Given recent developments in artificial intelligence and materials design, computational tools are well positioned to realize an order of magnitude increase in available information throughput across multiple disciplines of materials science. This book is timely due to the increasing number of relevant updates in artificial intelligence and the desire for a data-information-knowledge-understanding-wisdom hierarchy using machine learning, neural networks, genetic evolutionary programming, fuzzy logic systems, and multi-objective optimization. This book helps to educate the inexperienced to well-informed scientist or engineer on computer intelligence for materials design.
Chapters 1–3 describe conventional approaches to materials design and data mining. Chapters 4–6 are full overviews of artificial shallow-to-deep neural networks, genetic programming, and fuzzy logic schemes. The relevance of these approaches is well grounded in desirable attributes to control and optimize material growth, composition, properties, and machining based on available data. At the conclusion of each chapter, applications, including figures and tables, are provided to assist the reader in understanding each method in the context of materials engineering and to form the foundation for later advanced chapters.
Building on the basis of computer intelligence, the final chapters extend the text to provide advice and insights on combining techniques in tandem. Each approach is well understood by this point in the book, and the author guides the reader to use and join each method effectively in order to realize optimization goals in materials processing and fabrication. Examples with up-to-date references to the literature include designing better shaped memory nitinol and polymer composites, where artificial neural networks or fuzzy models are implemented as objective functions within an evolutionary genetic or multi-optimization scheme.
At the conclusion, the author indicates that computer intelligence techniques are well positioned to be used for commercial and research purposes beyond the applications discussed throughout the text. Identified areas that stand to benefit from these computational tools include microstructure, microscopy, green design, and uncertainty analysis. This book is a vital resource that goes beyond standard textbook material for those working in materials design, metallurgy, processing, scientific computing, and related fields.
Reviewer: Jeffery Aguiar of the Idaho National Laboratory, USA.
