A significant challenge in large scale industrial production of butanol is its low product titer. Butanol needs to be purified to higher than 99% purity in order to be used for fuel applications. The focus of this study is to selectively remove water from butanol-water vapor to achieve fuel grade butanol in a pressure swing adsorption (PSA) system using biosorbents developed from agricultural byproduct canola meal (CM). CM was characterized by Fourier Transform Infrared Spectroscopy (FTIR) that CM contains polar groups such as hydroxyls, carboxyls, and amines in cellulose, hemi-cellulose and protein that have the potential for water adsorption. Physico-chemical characterizations were also done to understand the major composition, elemental make-up, devolatilization characteristics and particle size distribution of the CM used. The results demonstrated that biosorbent based on CM was able to successfully dry lower grade butanol and generate fuel grade butanol of over 99 v/v%. Five operating parameters were studied at two different levels to get the optimum process conditions for butanol drying, including temperature (95 and 111°C); pressure (135 and 201 kPa); feed butanol concentration (55 and 95 v/v %); feed flow rate (1.5 and 3 mL min-1) and particle size of adsorbent (0.425-1.18 mm and 4.7 mm pellets). Orthogonal array design (OAD) tool was used to design experiments and to evaluate the effects of these parameters. The performance of butanol dehydration was evaluated using five indices - water uptake; butanol uptake; water selectivity; butanol recovery; and maximum effluent butanol concentration in the effluent. The results demonstrated that feed butanol concentration, temperature and pressure were found to be the most significant factors overall, affecting most of the indices. The effects of individual operating parameters on each butanol dehydration index were determined and a set of optimum operating conditions were proposed by the range analysis of the orthogonal array design at 111oC, 135 kPa, feed butanol concentration of 55 v/v%, feed butanol-water liquid flowrate of 3 mL/min and biosorbent particle size of 0.43-1.18 mm. The experiments conducted at the above mentioned optimum conditions resulted in water uptake of 0.48 g/g-ads, water selectivity of 5.4, butanol recovery of 90%, and the maximum butanol concentration in the effluent being over 99 v/v% , which are better than that obtained at any other conditions investigated in this work. The Dubinin–Polanyi model based on adsorption potential theory displayed a goodness of fit to the water adsorption isotherm data with a r2 value of 0.95 and average relative error of just 3.5%. The mean free energy determined from the model was 0.02 kJ/mol indicated the adsorption is physical. Thermodynamic parameters were also evaluated which revealed that the water adsorption is exothermic and spontaneous. Water saturated adsorbent was regenerated at 110°C under vacuum and reusability was studied. The contribution of two major components of CM namely cellulose and protein were also examined for their capability to selectively remove water from butanol. The results showed both of them were able to dry water, however cellulose was found to have a higher water uptake and water selectivity than protein, indicating that it plays a major role in drying butanol. In order to compare the performance of CM on drying of butanol with other biomaterials, adsorption experiments were done using corn meal as adsorbent, which is one of the most common starch based biosorbents for ethanol drying. The results demonstrated that canola meal had a higher water uptake and water selectivity than corn meal. Use of CM over corn meal adsorbent is also desirable so as to avoid placing pressure on food consumption. In addition, drying of butanol using other cellulose based biosorbents such as oat hull was also explored. Oat hull demonstrated a potential to adsorb water and dehydrate butanol, which requires further in-depth investigation.

