AI – Driven Polymer Design | 6.85 MB
Title: AI-Driven Polymer Design
Author: Bhasha Sharma · Vijay Chaudhary · Chanchal Ahlawat · James Njuguna
Category: Nonfiction, Science & Nature, Science, Physics, Solid State Physics, Technology, Material Science, Computers, Advanced Computing, Artificial Intelligence
Language: English | 235 Pages | ISBN: 9789819583539
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.
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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