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High-throughput multiscale characterization and artificial intelligence to develop new sustainable electrode materials for water electrolysis
Video introduction of the thesis
Goals
Improving the performance of alkaline electrolyzers through the development of high-performance heterostructured electrodes
Innovations
The traditional approach to improving electrocatalysts involves trial and error. Here, the innovative approach is to use semi-automated multi-scale characterization platforms to generate large amounts of data that will feed machine learning algorithms to accelerate the discovery of more active and sustainable materials for water electrolysis.
PhD student: Anton Voronkin
Promoter
Prof. Jon Ustarroz | Université Libre de Bruxelles |
Co-promoter
Prof. Nathalie Job | Université de Liège |
Research Center
Dr. Jean François Vanhumbeeck | Centre de Recherches Métallurgiques |
Tasks
T02-1 | Development of catalytic particles for integration into heterostructured catalytic coatings |
T02-2 | Elaboration of wet and dry heterostructured catalytic coatings |
T02-3 | High-throughput physico-chemical and functional characterization of synthesized coatings |
T02-4 | Artificial Intelligence algorithm development for semi-automatic processing of generated data |
Anton Voronkin presents his project during the Kick-off - September 13, 2024.
Poster PhD Day
Download the poster of the PhD Day which took place in Brussels on 12.09.2025.
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