An adsorbent suitable for adsorption desalination cycles is essentially characterized by a hydrophilic and porous structure with high surface area where water molecules are adsorbed via hydrogen bonding mechanism. Silica gel type A++ possesses the highest surface area and exhibits the highest equilibrium uptake from all the silica gels available in the market, therefore being suitable for water desalination cycles; where adsorbent’s adsorption characteristics and water vapor uptake capacity are key parameters in the compactness of the system; translated as feasibility of water desalination through adsorption technologies. The adsorption characteristics of water vapor onto silica gel type A++ over a temperature range of 30 oC to 60 oC are investigated in this research. This is done using water vapor adsorption analyzer utilizing a constant volume and variable pressure method, namely the Hydrosorb-1000 instrument by Quantachrome. The experimental uptake data is studied using numerous isotherm models, i. e. the Langmuir, Tóth, generalized Dubinin-Astakhov (D-A), Dubinin-Astakhov based on pore size distribution (PSD) and Dubinin-Serpinski (D-Se) isotherm for the whole pressure range, and for a pressure range below 10 kPa, proper for desalination cycles; isotherms type V of the International Union of Pure and Applied Chemistry (IUPAC) classification were exhibited. It is observed that the D-A based on PSD and the D-Se isotherm models describe the best fitting of the experimental uptake data for desalination cycles within a regression error of 2% and 6% respectively. All isotherm models, except the D-A based on PSD, have failed to describe the obtained experimental uptake data; an empirical isotherm model is proposed by observing the behavior of Tóth and D-A isotherm models. The new empirical model describes the water adsorption onto silica gel type A++ within a regression error of 3%. This will aid to describe the advantages of silica gel type A++ for the design of adsorption desalination processes where reducing capital cost and footprint area are highly important parameters to take into account.

Activated carbon is an adsorbent that is commonly used for removing organic contaminants from air due to its abundant pores and large internal surface area. This thesis is concerned with the static adsorption capacity and adsorption kinetics for single and binary organic compounds on different types of activated carbon. These are important parameters for the design of filters and for the estimation of filter service life. Existing predictive models for adsorption capacity and kinetics are based on fundamental “hard” knowledge of adsorption mechanisms. These models have several drawbacks, especially in complex situations, and extensive experimental data are often needed as inputs. In this work we present a systematic approach that can contribute to the further development of predictive models, especially for complex situations. The approach is based on Multivariate Data Analysis (MVDA), which is ideally suited for the development of soft models without incorporating any assumptions about the mathematical form or fundamental physical principles involved. Adsorption capacity and adsorption kinetics depend on the properties of the carbon and the adsorbate as well as experimental conditions. Therefore, to make general statements regarding adsorption capacity and kinetics it is important for the resulting models to be representative of the conditions they will simulate. Accordingly, the first step in the investigations underlying this thesis was to select a minimum number of representative and chemically diverse organic compounds. The next steps were to study the dependence of the derived affinity coefficient, β, in the Dubinin-Radushkevich equation on properties of organic compounds and to establish a new, improved model. This new model demonstrates the importance of adding descriptors for the specific interaction with the carbon surface to the size and shape descriptors. The adsorption capacities of the same eight organic compounds at low relative pressures were correlated with compound properties. It was found that different compound properties are important in the various stages of adsorption, reflecting the fact that different mechanisms are involved. Ideal adsorbed solution theory (IAST) in combination with the Freundlich equation was developed to predict the adsorption capacities of binary organic compound mixtures. A new model was proposed for predicting the rate coefficient of the Wheeler-Jonas equation which is valid for breakthrough ratios up to 20%. Finally, it was shown that the Wheeler-Jonas equation can be adapted to describe the breakthrough curves of binary mixtures. New models were proposed for predicting its parameters, the adsorption rate coefficients, and the adsorption capacities for both components of the binary mixture. Thus, multivariate data analysis can not only be used to assist in the understanding of adsorption mechanisms, but also contribute to the development of predictive models of adsorption capacity and breakthrough time for single and binary organic compounds.

