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.
Guest Editors: Heather Kulik and Yi-Qin Gao; Lead Editor: Xiaosong Li.
