The Advances in Computational Intelligence in Materials Science (ACIMS) book series applies a range of computational methods, such as artificial intelligence (AI), machine learning, evolutionary algorithms, and other computational techniques, to address significant challenges in materials science. By focusing on the intricate relationship between industry and academia, the series explores various aspects including development issues, challenges, innovations, and knowledge exchange. This interdisciplinary approach aims to foster collaboration, facilitate technology transfer, and promote advancements in materials science research and development.

The series covers, but is not limited to the following topics:

• • Simulation and modelling in Sustainable Manufacturing
• • Data, Information and Knowledge Management in Sustainable Manufacturing
• • Computational Intelligence Methods and Application
• • Intelligent web mining and applications
• • Sustainable development of manufacturing enterprises
• • Sustainability Assessment in Production
• • Existing macro-level approaches for quantifying eco-innovation
• • Product design and manufacture for societal impact
• • Environmentally conscious design/manufacturing processes
• • Big data machine learning and Industry 4.0 applications
• • Intelligent quality tools and Potential failure analysis
• • Production planning, control and Performance evaluation
• • Soft computing analysis applied to industry
• • Materials Science and Metallurgy
• • Materials Processing, Characterization and Forming
• • Simulation, modelling and control of smart materials
• • Carbon Based Materials, Engineering and Structural Materials
• • Biomaterials and Materials for Optics
• • Ceramics, Composites, Glass and Polymers Technology
• • Smart Material and CAD/CAM/CAE/CIM
• • Catalysis for Petroleum, Polymer and Chemical Processing Sector
• • Future Advancements