Metal-organic frameworks have emerged as one of the key materials of interest over the last decade, with the number of publications and MOF structures registered with the Cambridge Crystallography database increasing year on year. One of the key reasons for this interest is the potential for very large internal surface areas of MOFs and the ability to tune pore sizes in order to target materials for the intended applications. The general range of surface areas of MOFs vary greatly, although a majority of MOFs exhibit surface areas of over 1000 m²g⁻¹, with an expected potential of possibly greater than 10000 m²g⁻¹ and large internal volumes, which in turn results in a number of useful properties for applications such as gas storage and separation, heterogeneous catalysis and even for use as medical devices. MOFs can also mimic some of the useful properties of zeolites such as molecular sieving, with the potential for tuneable pore sizes allowing a more optimal pore size for the selected application. However, MOFs are rarely produced at a large scale and are yet to become a viable alternative to current technologies. Here we have selected two archetypal MOFs to investigate, with the aim of producing continuous synthesis routes for these MOFs. We selected two MOFs with well documented syntheses in the literature in order to allow us to quickly ascertain the relative performance of our materials and optimise these. We also explore the possibilities of using unconventional heating methods such a microwave heating in order to exploit the potential benefits of this heating technique. MOF-5, with structure Zn₄O(BDC)₃ (BDC = benzene dicarboxylate) is one of the most commonly synthesized MOFs with potential applications such as hydrogen storage and catalysis. Here we showed that the formation mechanism of MOF-5 from solution is actually very complex and features multiple metastable crystalline phases. Importantly, we show that for MOF-5 formed through a common synthetic technique will always transition through at least one metastable crystalline phase before formation of MOF-5. Parameters affecting the synthesis of MOF-5 were then analysed and optimised in order to gain a deeper understanding of the process chemistry, how process intensification affects the final product and create a continuous MOF-5 synthetic procedure. We have demonstrated that MOF-5 can be formed continuously with high Langmuir Surface Areas (>2000 m² g⁻¹) while also producing yields of greater than 80%, giving space-time yield (STY) of 50 kg m³ day⁻¹ suggesting that MOF-5 should be scalable to a high degree. HKUST-1, Cu-BTC (BTC = benzene tricarboxylate), has the potential to be used in gas applications such as short chain hydrocarbon separation, hydrogen storage or purification and H₂S sequestration. Here we demonstrate a scalable continuous synthesis of HKUST-1 with a space time yield of 80 kg m³ day⁻¹ while maintain a Langmuir surface area of >2000 m² g⁻¹. Further optimisation of this system by varying the solid concentrations and the residence time was investigated. We then show that microwave heating can be used to produce HKUST-1 in several orders of magnitude faster than by conventional heating. The use of microwave technology for continuous production system of HKUST-1 enabled STY of 80000 kg m³ day⁻¹ and surface area of >1900 m² g⁻¹, thus strongly suggesting the significant benefits of combining continuous manufacture with microwave heating. We have shown that continuous production of two archetypal MOFs is possible, and optimised these systems while also comparing a number of key parameters in order to provide an overview of the potential benefits of process intensification and scale up. Further, we have highlighted clearly the potential benefits of using techniques such as microwave heating in order to exploit the beneficial changes to process chemistry of this heating method.

This thesis describes work done to investigate the influence of controlled fluid shear on the primary nucleation of glycine from aqueous solution. Crystallisation from solution is vital to many natural and industrial processes. It is widely used for separation and purification in industries such as chemicals, food and pharmaceuticals. Nucleation, which is the first step in the formation of a new crystalline solid phase from solution, is of fundamental importance in determining product crystal quality, however, at present it is poorly understood mechanistically. An improved understanding of nucleation and the effects of relevant industrial process parameters on nucleation pathways and resulting kinetics is therefore necessary to better design and optimise industrial applications of crystallisation. In industrial processes, fluid shear is widely encountered, for example through agitation in a vessel, or transport through pipes. The role of fluid shear on the primary nucleation of small organic compounds from solution has not been well studied to date so in this work, the influence of fluid shear on the primary nucleation of glycine, the smallest amino acid, is studied. Couette and capillary flow setups were used to obtain flow conditions which were well understood and quantifiable. Supersaturated aqueous glycine solutions were exposed to flow in these setups under isothermal conditions and induction times (time between the creation of supersaturation and the formation of a new crystalline phase) were measured. Efforts were taken to ensure that the first crystals formed through primary nucleation and the measured induction times were related to the rates of primary nucleation in the solutions. Dynamic light scattering measurements were also carried out to study the mesoscale clusters which exist in aqueous glycine solutions. The work carried out showed that fluid shear had a profound effect on the primary nucleation of glycine from aqueous solution, with exposure to fluid shear resulting in higher rates of primary nucleation. The onset of nucleation was associated with an increase in average mesoscale cluster size. It is proposed that exposure to fluid shear resulted in the coalescence of mesoscale clusters, with the larger coalesced clusters leading to a more rapid nucleation pathway.

