AI in Material Science and Discovery: Unlocking the artificial intelligence potential through data-driven approaches

The rapid advancement of artificial intelligence (AI) and machine learning (ML) is transforming nearly every domain of science and engineering, and materials science is no exception. The intersection of AI with materials research marks a pivotal shift in how we discover, design, and understand new materials. Traditional trial-and-error approaches are being replaced or enhanced by data-driven methods capable of sifting through vast design spaces, identifying hidden patterns, and accelerating the development of next-generation materials. This book, AI in Material Science and Discovery, is a comprehensive guide designed to introduce students, researchers, and professionals to the tools, methods, and transformative potential of AI in the realm of material innovation.


Spanning foundational concepts to cutting-edge applications, this book offers a structured journey through the role of AI in materials data curation, property prediction, microstructure analysis, and autonomous experimentation. Each chapter bridges material science principles with AI methodologies, supported by real-world case studies and examples. As the field rapidly evolves, the goal of this book is not only to inform but also to inspire readers to contribute to this exciting interdisciplinary frontier. Whether you're a material scientist exploring AI or an AI practitioner entering materials science, this book serves as a timely and essential resource.