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This book presents an overview of how AI is transforming materials science to meet the challenges of everyday life and across various technological domains. The author delves into various AI techniques such as machine learning, deep learning, and data-driven approaches, showcasing their application in materials discovery, characterization, and property prediction. As a reference, the book provides researchers and academicians established, state-of-the-science insights into the integration of AI with computational methods like molecular dynamics simulations, density functional theory calculations, and multiscale modelling, enhancing accuracy and efficiency in material research. In addition, the book highlights the successful applications of AI in optimizing material performance, accelerating materials development cycles, and enabling novel discoveries in the fields ranging from energy to environment materials. Artificial Intelligence in Computational Materials Science: Methods and Applications serves as a vital resource for researchers, engineers, and students interested in harnessing the potential of AI s for the advancement of materials science, innovating across industries, and addressing complex scientific challenges.
