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Item type:Publication, Access status: with files , The steam barrier as a design constraint in carbon capture: pathways to low-temperature regenerationPoint-source carbon capture is conventionally based on steam stripping to regenerate chemical solvents, creating a dependence on high-grade thermal energy and limiting integration with low-temperature heat sources. Steam-based regeneration is highly effective because it simultaneously supplies heat, promotes CO desorption, and facilitates production of a high-purity CO stream. Nevertheless, the widespread use of steam stripping should not be interpreted as evidence that high-temperature regeneration is the only viable pathway for CO release. In this Perspective, we examine solvent regeneration through the lens of energy quality and temperature-sensitive thermodynamic control variables, highlighting why CO desorption can occur at temperatures substantially below those required for conventional steam stripping. We connect observations across buffer systems, sterically hindered and tertiary amines, thermomorphic solvents, and enzymatically assisted capture to a common underlying mechanism: temperature-dependent acid–base equilibria and phase behavior that enable equilibrium-driven desorption without vaporization. Within this framework, carbonic anhydrase emerges not as a marginal absorber-side additive, but as a kinetic enabler that becomes viable under mild, low-temperature desorption conditions. Viewed through this lens, the steam barrier is revealed as one of multiple design options rather than a physical inevitability, opening systematic pathways toward carbon capture systems compatible with low-grade heat and improved exergy efficiency.Publicationtype: Journal Article77 107 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Multifunctional carbon‐nanotube supported catalyst for efficient glycerol hydrogenolysis to 1,2‐propanediol(Wiley, 2026-03); ; Multiwall carbon nanotube (NC7000) supported mono-, bi-, and trimetallic catalysts were synthesized and tested in a multi- batch reactor setup supported by data-driven modeling for the chemical hydrogenolysis of glycerol to 1,2-Propanediol (1,2-PDO) at 220◦C under 30 bar hydrogen pressure in aqueous solution. ICP-OES, N2 -physisorption, scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive x-ray spectroscopy (EDX), powder x-ray diffraction (XRD) and x-ray photoelectron spectroscopy (XPS) were used to investigate the physico-chemical properties of the synthesized catalysts. Interesting structure-activity-selectivity correlations could be deduced from the different metal ratios and combinations. While Ru was by far the most active monometallic species ( X = 100%), followed by Pt ( X = 80%) and Ir ( X = 65%), it suffered from a very low 1,2-PDO selectivity ( S < 10%). Combining Ru with the more selective transition-metals RuX2 ( X = Fe, Co, or Ni) maintained the high activity ( X > 95%) but only moderately increased 1,2-PDO selectivity ( S = 20%–30%). Interestingly, combining Ru with Cu in a bimetallic RuCu2 catalyst slightly decreased activity ( X = 81%) but drastically improved 1,2-PDO selectivity ( S = 58%). Moreover, a trimetallic combination of RuMCu2 (M = Pt, Pd, Ir) did not further increase activity ( X = 50%–70%) but could push 1,2-PDO selectivity up to 79% for the trimetallic RuIrCu2 catalyst. Most prominently, a final metal ratio variation for the RuCux catalyst was derived with the help of the data-driven models producing the most promising RuCu3 /NC7000) catalyst combining both high activity ( X = 78%) with a very high 1,2-PDO selectivity ( S = 79%) resulting in the highest 1,2-PDO yield of 58% in a nearly closed carbon balance ( C > 95%). This lays the foundation for implementing this highly active and selective catalyst in a future SMART reactor for glycerol valorization.Publicationtype: Journal Article87 78 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Optimal design of extraction-distillation hybrid processes by combining equilibrium and rate-based modeling(PSE Press, 2025-07-27); ; ; ; Liquid-liquid extraction (LLX) is an essential technique for separating heat-sensitive, highly diluted, or azeotropic mixtures. However, the design and optimization of LLX processes can be challenging due to mass transfer limitations and complex fluid dynamics. While distillation can often be modeled using equilibrium-based (EQ-based) approaches with (constant) height equivalent to theoretical stage (HETS) values, these kinetic effects can limit the applicability of EQ-based LLX models for conceptual design. Non-equilibrium (NEQ) or rate-based modeling can account for detailed mass transfer and fluid dynamics but further increases the nonlinearity and complexity of the respective optimization problems, which should account for closed-loop solvent recovery. To successfully address these complexities, we propose an integrated methodology combining NEQ-based simulation with EQ-based superstructure optimization to design a hybrid extraction-distillation process. An NEQ model is first used to derive operation-dependent HETS correlations, which are then incorporated into an EQ-based superstructure model for techno-economic optimization targeting total annualized cost. This approach balances model fidelity and computational efficiency, providing more reliable solutions by capturing the solvent-specific mass transfer behavior. We illustrate the methodology for a dilute acetone-water system with different solvents.Publicationtype: Journal Article25 18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Hybrid optimization