AIP Publishing LLC
AIP Publishing LLC
  • pubs.aip.org
  • AIP
  • AIP China
  • University Science Books
  • Resources
    • Researchers
    • Librarians
    • Publishing Partners
    • Topical Portfolios
    • Commercial Partners
  • Publications

    Find the Right Journal

    Explore the AIP Publishing collection by title, topic, impact, citations, and more.
    Browse Journals

    Latest Content

    Read about the newest discoveries and developments in the physical sciences.
    See What's New

    Publications

    • Journals
    • Books
    • Physics Today
    • AIP Conference Proceedings
    • Scilight
    • Find the Right Journal
    • Latest Content
  • About
    • About Us
    • News and Announcements
    • Careers
    • Events
    • Leadership
    • Contact
  • pubs.aip.org
  • AIP
  • AIP China
  • University Science Books
  • Journals
  • Upcoming Special Topics
  • Chemical Physics Reviews
  • AI and Machine Learning in Chemical and Materials Science

AI and Machine Learning in Chemical and Materials Science

Submission Deadline: January 31, 2025

Artificial intelligence (AI) and machine learning (ML), with their rapidly evolving capabilities, stand at the forefront of a paradigm shift in chemical and materials research. These data science techniques are ushering in an era where data-driven methodologies can significantly augment traditional experimental and computational procedures, leading to unprecedented scientific discovery in these fields. Recognizing the potential of these technologies and the need for a focused discussion on their advancements, this special topic issue aims to spotlight the most recent progress in AI/ML-assisted research in chemical and materials science with a focus on physical insights that can be gleaned from either application or development of AI/ML models. This issue seeks to provide a comprehensive overview, including the latest innovations, challenges, and future prospects of AI/ML in chemical and materials research.

Topics covered include, but are not limited to:

  • New AI/ML tools to facilitate chemistry and materials discovery
    AI/ML-aided design of catalysts, chemical reactions, and functional materials
    AI/ML in sustainable and green chemistry and materials research
  • AI/ML in solving complex quantum chemistry problems and in the analysis of complex spectroscopic data
  • AI/ML in quantum information science

Guest Editors

Heather Kulik, MIT

Yi-Qin Gao, Peking University

 

Chemical Physics Reviews Editors

Xiaosong Li, University of Washington,

Submission Deadline: January 31, 2025
  • Featured
  • APL Computational Physics: Now Open for Submissions
  • APL Engineering Physics: Coming Soon
  • APL Electronic Devices: First Articles Now Online
  • International Journal of Fluid Engineering: Now Open for Submissions
  • MechanoEngineering: Coming Soon
  • Call for Applications
  • Upcoming Special Topics
  • Submit Your Article
  • Visit AIP Author Services
  • Sign Up for News

Keep Up With AIP Publishing

Sign up for the AIP newsletter to receive the latest news and information from AIP Publishing.
Sign Up

AIP PUBLISHING

1305 Walt Whitman Road,
Suite 110
Melville, NY 11747
(516) 576-2200

Resources

  • Researchers
  • Librarians
  • Publishing Partners
  • Commercial Partners

About

  • About Us
  • CareersĀ 
  • Leadership

Support

  • Contact Us
  • Terms Of Use
  • Privacy Policy

© 2025 AIP Publishing LLC
  • 𝕏