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Publications (879)
The chemical industry is one of the largest consumers of fossil raw materials in the European Union (EU). Phasing out the use of fossil carbon both for energetic and material use (decarbonization/defossilization) requires the introduction of alternative processes and systems of production and consumption. One strategy that brings forward the defoss...
Zusammenfassung
Im Power‐to‐X‐Konzept werden wandgekühlte Festbett‐Rohrbündelreaktoren zur Durchführung exothermer, heterogen katalysierter Reaktionen eine zentrale Rolle einnehmen. Um hohe Produktausbeuten ohne Überhitzung der Reaktoren zu erzielen, ist jedoch ein effektives Wärmemanagement erforderlich, insbesondere bei lastflexiblem Betrieb. Ein...
Predictive thermodynamic models are crucial for the early stages of product and process design. In this paper the performance of Graph Neural Networks (GNNs) embedded into a relatively simple excess Gibbs energy model, the extended Margules model, for predicting vapor-liquid equilibrium is analyzed. By comparing its performance against the establis...
Solving mixed-integer optimization problems with embedded neural networks with ReLU activation functions is challenging. Big-M coefficients that arise in relaxing binary decisions related to these functions grow exponentially with the number of layers. We survey and propose different approaches to analyze and improve the run time behavior of mixed-...
To address the problems of virgin plastic production from fossil resources and the growing amount of plastic waste, a rapid transition to a circular economy is being pursued. The separation of mixed plastics into pure fractions is of paramount importance for promoting recycling and preventing downcycling. In this study, experimental parameters were...
Power-to-X processes convert excess renewable energy into storable fuels such as methane, addressing critical energy storage and transportation challenges. However, implementing these processes presents operational difficulties, particularly in managing fluctuating energy inputs. Digital Twins, or virtual replicas of physical systems, offer a promi...
A comprehensive analysis of the flow in Schwarz-D triply periodic minimal surfaces (TPMS) structures based on CFD simulations is presented. The pressure drops and friction factor characteristics of the structure are investigated by employing both full-scale and representative elementary volume (REV)-scale CFD setups. The results are validated again...
Power‐to‐methane (PtM) offers an efficient opportunity for surplus renewable energy storage, but heat management is a major challenge for conducting the highly exothermic methanation reaction. To address this challenge, this study presents the first successful demonstration of core‐shell catalyst pellets in a pilot‐scale reactor for CO 2 methanatio...
Depolymerization and subsequent capture of monomers is of interest for process efficiency and sustainability. Polyamide‐6 (PA‐6) can be depolymerized in aqueous solution using a homogeneous catalyst. To purify the ε‐caprolactam (CPL) monomer and recycle the catalyst, two potential crystallization‐based strategies are studied: direct crystallization...
Hydrogen is vital for sectors like chemicals and others, driven by the need to reduce carbon emissions. Proton Electrolyte Membrane Water Electrolysis (PEMWE) is a key technology for the production of green hydrogen under fluctuating conditions of renewable power sources. However, due to the scarcity of noble metal materials, the stability of the a...
When designing extractive distillation processes, using selectivity and capacity at infinite dilution alone is hard to identify the real optimal solvent with minimal process cost. To overcome this problem, a new process-driven solvent screening approach is developed. As simple and reliable surrogate models, rational functions (algebraic fractions s...
Addressing climate change requires a transition to renewable energy sources. An integral part of this transition is the conversion of carbon dioxide through methanation, facilitated by the Power-to-X reactor technology. However, the implementation of this process can present significant operational hurdles, particularly in terms of control. The lat...
Purification of polymer‐grade (99.9%) C2H4 from C2 hydrocarbon mixture is industrially important but challenging. Cryogenic distillation is energy intensive. Recently, pressure/vacuum swing adsorption (P/VSA) processes using metal‐organic frameworks (MOFs) as adsorbents have been attracting increasing attention as an alternative technology. A multi...
Due to the urgent need for global climate change mitigation, the use of renewable carbon sources and the application of circular economy principles represent promising ways to implement the necessary fundamental transformation toward a sustainable (i.e., carbon-neutral) carbon-based chemical industry. As this required transformation involves a mult...
