Comparative Catalytic Performance of Metal–Organic Frameworks in CO2 Reduction

Thesis Abstract

The escalating demand for sustainable CO2 management necessitates efficient catalytic platforms capable of converting carbon dioxide into value-added fuels and chemicals under mild conditions. This study investigates the comparative catalytic performance of representative metal–organic frameworks (MOFs) for CO2 reduction, addressing the variability in activity, selectivity, and stability arising from framework topology, metal nodes, and functionalization. The aim is to elucidate structure–function relationships that govern CO2 activation and multi-electron transfer processes, and to identify MOFs with robust performance under operationally relevant conditions. Specific objectives include (1) synthesizing and characterizing a diverse set of MOFs—UiO-66, ZIF-8, NH2-MIL-125(Ti), and Fe-MOF-74 modified variants—with systematic alterations in secondary building units and functional groups; (2) evaluating catalytic activity for CO2 electroreduction to CO and formate, using standardized electrochemical cells under identical electrolytes and gas purities; (3) assessing selectivity, turnover frequency (TOF), overpotential, and long-term stability via chronoamperometry, current density normalization, and post-reaction structural analysis; (4) probing CO2 adsorption energies and activation barriers through in situ infrared spectroscopy and operando X-ray absorption spectroscopy (XANES/EXAFS) to correlate electronic structure with catalytic performance; and (5) developing a predictive model linking MOF descriptors (pore size, surface area, metal oxidation state, linker functionalization) to observed activity using multivariate regression and machine-learning approaches. A mixed-methods approach combines experimental synthesis and electrochemical testing with computational insights. The population comprises commercially sourced and lab-synthesized MOFs (N = 6–8 distinct frameworks) subjected to standardized activation protocols. Sample sizes for electrochemical runs include triplicate measurements per MOF in three independent batches to ensure reproducibility, yielding an anticipated dataset of approximately 60–72 catalytic trials. Instruments include a gas-tight three-electrode electrochemical cell, a potentiostat with controlled potential steps, gas chromatography for product quantification, nuclear magnetic resonance (NMR) spectroscopy for formate detection, in situ attenuated total reflectance infrared (ATR-IR) spectroscopy for adsorbate monitoring, and synchrotron-based X-ray absorption spectroscopy for oxidation state and local coordination environment analysis. Data analysis employs regression and analysis of variance (ANOVA) to compare performance metrics (overpotential, TOF, Faradaic efficiency) across MOFs, with post-hoc tests identifying statistically significant differences. Multivariate statistical modeling, including principal component analysis (PCA) and machine-learning regression (random forest), will be used to relate MOF descriptors to catalytic outcomes. Theoretical interpretation draws on the d-electron configuration theory and Sabatier principle, complemented by concepts from metal–support interactions and porous-media diffusion limitations. Expected findings include clear distinctions in catalytic activity and selectivity linked to pore architecture, metal node identity, and linker functionalities. It is anticipated that amino-functionalized MOFs (e.g., NH2-MIL-125(Ti)) will exhibit enhanced CO2 adsorption and activation, while high-coordination-number metal centers (e.g., Ti, Fe) will facilitate multi-electron transfer pathways, lowering overpotentials for CO2-to-CO and CO2-to-formate routes. The work should reveal trade-offs between accessibility (larger pore sizes) and active-site density (crowding effects), with some frameworks demonstrating superior long-term stability under electrochemical cycling due to robust node coordination and framework rigidity. The study contributes to knowledge by providing a systematically controlled comparative dataset that links MOF structural features to catalytic performance in CO2 reduction, enabling rational design principles for MOF-based electrocatalysts. It will offer a validated descriptor set and a predictive model capable of screening candidate MOFs prior to synthesis, reducing trial-and-error in catalyst development. Conclusions are expected to emphasize that MOF performance is governed by an integrated interplay of adsorption energetics, electronic structure of the metal node, and transport properties within hierarchical porosity. Recommendations include prioritizing MOFs with functionalized linkers that promote CO2 activation while maintaining structural stability under reductive conditions, adopting in situ characterization as a standard for catalyst evaluation, and extending the framework to tandem catalytic systems that couple CO2 reduction with subsequent hydrocarbon chain growth. The research suggests avenues for future work, such as exploring post-synthetic metalation strategies and solvent effects to further tune activity and selectivity.