Dr Francisco Martin-Martinez is a Senior Lecturer in Natural Sciences and Computational Chemistry in the Department of Chemistry, and an affiliate member of the King’s Institute for AI.

Fran began his academic journey at University of Granada, where he studied Chemical Engineering and earned a PhD in Theoretical and Computational Chemistry. Following his PhD, he held a postdoctoral position at the Vrije Universiteit Brussel, before moving to the Massachusetts Institute of Technology (MIT), where he worked as a Research Scientist for almost 6 years. In 2020, he joined Swansea University as lecturer in Chemistry, before transitioning to King’s College London in 2024. He is also a member of the Thomas Young Centre, and honorary research fellow at Swansea University.

At King’s, Fran leads the MMLab, a multidisciplinary research group focused on nature-learned matter. The lab leverages computational chemistry, machine learning, and biomimicry to engineer sustainable materials inspired by natural systems, with a particular emphasis on understanding materials degradation pathways to enhance performance and durability. Research efforts focus on utilizing biomass – including lignin, cellulose, and chitin – and biobased feedstocks, such as biocrude oils and biochar, to construct materials with tailored properties for applications in self-healing infrastructure, precision agriculture, and energy storage.

In 2022, Fran was selected as a Google Cloud Research Innovator to work with Google Cloud on simulating self-healing biobased materials.

In addition to his primary academic roles, Fran enjoys working with start-ups and social enterprises to advance socially directed science and technology. He is Affiliate Member of the Royal Society of Chemistry, the Spanish Federation of Chemical Engineers, the American Chemical Society, and the Spanish Royal Academy of Chemistry.

Research Interests

• Computational chemistry and multiscale modelling
• Nature-inspired materials and biomimicry
• Biomass and biobased materials
• Precision agriculture and soil remediation
• Self-healing infrastructure materials

Teaching

• Advanced Topics in Physical and Computational Chemistry
• Natural Sciences Experimental Skills
• Research Methods Literature Reviews
• MSCi Research Project & Dissertation
• MRES Research Project in Interdisciplinary Chemistry

Research profile

For more information on Dr Martin-Martinez's research please see his Research Portal page

The Martin-Martinez Group

The Martin-Martinez Group integrates computational chemistry, machine learning, and biomimicry to engineer sustainable materials inspired by natural systems, with a particular emphasis on understanding materials degradation mechanisms to enhance performance and durability. Learning Nature’s intelligence to engineer materials for circularity as well as functionality, they utilise biomass – including lignin, cellulose, and chitin – and biobased feedstocks, such as biocrude oils and biochar, to construct materials with tailored properties for applications in self-healing infrastructure, precision agriculture, and energy storage. They employ a variety of tools such as Density Functional Theory (DFT), Molecular Dynamics (MD) simulations, and Coarse-Grained (CG) modelling to simulate the behaviour of molecules and materials across scales, from the nanoscale to the mesoscale. They simulate a range of phenomena, including chemical reactivity, electron transport, mechanical properties, self-assembly and degradation mechanisms. The extensive datasets generated from their computational work serve as valuable resources for training machine learning (ML) models that expedite the prediction of properties and facilitate the discovery of more sustainable molecules and materials.

Visit the Martin-Martinez Group website to find out more.