Skip to main content
  • Hoopla logo
    Powered by Hoopla
  • Browse
  • My Hoopla
  • Log In
Books, videos, and music - all free from your public library!
LoginSign Up

Footer

Hoopla logo, Go to homepage
  • For Patrons
  • For Libraries (opens in new window)
  • For Vendors (opens in new window)
  • Facebook (opens in new window)
  • X (opens in new window)
  • Instagram (opens in new window)
  • YouTube (opens in new window)
  • TikTok (opens in new window)
  • LinkedIn (opens in new window)

Our Company

  • Our Story
  • Get Hoopla for your Library (opens in new window)
  • Get your content on hoopla (opens in new window)
  • Join our team (opens in new window)
  • Accessibility Statement

Our Content

  • Audiobooks
  • Ebooks
  • Movies
  • Television
  • Comics
  • BingePasses
  • Music
  • The Loop Blog

Help

  • Help Center
  • Submit Feedback
  • Facebook (opens in new window)
  • X (opens in new window)
  • Instagram (opens in new window)
  • YouTube (opens in new window)
  • TikTok (opens in new window)
  • LinkedIn (opens in new window)
  • Download on the App Store (opens in new window)
  • Get it on Google Play (opens in new window)
  • Available at Amazon Appstore (opens in new window)
© 2026 Midwest Tape, LLC. All rights reserved. Privacy Policy | Terms of Use
  1. Navigate Home
  2. Ebooks
  3. AI-Powered Innovation in Materials Science

EBOOK

AI-Powered Innovation in Materials Science

The Role of Language Models in Discovery and Design

Xue Jiang
(0)
sign up
Year
2026
Language
English
Publisher
Wiley

About

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.

Related Subjects

  • General (Materials Science)
  • Materials Science
  • Technology & Engineering
  • Adult Nonfiction
  • General (Artificial Intelligence)
  • Artificial Intelligence
  • Computers
  • Analytic
  • Chemistry
  • Science

Artists

Xue JiangAuthor
Yanjing SuAuthor