develop predictive models that can be used to design alloy materials. The objective of this work is to provide readers, particularly those new to AI and ML algorithms, with foundational knowledge and practical insights. The methodology employed involves a comprehensive overview of AI and ML techniques alongside MATLAB and Python implementations. Through included case studies, the authors present practical applications of these algorithms to metallurgical processes and the design of alloys. The results demonstrate the effectiveness of AI/ML strategies in optimizing materials properties and enhancing the design process, providing a valuable resource for academics and practitioners alike. This work aims to bridge the gap between theoretical foundations and practical applications in the field of materials engineering.

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Cite This Work

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  title={Artificial intelligence-aided materials design: AI-algorithms and case studies on alloys and metallurgical processes},
  author={Rajesh Jha and Bimal Kumar Jha},
  year={2022},
  language={en}
}
TY  - JOUR
TI  - Artificial intelligence-aided materials design: AI-algorithms and case studies on alloys and metallurgical processes
AU  - Rajesh Jha
AU  - Bimal Kumar Jha
PY  - 2022
LA  - en
ER  -

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