Enzymatic Cascade for Conversion of CO$_2$ to Methanol

  • Lera Shepard (King Abdullah University of Science and Technology (KAUST) (Creator)

Dataset

Description

Emissions of CO$_2$ largely contribute to global warming. Carbon dioxide can be captured and used to produce value-added chemicals. This thesis focuses on bioelectrocatalysis as a green and sustainable approach. Our aim was to perform conversion of CO$_2$ to methanol via a multi-enzymatic cascade. However, for reactions involving oxidoreductases, ß-NAD is required as a cofactor. Its use in stoichiometric amounts is unprofitable. We address the issue by employing electrochemical regeneration of the cofactor. For the cascade, we expressed and purified formate dehydrogenase, formaldehyde dehydrogenase and alcohol dehydrogenase. Enzymes activity was tested and found to be low for two enzymes. A reliable method to detect methanol via headspace gas chromatography with a flame ionization detector was developed. We tested the cascade with employed in situ electrochemical cofactor regeneration. After two and a half hours of the reaction 4 µmol methanol were detected. Further research is needed to optimize the setup.
Date made available2021
PublisherKAUST Research Repository

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