Due to the material benefits in the reduction of the operating temperatures of SOFCs, development of novel electrolyte and electrode materials is deemed to be essential for SOFC performance optimisation at intermediate temperatures. Iron-based perovskites were previously overlooked as anode materials due to their instability in reducing atmospheres at SOFC operating temperatures, although substantial research has been conducted into the use of these materials as SOFC cathodes. The reduction in operating temperature allows for use of materials, such as iron-based perovskites, which lack the requisite thermal or redox stability for high temperature operation. Synthesis of iron rich strontium molybdenum ferrite double perovskites determined that the previously observed performance of these materials was intrinsically linked to initial high temperature reduction, thus reducing the utility of these materials at intermediate temperatures. XRD and DC conductivity measurements determined that doping of SrFeO₃₋δ with titanium and niobium produced the optimal balance between conductivity and stability for SrFe₀.₉(Ti,Nb)₀.₁O₃₋δ. Introduction of transition metal dopants further increased the electronic conductivity with copper doping exhibiting the highest electronic conductivity of the redox stable SrFe₃₋₀₉ ̣₁₈₆₄₂₇⁻²°₀.₈-x(TM)x(Ti,Nb)₀.₁O₃-δ materials. Increasing the copper content of SrFe₀.₈-xCu₀.₁+xNb₀.₁O₃-δ resulted in a reduction of the electronic conductivity. A-site doping with lanthanum replicated the structure and conductivity observed previously in the literature, with redox stability at intermediate temperature observed for both La₀.₆0.6Sr₀.₄FeO₃-δ and La₀.₈Sr₀.₂FeO₃-δ. Replacement of lanthanum with yttrium elicited a reduction in the electronic conductivity, with Y₀.₃Sr₀.₇FeO₃-δ exhibiting the highest electronic conductivity of the redox stable materials. Symmetrical fuel cell testing with 60:40 SrFe₀.₉Ti₀.₁O₃-δ-Gd₀.₂Ce₀.₈O₂-δ, 55:45 La₀.₆Sr₀.₄FeO₃-δ-Gd₀.₂Ce₀.₈O₂-δ and SrFe₀.₈Cu₀.₁Nb₀.₁O₃-δ electrodes recorded performances of 22 mWcm⁻², 80 mWcm⁻² and 306 mWcm⁻² respectively at 700 °C. The fuel cell performance of a symmetrical SrFe₀.₈Cu₀.₁Nb₀.₁O₃-δ-Gd₀.₂Ce₀.₈O₂-δ- SrFe₀.₈Cu₀.₁Nb₀.₁O₃-δ fuel cell was an improvement on the symmetrical fuel cell performance from the literature.

This research investigates the removal of aromatic organic contaminants (nitrobenzene (NB), aniline (AN), paracetamol (PCT) and hydroquinone (HQ)) from aqueous systems. For NB, this study focusses on removal via both iron reduction and adsorption, while removal of the other three compounds is focussed purely on adsorption. The results demonstrate NB degradation using iron powder produces AN, with the rate decreasing under basic conditions, due to corrosive effects; it is established that the iron surface is essential to the degradation process. Initial NB concentration influences degradation, and pseudo-first order kinetics are observed for all systems studied. For the adsorption studies on all four species, non-functionalised Macronet MN200, acidic functionalised hyper-cross-linked polymeric resins MN500 and S957, and Granular Activated Carbon (GAC) were tested as sorbents. The results show the kinetics of adsorption, for all contaminants, follow pseudo-second order models with rates controlled by particle diffusion. For adsorption of NB, PCT and HQ, the equilibrium uptake capacities increase with decreasing acidic functionalisation of the sorbent surface; while the opposite trend was obtained for AN removal. The adsorption rate decreased as sorbent acidic capacity increased, for all sorbents, due to the inherent surface chemistry and smaller surface area of the acidic functionalised sorbents used. For equilibria study, the Freundlich equation fits the data most appropriately and adsorption of all contaminants onto the selected sorbents is a physical process. Adsorption of NB, AN, and PCT onto the studied sorbents is favourable, while it is moderately favourable for HQ. Leaching tendencies showed < 40% of all contaminants were leached from the sorbents with the higher leaching rates for the macroporous sorbents. Overall, the results obtained suggest polymeric resins as viable candidates for the removal of targeted aromatic substances from aqueous systems.

