Publications

Atinary’s ACS Catalysis study demonstrates major gains in hydroformylation, reducing rhodium use and costs with AI-driven optimization.

Atinary’s latest MFBO study in Nature Computational Science shows how mixing high- and low-fidelity experiments boosts R&D and cuts costs.

Atinary announces their latest research on Multi-fidelity Optimization (MFBO), a machine learning technique that optimizes several information sources with different fidelities.

🔬🚀 Our latest article, a collaboration between Atinary & IBM Research, was published in the May 2024 issue of Chemical Science from the Royal Society of Chemistry!

🔬🚀 Our latest article describes a framework and lay out the key technologies to accelerate R&D and optimize experiment planning.