AI-Powered Innovation in Materials Science
eBook - ePub

AI-Powered Innovation in Materials Science

The Role of Language Models in Discovery and Design

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

AI-Powered Innovation in Materials Science

The Role of Language Models in Discovery and Design

About this book

Accelerate materials innovation using language models and machine learning methods

Language models and machine learning are transforming how researchers discover, design, and optimize advanced materials. AI-Powered Innovation in Materials Science: The Role of Language Models in Discovery and Design provides a systematic exploration of these methods, from data mining and predictive modeling to autonomous experimentation. Written by award-winning researchers from the University of Science and Technology Beijing, this reference connects foundational AI theory with practical implementations.

The book covers the evolution of language models in materials science, demonstrating methodologies through real-world case studies in energy, sustainability, and advanced manufacturing applications. Readers gain actionable insights into predicting material properties before experimental validation, optimizing synthesis pathways, and uncovering hidden correlations in materials data. The authors critically analyze current challenges while mapping future directions for materials intelligence research.

You'll also discover:

  • Methodologies for integrating AI throughout the materials research pipeline from initial data mining through autonomous experimentation and discovery workflows
  • Practical case studies demonstrating how language models accelerate innovation in renewable energy, aerospace, and high-performance electronics applications
  • Frameworks for predictive modeling that minimize costly trial-and-error processes while optimizing synthesis pathways for scalable material production
  • Strategies for translating laboratory breakthroughs into practical manufacturing solutions through end-to-end lifecycle management and sustainability considerations
  • Critical analysis of current limitations and a comprehensive roadmap for developing next-generation materials intelligence capabilities and research directions

Materials scientists, theoretical chemists, computational scientists, and computer scientists working at the intersection of AI and materials research will find this book invaluable. It provides the theoretical foundations and practical methodologies needed to accelerate materials development for grand challenges in energy, sustainability, and advanced manufacturing.

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Information

Publisher
Wiley-VCH
Year
2026
Print ISBN
9783527356355
Edition
1
eBook ISBN
9783527855827

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. Preface
  6. Chapter 1: The Revolution of AI for Materials
  7. Chapter 2: Fundamentals of Language Models and NLP
  8. Chapter 3: Reinforcement Learning in Materials
  9. Chapter 4: Materials Word Embedding Models
  10. Chapter 5: Materials Transformer-based Models
  11. Chapter 6: Materials Data Extraction from Literature by NLP and Large Language Models
  12. Chapter 7: Case Studies of Chemical Information Extraction
  13. Chapter 8: Case Studies of Alloy Information Extraction
  14. Chapter 9: Case Studies of Materials Synthesis Information Extraction
  15. Chapter 10: Materials Predictive Modeling with Language-augmented Approaches
  16. Chapter 11: Case Studies of Materials Predictive Modeling
  17. Chapter 12: Retrieval-augmented Generation for Materials Large Language Models
  18. Chapter 13: Fine-tuning and Application for Materials Large Language Models
  19. Chapter 14: Materials Agents for Autonomous Research
  20. Chapter 15: Case Studies of Materials Agents
  21. Chapter 16: Challenges and Future Developments
  22. Index
  23. End User License Agreement

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Yes, you can access AI-Powered Innovation in Materials Science by Xue Jiang,Yanjing Su in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.