In this study, we evaluated the effectiveness of various frequency response analysis (FRA) techniques for identifying fault states in the diagnosis of polymer electrolyte membrane fuel cells (PEMFCs). To this end, an identifiability analysis was conducted to determine the reliability of parameters obtained by fitting a previously validated PEMFC mo...
Given the problems of virgin plastic production from fossil resources and the growing amount of plastic waste, a rapid transition towards a circular economy is pursued. For recycling, the separation of mixed plastics into pure fractions is of paramount importance to prevent downcycling. Here, experimental parameters for selective bulk dissolution o...
This research focuses on the rational design of porous enzymatic electrodes, using horseradish peroxidase (HRP) as a model biocatalyst. Our goal was to identify the main obstacles to maximizing biocatalyst utilization within complex porous structures and to assess the impact of various carbon nanomaterials on electrode performance. We evaluated as-...
First industrial-scale Power-to-Methanol plants are starting to be deployed in various geographic locations to tackle the problem of high greenhouse gas emissions of the predominantly fossil-based production of methanol. With the aim to speed up the deployment by streamlining their engineering and construction, we explore the potential of reducing...
Considerable attention has been dedicated to lipid rafts due to their importance in numerous cell functions such as membrane trafficking, polarization, and signaling. Next to studies in living cells, artificial micrometer-sized vesicles with a minimal set of components are established as a major tool to understand the phase separation dynamics and...
Efficient absorption processes require optimized packed bed column structures, which affect gas-liquid contact, flow distribution, and pressure drop. An optimal setup ensures efficient mass transfer with high surface area while keeping down the pressure drop, which leads to energy savings and better absorption. TPMS structures such as the Gyroid, S...
Machine learning models have gained prominence for predicting pure-component properties, yet their application to mixture property prediction remains relatively limited. However, the significance of mixtures in our daily lives is undeniable, particularly in industries such as polymer processing. This study presents a modification of the Gibbs–Helmh...
We present a multi‐objective optimization framework for the design of an algal biorefinery with multiple target products. Four environmental endpoint indicators and the economic performance are used as objective functions following the life cycle assessment (LCA) methodology. The process alternatives are modeled as a superstructure covering a total...
As property and process models with many variables need to be considered, integrated computer‐aided molecular and process design (CAMPD) problems are computationally expensive. An efficient CAMPD approach is proposed for the simultaneous design of solvents and extractive distillation (ED) processes based on a data‐driven modeling strategy. First, a...
A spatially distributed electrochemical preferential oxidation (ECPrOx) reactor is evaluated and the influence of the temperature, CO inlet concentration, feed flow rate, and relative humidity on the polarization curve, the local current distribution, and the CO outlet concentration, selectivity, and conversion were investigated. For that, six diff...
This work introduced a scalable and integrated machine learning (ML) framework to facilitate important steps of building quantitative structure–property relationship (QSPR) models for molecular property prediction. Specifically, the molecular descriptor generation, feature engineering, ML model training, model selection and ensembling, as well as m...
The electrocatalytic stability of the oxygen evolution reaction (OER) is challenging for the storage of fluctuating renewable energies using polymer electrolyte membrane water electrolyzers (PEMWEs). Investigations are commonly conducted in so-called half-cell setups and different OER-related dissolution pathways have been proposed. However, the or...
Ionic liquids (ILs) could find use in almost every chemical process due to their wide spectrum of unique properties. The crux of the matter lies in whether a task-specific IL selection from enormous chemical space can be achieved by property prediction, for which limited labeled data represents a major obstacle. Here, we propose a one-stop ILTransR...
The accurate prediction of physicochemical properties of chemical compounds in mixtures (such as the activity coefficient at infinite dilution γij∞) is essential for developing novel and more sustainable chemical processes. In this work, we analyze the performance of previously-proposed GNN-based models for the prediction of γij∞, and compare them...
Hydrogen crossover in polymer electrolyte membrane electrolysis cells is important concerning faradaic efficiency, flammability hazards, and degradation phenomena. In recent years, steady-state H2-in-O2 measurements have demonstrated that the hydrogen crossover increases with current density, due to mass transport limitations in the cathode catalys...
