Bayesian Optimization for Resource-Efficient Hydroformylation
Atinary’s ACS Catalysis study demonstrates major gains in hydroformylation, reducing rhodium use and costs with AI-driven optimization.
Atinary’s latest collaboration and publication with dsm-firmenich is now published in ACS Catalysis!
Hydroformylation is a cornerstone industrial chemical reaction, used in medicines, fragrances, and specialty chemicals.
Through this collaboration, the process chemists at dsm-firmenich used SDLabs and applied Atinary’s FalconGPBO algorithm and Bayesian Optimization to efficiently explore billions of possible reaction conditions, identifying optimal hydroformylation parameters in just 88 experiments.
Key Highlights
This work showcases the power of AI-driven R&D and Self-Driving Labs™ technologies to accelerate chemical research, improve process efficiency, and support sustainable innovation.
Congratulations to all authors!
Atinary: Anna Tan, Daniel Pacheco Gutierrez, Loic Roch; dsm-firmenich: Lionel Saudan, Laurent Maggi, Clelia Fantini, Eric Walther, Julien Coulomb, Francesco Santoro.
🗞️ For more details:
Read the full publication: https://doi.org/10.1021/acscatal.5c06595
Link to explore the use-case of this collaboration.
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