Fran's research interested lies at the interphase between computational chemistry, and biomimicry. The MMlab focuses on developing Nature-inspired molecules and materials, with applications in energy harvesting and storage, self-healing infrastructure, and precision agriculture. His group applies Density Functional Theory (DFT), Molecular Dynamics (MD) simulations, and Coarse-Grained (CG) modelling to simulate the behaviour of molecules and materials from the nanoscale to the mesoscale, simulating chemical reactivity, electron transport, mechanical properties, self-assembly and degradation mechanisms. The large datasets generated are used for training Machine Learning (ML) algorithms that speed up property predictions, and molecular discovery.

Dr. Francisco Martin-Martinez is a Senior Lecturer in Natural Sciences, and Computational Chemistry in the Department of Chemistry at King’s College London. Fran began his academic journey at the University of Granada in Spain, where he studied Chemical Engineering and earned a PhD in Theoretical and Computational Chemistry. Following his PhD, he held a postdoctoral position with the Quantum Chemistry Group at the Vrije Universiteit Brussel. He then moved to the Massachusetts Institute of Technology (MIT), where he worked as a Research Scientist under Prof. Markus Buehler for almost 6 years before starting a lecturer position at the Chemistry Department of Swansea University in 2020. In 2024, Fran transitioned to King’s College London, where he leads the MMLab on nature-learned matter. In 2022, he was selected as a Google Cloud Research Innovator, because of his work on predicting chemical reactivity using cloud supercomputing and machine learning. In addition to his primary academic roles, Fran is a co-instructor at Station1, a start-up focused on socially driven innovation based in the USA.