Artificial Intelligence-Aided Materials Design: Ai-Algorithms and Case Studies on Alloys and Metallurgical Processes

ISBN-13: 9780367765279 / Angielski / Twarda / 2022 / 334 str.

Rajesh Jha; Bimal Kumar Jha

Opis

This book describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials. It will appeal to readers who are both new to and experienced with the use of AI/ML algorithms in data-driven materials science.

Spis treści

1. Introduction. 2. Metallurgical/Materials Concepts. 3. Artificial Intelligence Algorithms. 4. Case Study 1: Nanomechanics and Nanotribology: Combined Machine Learning-Experimental Approach. 5. Case Study 2: Design of Hard Magnetic Alnico Alloys: Combined Machine Learning-Experimental Approach. 6. Case Study 3: Design of Soft Magnetic Finemet Type Alloys: Combined Machine Learning-CALPHAD Approach. 7. Case Study 4: Design of Nickel-Base Superalloys: Combined Machine Learning-CALPHAD Approach. 8. Case Study 5: Design of Aluminum Alloys: Combined Machine Learning-CALPHAD Approach. 9. Case Study 6: Design of Titanium Alloys for High-Temperature Application: Combined Machine Learning-CALPHAD Approach. 10. Case Study 7: Design of Titanium Based Biomaterials: Combined Machine Learning-CALPHAD Approach. 11. Case Study 8: Industrial Furnaces I: Application of Machine Learning on an Industrial Iron Making Blast Furnace Data. 12. Case Study 9: Industrial Furnaces II: Application of Machine Learning Algorithms on an Industrial LD Steel Making Furnace Data. 13. Software/Codes Included with this Book. 14. Conclusion.