Lignocellulose is one of the most promising renewable bioresources for the production of chemicals. For sustainable and competitive biorefineries, effective valorization of all biomass fractions is crucial. However, current efforts in lignocellulose fractionation are limited by the use of either toxic or suboptimal solvents that do not always allow...
The accurate prediction of physicochemical properties of chemical compounds in mixtures (such as the activity coefficient at infinite dilution $\gamma_{ij}^\infty$) is essential for developing novel and more sustainable chemical processes. In this work, we analyze the performance of previously-proposed GNN-based models for the prediction of $\gamma...
Catalyst research is concerned with synthesizing increasingly active materials, leading to safety issues at reactor scale, unless the reaction heat release is controllable. Computational studies predict, that core-shell pellets, with catalytically active core and inert shell, are beneficial for this purpose, compared to established concepts, such a...
Renewable methanol production is an important part of the energy transition of the chemical industry from fossil to renewable resources. This work presents the design of a methanol production from renewable energy only, using an extended optimization-based FluxMax approach. This linear programming design approach considers waste-heat utilization in...
Interpretable machine learning (ML) is applied to accelerate the discovery of promising metal–organic frameworks (MOFs) for the selective separation of ethane (C2H6) and ethylene (C2H4). Based on molecular simulation data, ML models are first trained and tested to classify MOFs into C2H4-selective and C2H6-selective categories using different types...
Although eutectic solvents (ES), also widely termed as deep eutectic solvents (DES), have attracted significant interest in various chemical processes, the rational design of them remains challenging due to the difficulty in estimating eutectic formation. In this work, the regular solution theory (RST) and quantitative structure-activity relationsh...
Cylindrical, cm‐sized monolithic Al2O3 xerogels with hierarchical meso‐/macropore system were prepared by sol‐gel synthesis. The influence of both solvent exchange and drying on monolith stability and the resulting pore system was studied following mass and volume of the monolith as well as by porosimetry and electron microscopy. Crack‐free drying...
A two‐step integrated metal‐organic framework (MOF) and pressure/vacuum swing adsorption (P/VSA) process design has been recently established for gas separation. In the first step, selected MOF descriptors and process operating conditions are simultaneously optimized to maximize the process performance. Based on the obtained results, the second ste...
Understanding the influence of dynamic and stationary polarization on the deactivation of state-of-the-art IrOx catalysts is imperative for the design and operation of robust and efficient proton exchange membrane water electrolyzers. In this work, the deactivation and activity regeneration of a commercial IrOx catalyst were investigated under pote...
Adsorption is widely used for gas separation and storage. Its performance relies heavily on the selection of suitable adsorbents. In this work, a data-driven neural recommender system is developed for a preliminary adsorbent screening. Over 32,000 single-component isotherms are retrieved from the NIST isotherm database. After a series of filtering...
Significance
The discovery that amphiphilic polymers, similar to phospholipids, can self-assemble to vesicles has inspired numerous applications. For instance, these polymersomes are employed for drug delivery due to their increased chemical and mechanical stability. These polymers can be also mixed with lipids to form the so-called hybrid membrane...
A two-step integrated MOF and pressure/vacuum swing adsorption (P/VSA) process design has been recently established for gas separation. In the first step, selected MOF descriptors and process operating conditions are simultaneously optimized to maximize the process performance. Based on the obtained results, the second step (i.e., MOF matching) is...
There is considerable motivation in the catalysis community and chemical industry to envision a future where rational catalyst design and targeted chemical process optimization become standard. Achieving this goal for heterogeneous catalysis requires a cultural shift centered around effective research data management. The core elements of modern ca...
Identification of high-performing sorbent materials is the key step in developing energy-efficient adsorptive separation processes for ethylene production. In this work, a computational screening of metal-organic frameworks (MOFs) for the purification of ethylene from the ternary ethane/ethylene/acetylene mixture under thermodynamic equilibrium con...
Back Cover: In article number 2100712 by Ivan Ivanov and co‐workers, a functionalized dimethicone, commercially used as emulsifier in cosmetics, self‐assembles into vesicles and even provides a suitable environment for membrane proteins. Upon vigorous agitation in the presence of physiological concentrations of salt, these vesicles continuously fus...
