Large Language Models for Chemists: Applications and Insights [Hardcover]

1. Introduction  AIs Evolving Role in Chemistry? 2. How to Start with Data-Driven Chemistry?? 3. Foundations of AI and Tools for Chemists? 4. Large Language Models in Chemistry? 5. Literature and Knowledge Mining with LLMs? 6. Generative Models for Molecule and Materials Design? 7. LLMs and Automation? 8. Ethical Considerations and Future Perspectives

Large Language Models for Chemists breaks down that barrier by demystifying how LLMs work in an accessible way and showing, step-by-step, how they can be applied to solve real chemistry problems. Written in a friendly, tutorial style, the book assumes only a basic background in chemistry and minimal programming experience.?

Zhiling Zach Zheng is an Assistant Professor of Chemistry at Washington University in St. Louis, where he directs the Deep Synthesis Lab. His group combines artificial intelligence and automation to accelerate the discovery of porous materials for sustainability and human health. In addition to investigating fundamental aspects of metalorganic framework (MOF) synthesis and new structures, he explores how large language models can aid data mining, reaction and material design, and synthesis planning.

?Before joining WashU, Dr. Zheng was a BIDMaP Fellow at UC Berkeleys Department of Electrical Engineering and Computer Sciences from 2024 to 2025 and a postdoctoral researcher in the MIT Department of Chemical Engineering from 2023 to 2024 under the supervision of Professor Klavs Jensen. He earned his Ph.D. in Chemistry at the University of California, Berkeley, in 2023, working in Professor Omar Yaghis laboratory on MOFs for atmospheric water harvesting. He holds a B.A. in Chemistry, summa cum laude, from Cornell University (2019), where he worked with Professor Kyle Lancaster.

?Dr. Zhengs contributions have been recognized with the 2025 Carbon Future Young Investigator Award and the Inflection Award for AI-driven clÓ#