Statistically driven automated method for catalytic glucose conversion optimisation

RSC Advances

A statistically driven, automated approach to optimize glucose transformations to platform chemicals, methyl lactate and levulinic acid, is reported. The combination of a robotic synthesis platform with design of experiments methods enabled efficient and precise modelling of glucose conversion catalysed by SnCl4·5H2O with 0–100% H2O and methanol as a cosolvent. Using this strategy, optimal reaction conditions within the available reaction space were identified in 58 runs, showcasing the excellent efficiency of this method in producing high yields of methyl lactate (75.9%) and levulinic acid (64.5%) in independent reactions via distinct retro-aldol condensation and dehydration pathways, respectively.

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Joseph Install a, Rui Zhang a, Jukka Hietala b and Timo Repo a *

*Corresponding authors

a. Department of Chemistry, University of Helsinki, A. I. Virtasen aukio 1, P.O. Box 55, Finland

b. Neste Oyj, Technology Centre, Kilpilahti, P.O. Box 310, 06101 Porvoo, Finland

DOI: https://doi.org/10.1039/D4RA06038E

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