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Artificial intelligence (AI) rapidly transforms materials science by reshaping how materials are discovered and designed. Traditional approaches complement data methods that analyze vast experimental datasets with speed and accuracy. Through techniques like machine learning and generative modeling, AI enables the prediction of material properties and discovery of novel materials for energy and structural applications. As a result, the integration of AI into materials science reduces development time and cost while opening new paths toward sustainable and high-performance material systems. Applications of AI in Materials Science explores AI in materials engineering. It examines deep learning algorithms for materials science applications. Covering topics such as machine learning, nanotechnology, and biomaterials, this book is an excellent resource for academicians, researchers, software developers, engineers, and data scientists.