DigiCat develops materials and process design methodologies based on multiscale and AI-powered models, covering the full research pipeline from data to process and product.

We combine catalysis & materials science, process systems engineering, and artificial intelligence to accelerate the discovery, understanding and optimization of catalysts and catalytic processes. We aim to move beyond traditional trial-and-error approaches by developing digital tools that support catalyst and process design across different scales. Through this approach, we contribute to more efficient, selective and sustainable catalytic technologies for energy, environmental and chemical applications.

Our AI-powered research has been recognized, including Diogo's MSc thesis E-REDES Open Data Challenge 2025 and Daniel's Best Young Presentation Award at EuropaCat 2025. We are also actively contributing to the international chemical engineering community’s efforts in artificial intelligence, with Pedro's proeminent roles in EFCATS, EFCE and ACS Engineering Au, and through the organization of the 1st AI for Catalysis Summer School (by Pedro, Bárbara, Daniel and Arij).

Digital Catalysis

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Digital Catalysis

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