Large Language Models are transforming reticular chemistry by accelerating materials discovery through AI driven insights. These generative models assist scientists in extracting knowledge, designing materials, and analyzing experimental data, shifting research from traditional trial and error to data driven discovery cycles. By integrating chemistry aware AI into labs, including self driving robotic systems, LLMs streamline complex tasks and enhance collaboration. This advancement lowers barriers to AI adoption in chemistry, opening new frontiers in crystallization and materials science.
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