Glycerol oxidation reaction with high throughput and bayesian optimisation
Sushila Marlow a, Camille Petit a, Magda Titirici a, Shiochi Matsuda b, Ryo Tamura b, Jingyu Feng a, Hanzhi Ye a, Enrico Manfredi-Haylock a, Helen Tyrrell a
a Department of Chemical Engineering Imperial College London, South Kensington, Londres SW7 2AZ, Reino Unido, United Kingdom
b NIMS, Japan
Proceedings of MATSUS Spring 2026 Conference (MATSUSSpring26)
I4 Digital Discovery: From Energy Materials to Devices
Barcelona, Spain, 2026 March 23rd - 27th
Organizers: Shoichi Matsuda and Magda Titirici
Oral, Sushila Marlow, presentation 746
Publication date: 15th December 2025

Many industrial chemicals are currently derived from non-renewable petroleum feedstocks, but electrochemical conversion of renewable biomass waste offers a more sustainable alternative. We have developed a high-throughput, automated electrolyser system designed to optimize the electrocatalytic production of lactic acid from glycerol at the anode, while simultaneously generating clean hydrogen at the cathode. The custom-built system can autonomously run up to 16 reactions, systematically varying key parameters of temperature, applied current, electrolyte flow rate, and concentration. Reaction products are analysed using a 96-vial HPLC autosampler, integrated with a data analysis program to quantify product yields. These results are fed into a Bayesian optimization algorithm (PHYSBO), which employs a Gaussian process to predict and select the next set of experimental conditions.1 The chosen conditions are automatically updated into the experimental run program, initiating the next round of testing. This self-driving electrocatalysis platform tailors reaction conditions to each catalyst, ensuring optimal performance and a foundation for material comparison.

Thanks to the Titirici and Petit Research Groups at Imperial College London, and our collaborators abroad. 

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