With the world’s population increasing, fossil fuel resources are being consumed at an ever-increasing rate. At the same time, the globalization wave of recent years has also brought forward significant humanitarian and environmental concerns such as the depletion of other natural resources and climate change. With these problems in mind, the production of biofuels is seen as an alternative solution of strategic importance in many countries. The objective of this research is to propose a biofuel supply chain framework that aims to maximize profit and minimize environmental impact. This will be done by considering the various sub-components of the biofuel supply chain. Using the superstructure approach and supply chain block representation, a mathematical formulation is setup to analyse a biomass cultivation site, biomass storage and distribution facility, biofuel production plant, biofuel storage and distribution facility, by-product storage and distribution facility, and finally the customer. A case study on a wheat-to-bioethanol supply chain in the UK is proposed along with another case study on product distribution in the UK to test the validity and robustness of the proposed work. The result of the case studies shows that compared to traditional fossil fuels, biofuel is less competitive in terms of pricing due to the poor conversion ratio and high animal feed wheat price in the UK. However, the WTI Crude Oil price will increase in the long run and therefore, there will be good fighting chance for the biofuel supply chain to compete with the traditional fossil fuel supply chain in future. As for the biofuel distribution, a centralized distribution method is more cost effective when using diesel trucks for delivery. However, the use of electric trucks will give decentralized distribution an advantage in terms of costs. Overall, this research gives an overview of setting up a biofuel supply chain framework, where each of the sub-components is considered, together with other factors such as government policy and environmental impacts. Although biofuel may not be the most desirable energy source now, it still has great room for improvement in the future, with the advancement in technologies.

Currently there is no in vitro testing of glioblastoma biopsy material to assess tumour sensitivity to radiation, which could form a basis for personalised treatment plans for patients. In this work, a model to predict sensitivity to radiation, via the micronucleus assay, is set out and a proof of concept is presented where numbers of micronuclei in a glioblastoma cell line, LN18 is predicted. One key requirement for the model is that any in vitro testing needs to yield results within a few days, as the timeline for glioblastoma patients from diagnosis to treatment is short. In order to achieve this, a flow cytometry technique is assessed against traditional fluorescence microscopy for detection of micronuclei. Flow cytometry was completed using an in vitro Microflow kit from Litron Laboratories. There was no previous experience using this kit in cancerous cell lines and limited experience in cell lines that adhere to their flask’s surface as the kit is used mostly in peripheral blood lymphocytes. The flow cytometry technique can be completed within the required time frame and is much less labour intensive that fluorescence microscopy. However, there is a significant amount of variance between samples which makes the microscopy results more useful for fitting the modelling work to. It is expected with further experience and use of the supplied template, as this was incompatible at the time of the experiments, will play a role in reducing some of the variance. The model, in its current state of development, is able to predict numbers of micronuclei in a cohort of cells following doses of radiation between 1 and 3 Gy. The numerical solution is based on a decision tree structure where each double strand break that would be caused by radiation is run through the tree. The tree is traversed populated using probabilities for each decision, such as the success of a repair pathway, and Monte Carlo methods for predicting the cohort response to radiation. These probabilities are fitted to experimental data. The prediction of micronuclei is the first step for the MiNiMUS model. Future work should prioritise incorporating cell death into the model and further assessing the suitability of flow cytometry for rapid micronuclei detection.

The intention of the work was to develop easy to use technical design methods which are helpful for the daily work of the process engineer, and which also describe the operating behaviour of both the whole extruder and the individual processing sections. This goal was achieved by developing new models or the further developing of existing models. The examination of the developed models by trials and on production lines showed good accuracy of the models. The following models, which are developed in the present work, are of particular interest for the technical design of extruders: • Simple model for the calculation of the solids conveying capacity derived by trials. • Calculation of the melt transport in screw elements by simple models which are examined by test series with various extruder sizes, screw elements and polymers. • Design rules for screw elements used for melt discharge. • A model for the description of the degassing process was derived in terms of the operating equation of the degassing zone. The described operating equation shows a good agreement with degassing results obtained in various degassing trials. • Description of the operating behaviour of solid fed extruders and a simple assessment of the specific drive energy using the specific enthalpy rise. • Introduction of the mean shear stress at the barrel wall for melt fed co-rotating twin screw extruders and description of the operating behaviour by the operating equation. The influence of different feed temperatures and melt flow index values are also considered. • Scale-up for compounding and degassing tasks and the necessary restrictions to achieve the same results on test and production extruders. • Development of an analytical method for the design of extruder series by the optimal diameter ratio, dependent on whether the extruders are melt or solid fed.