methodologies for the design of chemical processes(De Gruyter, 2025-04); ; ; 68 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Hybrid optimization methodologies for the design of chemical processesProcess synthesis and design problems in chemical engineering usually require a solution to complex nonlinear optimization problems with continuous and discrete decision variables. The resulting mixed-integer nonlinear programming problems are particularly hard to solve, and different strategies are frequently applied for their solution. Gradient-based optimization enables fast computations, exploiting local sensitivity information, but is usually limited to local optima for nonconvex problems, whereas derivative- free optimization methods can be linked to available simulation models, with little effort, but also without any guarantee of optimality. Metaheuristics, especially swarm intelligence and population-based algorithms, are frequently applied for simulation-based process optimization, overcoming the lack of gradient information, at the cost of a considerable number of simulations. Another strategy that is receiving increasing interest builds on surrogate models that are first generated based on an initial sampling of process simulations for systematically varied design variables. Tractable surrogate models do provide the necessary sensitivity information that enables efficient gradient-based optimization, while being only an approximation of the original problem. Each strategy has its advantages and limitations, and no single best option is generally favorable for all kinds of problems. Thoughtful combinations of different strategies have the potential to overcome or at least reduce the individual limitations, while simultaneously combining the strengths of the individual methods. The current chapter provides an introduction and overview of such hybrid optimization methodologies, together with some illustrations of their use for applications in chemical engineering. Several case studies, including utility and entrainer selection, illustrate the performance of hybrid optimization methods and indicate the ability to solve even more complex design problems.Publicationtype: Book Part22 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , HOOU an der TU Hamburg : Jahresbericht 2024(Technische Universität Hamburg, 2025); ; ; ; In diesem Bericht stellt die Hamburg Open Online University an der TU Hamburg (HOOU@TUHH) ihre Arbeit im Jahr 2024 vor.Publicationtype: Project Deliverable95 56 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Exergy-based optimization for the synthesis of heat pump assisted distillation columnsWhile distillation columns are the main unit operation in fluid separation processes, considered versatile, robust, and well-understood, they are also oftentimes framed as energy intensive and potentially inefficient. Heat pumps bear the potential to improve the energy efficiency of distillation processes and simultaneously allow for the electrification of the thermal-driven separation processes. However, the economic viability and potential for energy savings depend strongly on the temperature lift and the compression ratio of the heat pump. Both can be reduced by considering intermediate heat exchangers rather than a full temperature lift from below the top vapor to above the bottoms temperature. Such intermediate heat exchangers may furthermore improve the internal efficiency of the distillation column and thereby improve the overall energy efficiency. The current contribution presents an exergy-based optimization that allows for an improved heat load distribution that can provide significant improvements of the internal efficiency and further enables a conceptual design of heat pump assisted distillation, using vapor recompression to provide the heat loads at the intermediate heat exchangers. The benefits of the approach are illustrated for the separation of a nonideal acetone-water mixture, highlighting the capability to identify unintuitive designs with significant saving potential.Publicationtype: Conference Paper125 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , 53 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Evaluation of the potential of a deep eutectic solvent for liquid-liquid extraction of furfural using optimization-based process designReducing our environmental impact is the greatest challenge of our time and affects all areas of the chemical, biochemical, and pharmaceutical industries. The use of sustainable and biodegradable solvents in downstream processes, such as deep eutectic solvents (DESs), is one essential step in this direction. While many studies have focused on the investigation of- the thermo-physical properties of DESs, relatively little attention has been paid to solvent regeneration in the context of a closed-loop process, assuming a simple recovery due to the negligible vapor pressure of the DES. In order to evaluate the suitability of this assumption, the current work performs an optimization-based process design for the recovery of furfural from a diluted fermentation broth by liquid-liquid extraction, comparing a previously screened DES with toluene as an established organic solvent. The comparison reveals important limitations of the DES due to considerable water content in the raffinate and the high boiling point resulting in a more complex and energy-demanding process.Publicationtype: Conference Paper41 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , From problem specification to converged flowsheet simulations: integrated workflow in an industrial context(Elsevier, 2023-06); ; 28