Artificial Intelligence-Aided Materials Design

AI-Algorithms and Case Studies on Alloys and Metallurgical Processes

Rajesh Jha, Bimal Kumar Jha

• Publisher: CRC Press
• Year: 2022
• ISBN:
  9781000541380
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Materials Science
• Index: Technology & Engineering

This bookdescribes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft 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 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 to develop predictive models through AI/ML algorithms by writing their own computer code or using resources where they do not have to write code

• 
  
  

• Coversdownloadable 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

• 
  
  

• Uses case studies to examine the importance of using unsupervised machine learning algorithms in determining patterns in datasets

• 
  
  

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.