Nakul Rampal

Kavli Energy NanoScience Institute, Blue Planet (Norway)

Papers

Total Citations

247

H-Index

About

Nakul Rampal is a pioneering researcher at the intersection of artificial intelligence and reticular chemistry, whose work is redefining how we discover and optimize advanced porous materials. His primary research areas span AI-driven materials discovery, large language models (LLMs) for scientific automation, and the design of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs). Rampal’s most impactful contribution is the development of a multi-AI-driven system that integrates ChatGPT and Bayesian optimization, supported by seven LLM-based assistants, to autonomously orchestrate laboratory research—a breakthrough that has garnered 145 citations for his 2023 paper. This work, along with his 2025 paper on LLMs for reticular chemistry (100 citations), demonstrates his leadership in applying generative AI to accelerate materials synthesis and characterization. He has also contributed a comprehensive review of reticular chemistry’s evolution, from early molecular hosts to MOF-5. With over 245 total citations and a rapidly growing influence, Rampal is a rising star whose fusion of machine learning and chemistry promises to transform how researchers design crystalline, porous frameworks for applications in gas storage, catalysis, and beyond.