The use of predictive methods for physicochemical properties is of special interest given the difficulties involved in the experimental determination of large chemical spaces. In this work, we focus on the prediction of infinite dilution activity coefficients γij∞ of organic systems using graph neural networks (GNNs). Our proposed method involves t...
A novel integrated machine learning (ML) framework, consisting of structure decomposition, feature integration and predictive modeling, is proposed to correlate MOF structures with gas adsorption capacities. First, metal nodes, organic linkers, and underlying topologies are identified from MOF structures. Numerical features of the organic linker ar...
Fixed-bed reactors employed within Power-to-X technologies are expected to be subject to volatile process feeds, in order to minimize intermediate buffer or storage systems. In this context, catalyst particles with an inert shell have proven suitable to prevent reactor runaway and severe temperature excursion at various loads and during load-change...
Gas separation accounts for a major production cost in chemical industries. So far, pressure swing adsorption (PSA) has been widely used for gas separation applications such as H2 purification and CO2 capture. For PSA processes, the adsorption efficiency is greatly affected by the selected adsorbent and process operating conditions. Over the past d...
Metal-organic frameworks (MOFs) are recognized as promising materials for gas storage and separation due to their structural diversity, high porosity, and tailorable functionality. Considering the large number of possible MOFs, an integrated machine learning framework is proposed to discover promising candidates with desirable adsorption properties...
In this contribution, we propose a new CAMD approach for solvent design by combining machine learning with deterministic optimization. Variational autoencoder (VAE), a powerful generative machine learning method, is used to transfer a molecular structure into a continuous latent vector with an encoder and to convert the latent vector back to the mo...
Considering the critical roles of hydrogen in energy transition and the renewable character of biogas, an integrated process linking ionic liquid (IL) based biogas upgrading and thermal plasma (TP) assisted hydrogen production is conceptually proposed and studied from the process intensification point of view. To select a practically suitable IL ab...
An integrated metal–organic framework (MOF) and pressure/vacuum swing adsorption (P/VSA) process design framework is presented for gas separation. It consists of two steps: adsorbent descriptor optimization, and MOF matching. In the first step, MOFs are represented as a large set of chemical and geometric descriptors from which the most influential...
Giant unilamellar vesicles serve as membrane models and primitive mockups of natural cells. With respect to the latter use, amphiphilic polymers can be used to replace phospholipids in order to introduce certain favorable properties, ultimately allowing for the creation of truly synthetic cells. These new properties also enable the employment of ne...
Although it is well known that solvent is one of the most important decision variables in liquid-liquid extraction processes, many previous studies focused on a specific class of solvents while neglecting alternatives. This work presents a comparative screening of two types of most extensively studied solvents, i.e., organic solvents (OS) and ionic...
A chemical plant layout for the production of syngas from renewable power, H 2 O and biogas, is presented to ensure a steady productivity of syngas with a constant H 2 -to-CO ratio under time-dependent electricity provision. An electrolyzer supplies H 2 to the reverse water-gas shift reactor. The system compensates for a drop in electricity supply...
The use of hydrogen as clean energy has attracted significant attention because conventional industrial hydrogen production processes show negative environmental impact, require intensive energy, and/or are dependent on natural gas. The main objective of this study is to develop an innovative and environment-friendly hydrogen production process uti...
A variety of artificial cells springs from the functionalization of liposomes with proteins. However, these models suffer from low durability without repair and replenishment mechanisms, which can be partly addressed by replacing the lipids with polymers. Yet natural membranes are also dynamically remodeled in multiple cellular processes. Here, we...
An integrated metal-organic framework (MOF) and pressure/vacuum swing adsorption (P/VSA) process design framework is presented for gas separation. It consists of two steps: descriptor optimization and MOF matching. In the first step, MOFs are represented as a large set of chemical and geometric descriptors from which the most influential ones are s...
A new method for integrated ionic liquid (IL) and absorption process design is proposed where a rigorous rate‐based process model is used to incorporate absorption thermodynamics and kinetics. Different types of models including group contribution models and thermodynamic models are employed to predict the process‐relevant physical, kinetic, and th...