Mehta, Kallum Hiten; (2025) Optimisation of Selective Oxidation Reactions Using Thermal and Electrochemical Flow Catalysis. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

The development of sustainable oxidation processes is crucial for greener chemical synthesis. This thesis explores the optimisation of selective oxidation reactions using heterogeneous flow catalysis, with a focus on aqueous-phase reactions and the integration of electrochemical H₂O₂ production. A key aspect of this work is the application of a novel machine learning (ML) framework, employing an autoencoder to facilitate target prediction and a visualisation-based sampling strategy to improve reaction optimisation efficiency. Initially, the synthesis and characterisation of Titanium Silicalite-1 (TS-1), a widely used catalyst for selective oxidation was explored. A suite of in-situ and ex-situ techniques were used to correlate chemical properties with catalytic performance. Then the aqueous-phase epoxidation of allyl alcohol was conducted using a typical batch process to identify beneficial conditions for catalytic conversion. Subsequently, a flow reactor setup was established to determine catalyst activity and selectivity for epoxide using a range of conditions and this information was used to optimise the reaction yield through a Machine Learning (ML) strategy. This workflow allowed us to improve the reaction yield by two orders of magnitude compared to the batch process. Further extension of this approach for the oxidation of furfural was carried out, highlighting how reaction parameters can influence product distribution for more complex reaction schemes. Finally, a reactor design for integrating in-situ electrochemical H₂O₂ generation with selective oxidation reactions was presented. A dual-membrane reactor was developed to enable efficient peroxide production through the oxygen reduction reaction, and simultaneous utilisation in selective oxidation reactions. This sought to reduce external oxidant requirements, and initial attempts at achieving this integration were presented. Collectively, this work advances the field of flow catalysis by demonstrating how the reactor mode, ML-aided optimisation and electrochemical in-situ peroxide production can improve the sustainability and efficiency of selective oxidation reactions.

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