About this book series
This book series is dedicated to showcasing the latest research and developments at the intersection of materials science and engineering, computational intelligence, and data sciences. The series covers a wide range of topics that explore the application of artificial intelligence (AI), machine learning (ML), deep learning (DL), reinforcement learning (RL), and data science approaches to solve complex problems across the materials research domain.
Topical areas covered in the series include but are not limited to:
· AI and ML for accelerated materials discovery, design, and optimization
· Materials informatics
· Materials genomics
· Data-driven multi-scale materials modeling and simulation
· Physics-informed machine learning for materials
· High-throughput materials synthesis and characterization
· Cognitive computing for materials research
The series also welcomes manuscript submissions exploring the application of AI, ML, and data science techniques to following areas:
· Materials processing optimization
· Materials degradation and failure
· Additive manufacturing and 3D printing
· Image analysis and signal processing
Each book in the series is written by experts in the field and provides a valuable resource for understanding the current state of the field and the direction in which it is headed. Books in this series are aimed at researchers, engineers, and academics in the field of materials science and engineering, as well as anyone interested in the impact of AI on the field.
- Electronic ISSN
- 2948-1821
- Print ISSN
- 2948-1813
- Series Editor
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- N M Anoop Krishnan
