AI-Driven Polymer Design
Description
This book highlights how artificial intelligence (AI) is transforming the design, analysis, and application of polymers in modern science and industry. AI technologies, including machine learning (ML) and deep learning, have revolutionized the discovery, prediction, and optimization of polymers, enabling the rapid development of materials with specific properties suited for various applications such as healthcare, energy, and electronics. It covers the role of AI in understanding the relationship between the molecular structure of polymers and their physical, chemical, and mechanical properties. By integrating advanced AI models, the book demonstrates how new polymeric materials can be designed more efficiently, with tailored properties for targeted applications. It offers both theoretical and practical insights into AI algorithms, predictive modeling, polymer property analysis, and case studies.
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Persons
Dr. Bhasha Sharma is currently working as a visiting faculty at University of Delhi, India. She obtained her Ph.D. in Chemistry from the University of Delhi. Her research interests revolve around sustainable polymers for packaging applications, environmental benign approaches for biodegradation of plastic wastes, fabrication of bionanocomposites, and finding strategies to ameliorate the electrochemical activity of biopolymers.
Dr. Vijay Chaudhary is currently working as an Assistant Professor in the Department of Mechanical Engineering at Amity University Uttar Pradesh, Noida. He obtained his Ph.D. in Mechanical Engineering from the Netaji Subhas University of Technology, University of Delhi. His research area of interest lies in Processing and characterization of Polymer composites, Tribological analysis of fiber-based polymer composites, water absorption of fiber-based polymer composites, and surface modification techniques related to polymer composite materials .
Dr. Chanchal Ahlawat is an assistant professor at Bennet University, Greater Noida. She obtained her PhD from Jaypee Institute of Information and Technology, Noida. Her research interest areas are Internet of Things, Fog Computing, Machine Learning and Deep Learning.
Prof. Njuguna's research is focused on experimental research on composite materials reinforcement, toughness, materials design and selection; and structural-property relationship. Structural composites research is focused on new products design and industrial applications such as engineering design, evaluation of composites integrity and durability evaluation primary structural applications in extreme harsh conditions such as high temperature, high pressure, shock and impact resistance. Research on integrated energy focus on system integration for energy mix, hydrogen storage systems, knowledge transfer, technology road mapping and maximising energy assets lifespan. A side stream of his research is a focus on AI for materials, exploiting materials failure behaviour to investigate emission/diffusion/release of nanofillers from polymer fibre-reinforced nanocomposites which contributes to research on their durability and on furthering Nano Safety of nanomaterials to human and environmental health.
Content
Introduction to AI in Polymer Design.- Structure-Property Relationships in Polymers.- Machine Learning for Polymer Property Prediction.- AI-Driven Optimization of Polymer Structure.- Computational Tools for AI in Polymer Science.- Real-World Applications of AI-Designed Polymers.- Challenges in AI-Driven Polymer Design.- Future Trends in AI and Polymer Science.