<p>Activated carbon is an adsorbent that is commonly used for removing organic contaminants from air due to its abundant pores and large internal surface area. This thesis is concerned with the static adsorption capacity and adsorption kinetics for single and binary organic compounds on different types of activated carbon. These are important parameters for the design of filters and for the estimation of filter service life. Existing predictive models for adsorption capacity and kinetics are based on fundamental “hard” knowledge of adsorption mechanisms. These models have several drawbacks, especially in complex situations, and extensive experimental data are often needed as inputs. In this work we present a systematic approach that can contribute to the further development of predictive models, especially for complex situations. The approach is based on Multivariate Data Analysis (MVDA), which is ideally suited for the development of soft models without incorporating any assumptions about the mathematical form or fundamental physical principles involved. </p><p>Adsorption capacity and adsorption kinetics depend on the properties of the carbon and the adsorbate as well as experimental conditions. Therefore, to make general statements regarding adsorption capacity and kinetics it is important for the resulting models to be representative of the conditions they will simulate. Accordingly, the first step in the investigations underlying this thesis was to select a minimum number of representative and chemically diverse organic compounds. The next steps were to study the dependence of the derived affinity coefficient, β, in the Dubinin-Radushkevich equation on properties of organic compounds and to establish a new, improved model. This new model demonstrates the importance of adding descriptors for the specific interaction with the carbon surface to the size and shape descriptors. The adsorption capacities of the same eight organic compounds at low relative pressures were correlated with compound properties. It was found that different compound properties are important in the various stages of adsorption, reflecting the fact that different mechanisms are involved. Ideal adsorbed solution theory (IAST) in combination with the Freundlich equation was developed to predict the adsorption capacities of binary organic compound mixtures. A new model was proposed for predicting the rate coefficient of the Wheeler-Jonas equation which is valid for breakthrough ratios up to 20%. Finally, it was shown that the Wheeler-Jonas equation can be adapted to describe the breakthrough curves of binary mixtures. New models were proposed for predicting its parameters, the adsorption rate coefficients, and the adsorption capacities for both components of the binary mixture. Thus, multivariate data analysis can not only be used to assist in the understanding of adsorption mechanisms, but also contribute to the development of predictive models of adsorption capacity and breakthrough time for single and binary organic compounds.</p>

Komposit-Adsorbentien, die aus einer mit hygroskopischem Salz imprägnierten Zeolithmatrix bestehen, bilden eine vielversprechende Materialklasse für die thermochemische Energiespeicherung (TCES). Sie vereinen die hohe Wärmespeicherdichte des Salzes und die einfache technische Handhabbarkeit des Zeoliths. Dabei verhindert die poröse Matrix das Auslaufen von Salzlösung und kompensiert volumenänderungen während der Ad- und Desorption. Das dynamische Sorptionsverhalten solcher Komposite unterscheidet sich jedoch von dem reiner Zeolithe. Speziell die Adsorptionskinetik ist langsamer, was zu Problemen wie einer geringeren und nicht konstanten thermischen Leistung sowie unvollständiger Adsorption und langen Adsorptionspasen von Energiespeichern auf Basis dieser Materialien führt. Numerische Modellierung hat sich als wichtiges Werkzeug erwiesen, um die Ursachen solcher Leistungseinschränkungen zu identifizieren. Dadurch erleichtert es die Entwicklung von thermochemischen Energiespeichern: Optimale Designs und Arbeitsbedingungen können per Simulation gefunden werden bevor Prototypen gebaut werden müssen. In dieser Arbeit wurde ein numerisches Modell einer Adsorbensschüttung in einer offenen Sorptionskammer entwickelt, in die Open-Sourve Finite-Elemente-Software OpenGeoSys implementiert und mittels experimenteller Daten validiert. Die Modellierungserebnisse zeigen, dass etablierte Sorptionskinetiken das dynamische Adsorptionsverhalten von Salz/Zeolith-Kompositen unter anwendungsrelevanten Arbeitsbedingungen erfassen. Außerdem zeigen sie, dass der Hauptgrund für die Unterschiede zwischen dem Sorptionsverhalten der Komposite und reiner Zeolithe in ihren qualitativ unterschiedlichen Sorptionsgleichgewichten liegt. Ein zweiter Fokus dieser Arbeit liegt darauf zu untersuchen, ob ein begrenzter Umfang an experimentellen Daten genügt, um die entwickelten numerischen Modelle