Comparative Study of Catalytic Efficacy in Bio-Derived Solvent Systems

Thesis Abstract

The rising demand for sustainable chemical processes motivates scrutiny of catalytic performance in bio-derived solvent systems, where solvent—catalyst interactions can significantly influence reaction efficiency, selectivity, and environmental footprint. The study addresses the gap in comparative data on how bio-derived solvents modulate catalytic activity across representative reaction classes, aiming to identify solvent-catalyst pairings that maximize yield while minimizing energy input and waste generation. The primary aim is to evaluate and compare the catalytic efficacy of iron- and nickel-based catalysts in renewable solvent media derived from lignocellulosic sources (Ethyl lactate, ?-valerolactone, and 2-methyl THF) relative to conventional petrochemical solvents. Specific objectives include (i) quantifying reaction yields and selectivities for (a) esterification, (b) hydrogenation, and (c) C–C coupling reactions under identical temperature–pressure–time conditions; (ii) assessing catalyst stability and recyclability over five consecutive cycles; (iii) analyzing solvent effects on catalyst dispersion and turnover frequency; (iv) modeling structure–reactivity relationships using targeted physicochemical descriptors; and (v) conducting a comparative life cycle assessment to frame the environmental benefits of bio-derived solvent systems. A mixed-methods approach combines experimental kinetics with statistical modeling. The population comprises standard catalytic systems Fe- and Ni-based heterogeneous catalysts supported on mesoporous silica, tested in three bio-derived solvents alongside a conventional solvent as control. A total of 12 catalytic runs per reaction type are conducted at 120–180°C under 1–5 MPa hydrogen pressure, with reaction times set to 2–6 hours. In total, 36 experimental runs per solvent category are executed, with triplicate measurements for each condition to ensure reliability. Data collection employs gas chromatography–mass spectrometry (GC-MS) for product quantification, inductively coupled plasma optical emission spectroscopy (ICP-OES) for metal leaching analysis, Brunauer–Emmett–Teller (BET) surface area measurements for catalyst characterization, and transmission electron microscopy (TEM) for particle size distribution pre- and post-reaction. Catalyst stability is further evaluated by X-ray photoelectron spectroscopy (XPS) to monitor oxidation state changes. Data analysis utilizes regression analysis to model reaction yield as a function of solvent descriptor variables (H-bonding capacity, polarity, dielectric constant) and catalyst properties (metal type, oxidation state, dispersion). Analysis of variance (ANOVA) tests determine the significance of solvent effects across catalysts and reactions, while Scheffe post hoc tests identify specific group differences. Turnover frequency (TOF) and turnover number (TON) are calculated to compare intrinsic catalytic efficacy, and leaching data are analyzed via mass balance and ICP-OES to ensure account for activity loss. A partial least squares (PLS) regression is employed to relate physicochemical solvent descriptors to observed catalytic performance, and a limited kinetic model is fitted to the esterification and hydrogenation datasets to extract rate constants. The study also applies a pragmatic framework analogous to the Theory of Planned Behavior for interpreting decision-relevant outcomes in process design, with insights into scalability considerations. Expected findings anticipate that bio-derived solvents will exhibit distinct, solvent-dependent improvements in selectivity and reduced catalyst deactivation for specific reaction classes, with ?-valerolactone offering superior stability in esterification, Ethyl lactate enhancing hydrogenation selectivity, and 2-methyl THF delivering favorable C–C coupling yields at optimized temperatures. It is expected that bio-derived solvents will demonstrate reduced environmental impact per unit product when evaluated via preliminary life cycle indicators, with trade-offs in energy input for certain reactions. The study contributes to knowledge by quantifying solvent-mediated catalytic performance across multiple reactions, linking solvent physicochemical properties to activity, selectivity, and stability, and by providing a framework for solvent choice in greener catalysis. The main conclusion anticipates that judicious selection of bio-derived solvents can enhance catalytic efficacy while reducing environmental burden, and recommendations emphasize solvent–catalyst pairing guidelines, catalyst recovery strategies, and targeted process optimization for industrial adoption.