Photocatalytic Flow Synthesis of Acetone from Methane Carbonylation Using Customized Flow Patterns

Although the direct synthesis of acetone via photocatalytic methane carbonylation is a sustainable process, achieving high yields and selectivity remains challenging. Here, we present a microchannel flow reactor screened using machine learning, which uses Au-NiO heterostructure-decorated ZnO catalysts with interfacial regulation to enable highly selective and active photocatalytic methane carbonylation, producing acetone. Spectroscopic characterization and theoretical simulations show that the acetyl intermediate is generated at the Au-NiO interface and evolves into acetone under moderate CH₄/CO coverage. The mass transfer of CH₄/CO to the catalyst surface is enhanced using custom-made micropillar channels via an increased gas-liquid interfacial area, forming a continuous thin liquid film. Consequently, the optimized catalyst with abundant Au-NiO interfaces achieves an acetone production rate of 50.9 μmol h^-1 with a selectivity of 87.6% in a customized photocatalytic flow reactor. This work provides new insights into combining atomic engineering and multiphase flow regulation for photocatalysis.