Comparative Analysis of Green Solvent Efficacy in Catalytic Reactions Across Industries

Thesis Abstract

The transition toward sustainable chemical manufacturing hinges on the comparative efficacy of green solvents in catalytic reactions across diverse industrial contexts, where solvent choice simultaneously influences reaction efficiency, product quality, environmental impact, and process economics. This study addresses the gap in cross-sector empirical evidence guiding solvent selection by evaluating the performance of three representative green solvent classes—bio-based ethers, bio-based carbonates, and deep eutectic solvents (DES)—against conventional solvents in standardized catalytic transformations. The aim is to determine whether green solvents can match or surpass conventional media in reaction rate, selectivity, yield, and recyclability while reducing toxicity and lifecycle environmental footprint. Specific objectives include (i) benchmarking reaction metrics (conversion, yield, selectivity, turnover frequency) for representative reactions—Friedel–Crafts acylation, Suzuki–Miyaura cross-coupling, and esterification—performed in each solvent class across three industry-relevant substrates; (ii) quantifying environmental and economic performance via E-factor, solvent intensity, and estimated energy consumption; (iii) identifying mechanistic and physicochemical factors governing solvent–catalyst compatibility, using Hansen solubility parameters and dielectric constant correlations; and (iv) developing a decision framework for solvent selection tailored to reaction type and industrial constraints. A mixed-methods approach was adopted. The quantitative component employed a factorial experimental design (3 solvent classes × 3 reaction types × 3 substrates) with triplicate runs, yielding a dataset of 81 reaction conditions per solvent class, totaling 243 experiments. Reaction progress was monitored by in-situ FTIR spectroscopy and GC–MS for product and byproduct profiling, while product yields and purities were confirmed by NMR and HPLC. Catalyst activity and selectivity were analyzed through regression modeling to estimate turnover frequencies and selectivities as functions of solvent properties, with ANOVA used to assess statistically significant differences across solvents and reaction types. The qualitative component leveraged expert interviews (n=15) with process chemists and environmental engineers from pharmaceutical, agrochemical, and polymer industries to elucidate practical constraints, solvent recovery challenges, and perceived trade-offs, with thematic analysis guided by the Theory of Planned Behavior to understand decision drivers. Theoretical framing integrates Green Chemistry principles with the Analytical Reaction Environment model and the Solvent-Polymer-Catalyst Interaction framework to interpret observed performance trends. Key expected findings include that DES and bio-based carbonates exhibit comparable or superior yields and selectivities to conventional solvents in cross-coupling and esterification, with notably lower E-factor and solvent consumption per kilogram of product due to enhanced recyclability and reduced vapor pressures. Bio-based ethers are anticipated to offer favorable reaction rates for Friedel–Crafts acylations, but may require higher catalyst loading to achieve equivalent selectivity, depending on substrate polarity. Mechanistic insights are expected to reveal that solvent dielectric properties, hydrogen-bonding capacity, and viscosity significantly influence catalyst coordination environments and transition-state stabilization, thereby modulating turnover frequencies. Cross-industry comparison is anticipated to reveal substantive economic and environmental advantages for green solvents in high-volume, low-margin processes, contingent on solvent recovery efficiency and energy inputs for drying and concentration steps. Contributions to knowledge include (i) a comprehensive, empirically validated cross-sector performance matrix of green solvents in key catalytic transformations; (ii) a robust, data-driven decision framework for solvent selection that integrates reaction type, substrate class, and process economics; and (iii) mechanistic understanding of solvent–catalyst interactions that informs solvent design and catalyst optimization. The study is expected to show that judicious selection and effective recovery of green solvents can reduce process environmental footprints by 25–45% and operational costs by 8–15% in mature industrial settings, without compromising product quality. Practical recommendations emphasize scalable solvent recovery technologies, solvent–catalyst compatibility screening protocols, and integration of green solvents into continuous-flow processes where feasible. The main conclusion is that green solvents, when chosen based on a mechanistic understanding of solvent effects and aligned with recovery strategies, can offer a viable pathway to sustainable catalysis across industries. Recommendations include developing industry-wide solvent performance catalogs, investing in solvent-compatible catalyst libraries, and pursuing lifecycle assessments for process retrofit projects to accelerate adoption.