# Modeling Product Selectivity in Electrocatalytic Carbon Dioxide Reduction Using Scaling Relationships > **NIH NIH F32** · YALE UNIVERSITY · 2022 · $58,731 ## Abstract Project Summary The Wood-Ljungdahl (WL) pathway is a CO2 fixation pathway that relies on two different CO2 reducing enzymes — formate dehydrogenase (FDH) and carbon monoxide dehydrogenase (CODH) — to ultimately convert CO2 to biomass through formate and carbon monoxide. Biology has successfully evolved catalysts for the reactions in the WL-pathway that feature remarkable activity and selectivity that is envied by the pharmaceutical and commodity chemicals industries, where the efficient utilization of CO2 as a C1 building block is desirable. Despite this, attempts to design structural models of these enzymes for homogenous electrocatalytic CO2 reduction have been unsuccessful. A more comprehensive understanding of the enzymes found in the WL- pathway and the design of better CO2 reduction catalysts will require a better understanding of how the intrinsic properties — reduction potential (E1/2) of the catalyst , pKa and concentration of acid, and degree of intermediate stabilization by secondary sphere effects — direct product selectivity. In order to better understand how the properties of these enzymes lead to disparate selectivity, molecular “thermodynamic-kinetic scaling relationships” for the electrochemical CO2 reduction reaction (CO2RR) will be developed. “Scaling relationships” are defined as a correlation between thermodynamic variables with kinetic outcomes such as turnover frequency or selectivity. These scaling relationships will be used to determine how perturbations to tunable thermodynamic variables (catalyst E1/2, acid pKa, etc.) affect selectivity outcomes. Monitoring the selectivity as a function of these variables will enable the building of a selectivity model. In addition, we will determine how secondary sphere effects alter the selectivity through hydrogen bonding and electrostatic interactions in analogy to similar effects found in enzyme active sites. Last, we aim to address how electric fields — which are increasingly implicated in enzymatic mechanisms of action — alter the selectivity of CO2RR through the study of hybrid electrodes featuring an anchored molecular CO2 reduction catalyst. Prof. Mayer and Yale University have provided an excellent environment to not only conduct my proposed research but to grow as a scientist. The research I am proposing to conduct under the mentorship of Prof. Mayer will give me the knowledge to address a wide range of complex problems. During my burgeoning postdoctoral tenure, I am continuing to develop my professional skills by communicating my work through presentations and writing, and to continue mentoring students as I've done throughout my career but with a new perspective. Additionally, Yale University has surrounded me with faculty that are knowledgeable in many of the areas I aim to be. For example, Prof. Patrick Holland's incredible reputation for ligand design and Prof. Sharon Hammes– Schiffer's leadership in PCET theory will undoubtedly be beneficial resources for my propose... ## Key facts - **NIH application ID:** 10462533 - **Project number:** 5F32GM140723-02 - **Recipient organization:** YALE UNIVERSITY - **Principal Investigator:** Adam J Pearce - **Activity code:** F32 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $58,731 - **Award type:** 5 - **Project period:** 2021-08-01 → 2023-06-02 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10462533 ## Citation > US National Institutes of Health, RePORTER application 10462533, Modeling Product Selectivity in Electrocatalytic Carbon Dioxide Reduction Using Scaling Relationships (5F32GM140723-02). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10462533. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*