Large language models can accelerate reticular chemistry by guiding material design, data interpretation and discovery. This Perspective discusses how large language models integrate into laboratory workflows and modular artificial intelligence systems, streamlining data-driven research for new materials and tackling crystallization challenges.
- Zhiling Zheng
- Nakul Rampal
- Omar M. Yaghi
