Research

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Challenges to sustainable development. We tackle challenges to sustainable development goals, related to climate action, energy harvesting and storage, resilient infrastructure, and precision agriculture.

Collaborative researchWe work with top research groups and industry partners across Swansea, UK, and worldwide, e.g., USA, Chile, Nigeria, Belgium, Italy, and Spain.

 

Societal considerationsSocial inquiry, inclusion, and equity is essential to progress, and therefore to the sustainable development goals. We work for a social-driven innovation and socially-directed science and technology .

Design for reuse as well as performance. We bridge quantum chemistry and chemical engineering to develop nature-inspired biobased materials for a circular economy. We apply density functional theory (DFT), molecular dynamics (MD) simulations, coarse grain (CG) modeling and machine learning (ML) algorithms, to design for reuse as well as performance, integrating biomass waste, biomaterials and nanomaterials. Some examples of materials considered include lignin, nanocellulose, chitin, silk, biocrude oils, carbon quantum dots, and graphene.

Computational Chemistry, DFT
We perform DFT electronic structure calculations of molecules and solids. We apply conceptual DFT reactivity descriptors (Fukui function, chemical hardness), as well as spin density and molecular electrostatic calculations to study reaction mechanisms.
Molecular dynamics
We develop multiscale computational models for biomass-derived materials (nanocellulose, nanochitin, lignin).
Machine Learning in Chemistry
We are starting to apply deep learning algorithms to predict chemical properties without solving quantum mechanics calculations
Carbon nanostructured materials
We apply Clar's sextet Theory to predict the aromaticity distribution of polycyclic aromatic systems: graphene, nanoribbons, asphaltenes. We apply these insights to design biobased nanostructured carbon materials
Biomass and biobased materials
We study the polymerization and depolymerization mechanisms of lignin and other biomass materials, to provide fundamental knowledge that help the development of biorefineries
Bioinspired circular materials
We design bioinspired materials for reuse as well as performance. We simulate reversible chemistry pathways to design materials for a circular economy
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© 2020 by Francisco Martin-Martinez | Swansea, UK | f.j.martin-martinez@swansea.ac.uk

Machine Learning in Chemistry

We are starting to apply deep learning algorithms to predict chemical properties without solving quantum mechanics calculations