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Modelling a detailed kinetic mechanism for electrocatalytic reduction of CO2

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For the first time a fully-elementary reversible kinetic model for electrocatalytic CO2 reduction towards a multitude of different products has been established and verified with experimental data. The detailed reaction mechanism was generated by compiling hypothesized reaction paths and intermediates from many different sources. Thereby a focus was put on distinguishing different embodiments of similar elementary steps: For proton-coupled electron transfer three hydrogenation mechanisms were considered and for intermediates with unclear molecular structure separate paths were modelled. The micro-kinetic model was fed with tabulated energy parameters and results of DFT calculations to simulate CO2 reduction on a Cu(100) surface for constant applied potentials. The operating conditions were chosen according to published experimental results in order to compare Faradaic Efficiencies. With these, the model parameters were successfully calibrated across a wide potential range while keeping all values within a tight interval of theoretical bounds derived from ab initio calculations and other theoretical considerations. The calibrated model was found to be in good qualitative agreement with the measurement data and also captures trends of surface coverages reported for in-situ measurements. Most interestingly, it finds the widely accepted hypothesis of dimerization via CO intermediates to be inaccurate. Instead, coupling reactions ofCHO and *CH2 intermediates are observed. The shifting of dimerization routes with varying applied potential – especially towards ethylene – is supported by other experimental studies. Furthermore, this work establishes a methodology of creating and calibrating complex electrochemical micro-kinetic models.



Micro-kinetic model, Reaction mechanism generation, CO2 reduction reaction, Electrolysis, Fuel synthesis

Journal Title

Proceedings of the Combustion Institute

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Elsevier BV
This research was supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. S. D. Rihm acknowledges financial support from Fitzwilliam College, Cambridge, and the Cambridge Trust. M. Kraft gratefully acknowledges the support of the Alexander von Humboldt Foundation.