(Artificial Intelligence (AI): Elementary to Advanced Practices) 1st Edition
by Sudan Jha (Editor), Usman Tariq (Editor), Gyanendra Prasad Joshi (Editor), Vijender Kumar Solanki (Editor)
Artificial Intelligence-Aided Materials Design: AI-Algorithms and Case Studies on Alloys and Metallurgical Processes describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the included MATLAB and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference.
- Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats
- Helps readers develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code
- Provides downloadable resources such as MATLAB GUI/APP and Python implementation that can be used on common mobile devices
- Discusses the CALPHAD approach and ways to use data generated from it
- Features a chapter on metallurgical/materials concepts to help readers understand the case studies and thus proper implementation of AI/ML algorithms under the framework of data-driven materials science
This book is written for materials scientists and metallurgists interested in the application of AI, ML, and data science in the development of new materials.
