Producing a fuel simply from water and sunlight can seem like a dream, but it’s actually possible. Unfortunately, practical applications are hampered by our limited understanding of the photochemical processes. This team will rely on a regional computational centre located in Rwanda, supported by EPFL, to simulate the dynamics of the chemical processes with accuracy; an efficient way to study this complex reaction and make the dream a reality!
Keywords: Green energy, Photocatalysis, Quantum simulations
Steve Ndengué
Steve Ndengué is a Senior Lecturer in the Condensed Matter Physics section of the East African Institute for Fundamental Research.
Nicola Marzari
Nicola Marzari holds the Chair of Theory and Simulation of Materials at the EPFL, where he is also the director of the MARVEL National Centre
Research project
Photocatalytic water splitting has the potential to generate clean and sustainable energy. The efforts of finding optimal catalysts are nevertheless hampered by our limited understanding of the electronic processes of absorption, diffusion and recombination, where the photoexcited electrons and holes drive the redox reactions.
In this project we will develop a novel approach to study the dynamics of the photodissociation, embedding the quantum dynamics of individual molecules in a multi-scale treatment of the surrounding environment. This will allow us to simulate the dynamics of the process with accuracy, as well as capture the complexity of the interfaces. This approach can then be extended to many other photochemical processes. The project will involve researchers at the newly created ICTP-East African Institute for Fundamental Research in Kigali, Rwanda, and at EPFL in Lausanne, Switzerland. In the course of the project, five junior scientists and the two senior investigators will jump-start a long-term collaboration in a field of great scientific relevance and economic potential.
Publications / Science news
The project was presented at the 7th African School for Electronic Structure Methods and Applications (ASESMA 2023).
Junior Faculty development projects
Machine Learning for IoT
Parkinson’s disease cure
Reactive, sponge-like materials
Hybrid Solar-energy
