VSParticle (VSP), based in Delft, is collaborating with Meta’s Fundamental AI Research (FAIR) team and the University of Toronto (UofT) to innovate clean energy solutions.

This partnership combines VSP's advanced nanoporous layer printing technology, UofT's robust testing capabilities, and Meta AI's sophisticated models to develop and test new materials.

VSP is enhancing its nanoprinters to significantly increase production efficiency, aiming to boost output from 300 to 20,000 sparks per second.

This upgrade will accelerate the synthesis and validation of nanomaterials, enabling researchers to quickly confirm AI predictions and discover low-cost electrocatalysts.

To improve material discovery, AI models require training on large datasets of tested materials, ideally tens or hundreds of thousands, a capacity that VSP currently meets.

Electrocatalysts play a crucial role in decarbonizing industries, particularly in processes like carbon dioxide reduction reactions and hydrogen production.

Using spark ablation technology, VSP’s nanoprinter has already produced 525 materials identified as promising candidates for CO2 reduction.

The findings from the project have contributed to an experimental database that allows researchers to validate AI predictions with real-world data.

Larry Zitnick, Research Director at Meta AI, emphasized that this collaboration represents a significant advance in material discovery, which is essential for clean energy solutions.

Aaike van Vugt, co-founder and CEO of VSP, noted that the partnership aims to expedite the timeline from discovery to application for advanced materials necessary for clean energy.

VSP's technology is already being utilized globally, with their flagship VSP-P1 Nanoprinter contributing to advancements in gas sensors and catalyst-coated membranes for green hydrogen.

This announcement follows VSP's successful €6.5 million funding round, which will support their ongoing efforts in material development to tackle the climate crisis.