Bayesian Optimization for Resource-Efficient Hydroformylation

Published:
December 8, 2025
|
Last Updated:
February 13, 2026

Atinary’s latest collaboration and publication with dsm-firmenich is now published in ACS Catalysis!

Two infographic panels highlight hydroformylation’s role in everyday products, medicines, cleaners, and fragrances. Images of pills, measuring cup, detergent scoop with bottle, and lily-of-the-valley with perfume illustrate messages about healing, cleaning performance, and scents shaping daily experiences.

Hydroformylation is a cornerstone industrial chemical reaction, used in medicines, fragrances, and specialty chemicals.

Two infographic panels on chemistry: left explains hydroformylation using rhodium catalysts, showing linear/branched products and notes efficiency, selectivity, scarcity, expense. Right presents Bayesian optimization to find optimal reactions, claiming 2.9 billion combinations solved with 88 experiments.

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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