Coupling covariance matrix adaptation with continuum modeling for determination of kinetic parameters associated with electrochemical CO2 reduction

•Characterization methods for CO2R catalysts that neglect mass transfer are inaccurate•CMA-ES coupled with continuum modeling rigorously parameterizes literature data•Fit parameters broadly distributed, suggesting differences in catalyst structure•Presented method is applicable to any electrochemical system affected by Electrochemical synthesis processes (e.g., the reduction of carbon dioxide [CO2R]) possess immense potential electrify manufacturing chemicals and fuels. Key rationalizing optimizing performance these systems characterization electrocatalysts. However, extraction intrinsic kinetic behavior from experimental data convoluted poor reagents. Hence, common benchmarking result misreporting behavior. To address this issue, methodology presented here employs advanced optimization strategies informed deconvolute non-kinetic effects benchmark CO2R. The developed where relevant, such as ammonia or organic electrosynthesis, making it a powerful tool development electrocatalysts synthesis. In electrocatalysis, rate reaction function applied governed Tafel equation, which depends on two parameters: slope exchange current density (i0). determine involve subjective removal due competitive surface bulk reactions, resulting unquantifiable uncertainty. overcome challenge, we couple covariance matrix adaptation model CO2 (CO2R) explicitly deconvolutes extract associated 26 datasets over Ag Sn catalysts. fitted do not converge unique set values, i0 an apparent correlation, suggest consequence variations preparation methods. This work facilitates rigorous relevant. (CO2) emitted point sources cement production, separation natural gas, iron aluminum ore smelting, fermentation sugars) using electricity renewable resources wind solar) offers means recapturing its content. 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By means, (αi,c ii,0) determined (Note S2). procedure enables assessment degree between outputs input much output parameter when changed). positively sensitive input, results output; negatively decrease output. highly LBL) availability electrolyte; however, less because solvent water, assumed proton source evolution (HER) (Figures S3–S5). We i0,CO αCO, but more interestingly, HER (i0,H2 αH2) S3). 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