zu kalibrieren. Diese Möglichkeit wurde durch Simulationen von dynamischen Adsorptionsvorgängen an Komposit-Adsorbentien bestätigt. Zudem wurden Kriterien entwickelt, die die Rekonstruktion eines robusten Adsorptionsgleichgewichtsmodells aus einem beschränkten expermientellen Datensatz erlauben. Schließlich wurde im Kontext der Dubinin-Polanyi-Theorie der Adsorption in Mikroporen festgestellt, das die Wahl eines bestimmten Adsorbatdichtemodells nur einen kleinen Einfluss auf Vorhersagen der Leistungsfähigkeit von Adsorbentien für die TCES hat. Die Ergebnisse dieser Arbeit bilden eine fundierte Grundlage für die zukünftige numerische Untersuchung von Materialien, Reaktorgeometrien und Arbeitsbedingungen während der Entwicklung von thermochemischen Energiespeichern, die auf Zeolithen oder Komposit-Adsorbentien basieren.:Used symbols and abbreviations 1. Introduction 2. Foundations 2.1. Thermochemical energy storage 2.2. Zeolites and salt/zeolite composites 2.3. Dubinin-Polanyi theory 2.4. Multiphysical model of a fixed adsorbent bed 2.5. Experimental data 3. Assessment of adsorbate density models 4. Water loading lift and heat storage density prediction 5. Modelling of sorption isotherms based on sparse experimental data 6. Modelling sorption equilibria and kinetics of salt/zeolite composites 7. Summary 7.1. Main achievements 7.2. Conclusions and outlook Bibliography A. Publications A.1. Assessment of adsorbate density models A.2. A comparison of heat storage densities A.3. Water loading lift and heat storage density prediction A.4. Modelling of sorption isotherms based on sparse experimental data A.5. Modelling sorption equilibria and kinetics of salt/zeolite composites / Composite adsorbents consisting of a zeolite host matrix impregnated with a hygroscopic salt are a promising material class for thermochemical energy storage (TCES). They combine the high heat storage density of the salt with the easy technical manageability of the zeolite, which prevents the leakage of salt solution and inhibits volume changes upon ad- and desorption. The dynamic sorption behaviour of such composites, however, is different from the pure host matrix material. Particularly, the adsorption kinetics are slower, which leads to issues such as low and non-steady thermal output power, incomplete adsorption and long adsorption phases of TCES devices using these composite materials. Numerical modelling has proven to be a valuable tool to identify the causes for such performance limitations. Therefore, it facilitates the development of TCES devices: it allows to easily find optimum designs and operating procedures before actual prototypes have to be built. In this thesis a numerical model of a packed adsorbent bed in an open sorption chamber has been developed, implemented in the open-source finite element software OpenGeoSys and validated with experimental data. The modelling results show that established sorption kinetics models capture the dynamic sorption behaviour of salt/zeolite composites under application-relevant operating conditions. Moreover, they show that the main cause for the differences between the composites' and pure zeolite's sorption behaviour lies in their different sorption equilibria. A second focus of the thesis is to investigate the use of limited experimental data for the calibration of the numerical models. This possibility has been confirmed by dynamic sorption simulations of the composite materials. Furthermore, criteria were determined that allow the reconstruction of a robust adsorption equilibrium description from a reduced experimental data set. Finally, in the context of the Dubinin-Polanyi theory of adsorption in micropores, it has been found that the choice of a specific adsorbate density model has only a small influence on performance predictions of adsorbents for TCES. In summary, the results from this thesis will facilitate the screening of materials, reactor geometries and operating conditions via numerical simulations during the design of TCES devices based on zeolites and composite sorbents.:Used symbols and abbreviations 1. Introduction 2. Foundations 2.1. Thermochemical energy storage 2.2. Zeolites and salt/zeolite composites 2.3. Dubinin-Polanyi theory 2.4. Multiphysical model of a fixed adsorbent bed 2.5. Experimental data 3. Assessment of adsorbate density models 4. Water loading lift and heat storage density prediction 5. Modelling of sorption isotherms based on sparse experimental data 6. Modelling sorption equilibria and kinetics of salt/zeolite composites 7. Summary 7.1. Main achievements 7.2. Conclusions and outlook Bibliography A. Publications A.1. Assessment of adsorbate density models A.2. A comparison of heat storage densities A.3. Water loading lift and heat storage density prediction A.4. Modelling of sorption isotherms based on sparse experimental data A.5. Modelling sorption equilibria and kinetics of salt/zeolite composites