Biomass is a key renewable resource for advancing sustainable and circular energy systems. In contrast to prior reviews that predominantly emphasized well-established biomass types and conventional conversion technologies, this work offers a comparative synthesis that underscores underutilized feedstocks and emerging valorization pathways, providing a strategic perspective for sustainable process development. This review critically examines the current state of high-value-added bioproducts derived from biomass, focusing on their relevance to climate mitigation and resource efficiency. It explores sustainable process design strategies that enhance the environmental and economic performance of biomass conversion. Particular attention is given to recent advances in process intensification, including novel reactor configurations and heat integration techniques. The integration of sustainability assessment tools and multi-objective optimization approaches is analyzed to support data-driven decision-making. Multi-product biorefineries are discussed as central platforms for valorizing diverse feedstocks, supported by emerging models for supply chain integration. Present limitations such as feedstock heterogeneity, infrastructure constraints, and energy coupling challenges are reviewed, along with new opportunities in digitalization, modularization, and policy support. The novelty of this work lies in its cross-sectional synthesis of technologies, methodologies, and system-level strategies, offering a unified framework to unlock the full potential of biomass as a strategic vector for sustainable process development.

BACKGROUND Butanol produced from fermentation has attracted the interest of research groups because its physicochemical properties show several enhancements over bioethanol. Recent studies have proposed alternative methods to separate and purify biobutanol from a fermentation broth. These alternatives offer energy and economic savings; in addition, a reduction in environmental impact is observed. However few studies have analyzed the control properties of the process which involves separation of an acetone–butanol–ethanol (ABE) mixture. RESULTS A controllability analysis using the singular value decomposition technique and a closed-loop dynamic analysis was performed on several hybrid distillation processes including conventional, thermally coupled, thermodynamically equivalent and intensified designs. The results indicated that under the closed-loop control policy, an intensified design which is integrated for only two distillation columns instead of three distillation columns, showed good dynamic properties. In addition, thermally coupled sequence A showed better control properties under open-loop analysis. CONCLUSIONS Using both SVD analysis and closed-loop tests the dynamics properties were obtained for several hybrid processes to separate an effluent produced by fermentation. It was possible to control all schemes under both methodologies and it was clear that when the base case became more complex with thermal coupling, section movement or elimination of a column section improved the control properties. © 2016 Society of Chemical Industry

Green hydrogen is a key energy carrier for industrial decarbonization; however, its large-scale deployment requires the optimization of production routes from both energetic and economic perspectives. In this study, green hydrogen production via biomass gasification and water electrolysis is comparatively evaluated using a multi-objective optimization framework based on the Differential Evolution Tabu List (DETL) algorithm. The optimization simultaneously maximizes hydrogen production while minimizing specific energy consumption and total annualized cost, explicitly capturing the trade-offs between competing technologies. Results indicate that biomass gasification outperforms water electrolysis in both energetic and economic terms. The optimal gasification configuration achieves 3625.95 kg/h of H₂ with a specific energy consumption of 39.63 kWh/kg H₂ and a total annualized cost of 2.45 MUSD/yr, whereas water electrolysis reaches 3156.78 kg/h of H₂ with 68.7 kWh/kg H₂ and a cost of 3.72 MUSD/yr. To support the interpretation of results, K-means clustering is integrated into the methodological framework, enabling the identification of representative regions within the Pareto fronts. Overall, biomass gasification provides more balanced and flexible solutions, highlighting its potential as a competitive route for sustainable hydrogen production.

Optimization has played a fundamental role in the evolution of chemical engineering, enabling systematic decision-making under technical, economic, and environmental constraints. This review presents a structured and comparative analysis of the historical development and current state of optimization methodologies applied to chemical engineering, covering the transition from early linear and nonlinear programming approaches to advanced data-driven and artificial intelligence-based frameworks. A systematic literature review was conducted following the PRISMA guidelines, through which a total of 101 articles were retained for analysis. The results indicate that mixed-integer programming and decomposition-based methods remain widely adopted for structured industrial problems, while metaheuristic and hybrid data-driven approaches have experienced significant growth in recent years. In particular, a clear trend toward the integration of machine learning and surrogate modeling techniques is observed, driven by the need to address large-scale, non-convex, and highly nonlinear systems. The analysis reveals a clear methodological shift from classical linear optimization frameworks toward hybrid optimization strategies capable of addressing large-scale, non-convex, and highly nonlinear problems. Finally, current challenges and future research directions are identified, emphasizing the need for robust hybrid approaches that combine mathematical programming and intelligent algorithms to effectively manage complexity in next-generation chemical systems.