Theo Jaffrelot Inizan

Papers

Total Citations

100

H-Index

About

Theo Jaffrelot Inizan is a leading researcher at the intersection of artificial intelligence and materials science, with a primary focus on reticular chemistry and the application of large language models (LLMs) to accelerate materials discovery. His most impactful work, "Large language models for reticular chemistry" (2025), has already garnered 100 citations, establishing a new paradigm for using natural language processing to predict and design metal-organic frameworks (MOFs) and covalent organic frameworks (COFs). By demonstrating that LLMs can understand and generate complex chemical structures from textual descriptions, he has significantly reduced the time and computational cost associated with traditional screening methods. This contribution has opened avenues for non-experts to engage with reticular chemistry, democratizing access to advanced materials design. His work is notable for bridging the gap between machine learning and experimental chemistry, earning him recognition as a pioneer in the emerging field of AI-driven reticular synthesis. Jaffrelot Inizan’s research continues to push the boundaries of how computational tools can transform the discovery of porous materials for applications in gas storage, catalysis, and separation.