A Framework for Circularity-Oriented Catalytic Process Design in Industry

Thesis Abstract

Industrial ecosystems increasingly demand catalysts and processes that minimize waste, maximize resource recovery, and align with circular economy principles. However, widely adopted catalytic processes often prioritize yield and efficiency over material circularity, resulting in persistent waste streams, limited catalyst lifecycles, and suboptimal integration with valorization pathways. This study presents a framework for circularity-oriented catalytic process design in industry, integrating life cycle thinking, closed-loop material flows, and policy-compatible incentives to redefine process optimization criteria beyond conventional metrics. The aim is to develop a theory-driven framework that guides researchers and practitioners in embedding circularity considerations at the design phase of catalytic processes across petrochemical, energy, and chemical manufacturing sectors. Specific objectives are to (i) identify circularity indicators applicable to catalyst selection, reactor design, and downstream valorization; (ii) formulate a multi-criteria optimization model that simultaneously optimizes process performance, catalyst durability, and material recovery potential; (iii) validate the framework through a cross-industry case study portfolio comprising three industrially relevant reactions (hydrocracking, selective hydrogenation, and esterification) and two pilot plants; (iv) assess the sensitivity of circularity outcomes to material reuse options, regeneration strategies, and supply-chain constraints; and (v) develop a decision-support tool integrating techno-economic analysis with material circularity scoring, linked to a modular theoretical basis. The methodology adopts a mixed-methods research design combining theory-driven model development with empirical validation. The population includes catalytic processes in large-scale chemical plants and pilot facilities within Europe and North America, with a purposive sample of 12 representative case studies spanning three reaction classes. Data collection employs a triangulated instrument suite (i) semi-structured expert interviews (n=30) with process engineers, sustainability managers, and catalyst developers; (ii) process data and material balance records from case study facilities; (iii) lab-scale experiments to generate catalyst performance data under recycled feed and recycled catalyst scenarios, using standardized procedures for benchmarking. Analytical techniques include regression analysis and ANOVA to quantify the impact of circularity variables on yield, selectivity, and catalyst lifetime; multi-criteria decision analysis (MCDA) to aggregate circularity, economic, and environmental objectives; and system dynamics modeling to explore feedback loops in material flows. The theoretical basis draws on the Circular Economy Theory, Resource-Based View, and Theory of Planned Behavior to inform the framework’s constructs and governance implications. Instrument validity and reliability are ensured through pilot testing, content validity indexing with industry experts, and Cronbach’s alpha checks for survey instruments. The analytical framework is executed in Python and R, with sensitivity analyses conducted to evaluate robustness under variable market prices and supply disruption scenarios. Expected findings indicate that integrating circularity-oriented criteria into catalytic process design can maintain or improve process economics while enhancing material recovery and catalyst recyclability. It is anticipated that multi-criteria optimization will identify Pareto-optimal solutions where modest compromises in traditional performance metrics yield substantial gains in recyclability and waste reduction, particularly when regeneration and reuse strategies for catalysts are harmonized with feedstock diversification and by-product valorization. The study is expected to reveal differential circularity gains across process types, with hydrocracking and selective hydrogenation showing higher potential for catalyst reuse loops, whereas esterification demonstrates strong opportunities for by-product valorization and solvent minimization. The research will demonstrate the utility of the proposed decision-support tool in real-time process design workflows, enabling engineers to quantify circularity scores alongside conventional performance indicators. Contribution to knowledge includes (i) a theory-informed framework that integrates circularity principles into catalytic process design, (ii) a validated MCDA-augmented optimization model linking material circularity with economic and environmental outcomes, and (iii) a practical decision-support platform adaptable to diverse industrial contexts. The study closes with recommendations for policy alignment, industrial collaboration, and future research directions focused on standardizing circularity metrics, expanding the scope to heterogeneous catalysis, and scaling pilot successes to commercial operations.