Polymer electrolyte fuel cell (PEFC) performance is typically considered to have reached the targets required for most applications; however, maintaining this performance throughout the operational lifetime of the fuel cell, or restricting its degradation to an acceptable level, is still a challenge. One of the most important yet understudied areas identified as a source of fuel cell performance degradation is the bipolar plate (BPP). The BPP typically accounts for more than 80% of the weight of a stack and almost all of the volume. Thus BPP weight and size reduction, while maintaining the desired properties is crucial in increasing the performance, making fuel cells more commercially viable. Stainless steels BPPs are a popular choice, with the advantage of low cost, high strength and good corrosion resistance as well as ease of incorporating a flow field via stamping or embossing. The main criterion for material suitability with regards to stainless steel in particular, is large voltage drops at the interface; a consequence of corrosion protective insulating surface oxides. Surface modification/treatment techniques of inexpensive and widely available metals are capable of improving the performance of metals in fuel cell environments and are an alternative to the use of costly precious metal coatings. Electrochemical surface treatments involve modification of the oxide layer by enriching its chromium content, leading to higher corrosion resistance and lower interfacial contact resistance (ICR). This project explores the use of electrochemical surface treatment to improve the corrosion and contact resistance of 316 stainless steel (316 SS). The process is an anodic treatment, whereby the material is polarised positive of the transpassive region, under process conditions of H2SO4-to-glycerol ratio at varying treatment times. The surface treatment demonstrates an increase in the corrosion resistance, enhanced durability of the passive film and significantly reduces ICR (interfacial contact resistance), to values well below the DoE 2017 targets at a compression of 200 psi (138 N cm-2). While ex-situ near-surface characterisation suggests the improved properties of the electrochemically treated 316 SS are primarily as a consequence of Cr enrichment at the near-surface of the material. AFM analysis of surface roughness and morphology demonstrated increased Ra values of treated samples; which although has been previously associated with improved ICR, was not significant enough in this study to affect the ICR. The addition of glycerol as a viscosity-enhancing agent did not demonstrate a significant improvement of the process, while shorter treatment times demonstrated greater process current efficiencies, which consequently impact the economic costs. The process demonstrates that the use of anodized treated 316 SS to improve low ICR and satisfactory corrosion resistance of low cost metallic bipolar plate PEFCs is feasible.

Pressure swing adsorption (PSA) is a cyclic adsorption process for gas separation and purification, and can be used in a variety of industrial applications, for example, hydrogen purification and dehydration. PSA is, due to its low operational cost and its ability to efficiently separate CO2 from flue gas, a promising candidate for post-combustion carbon capture in power plants, which is an important link in the Carbon Capture and Storage technology chain. PSA offers many design possibilities, but to optimise the performance of a PSA system over a wide range of design choices, by experimental means, is typically too costly, in terms of time and resources required. To address this challenge, computer experiments are used to emulate the real system and to predict the performance. The system of PDAEs that describes the PSA process behaviour is however typically computationally expensive to simulate, especially as the cyclic steady state condition has to be met. Over the past decade, significant progress has been made in computational strategies for PSA design, but more efficient optimisation procedures are needed. One popular class of optimisation methods are the Evolutionary algorithms (EAs). EAs are however less efficient for computationally expensive models. The use of surrogate models in optimisation is an exciting research direction that allows the strengths of EAs to be used for expensive models. A surrogate based optimisation (SBO) procedure is here developed for the design of PSA systems. The procedure is applicable for constrained and multi-objective optimisation. This SBO procedure relies on Kriging, a popular surrogate model, and is used with EAs. The main application of this work is the design of PSA systems for CO2 capture. A 2- bed/6-step PSA system for CO2 separation is used as an example. The cycle configuration used is sufficiently complex to provide a challenging, multi-criteria example.

This thesis aims to address the optimal strategic design of bioenergy supply chains and provide insight into the future implications of these systems. Among the bioenergy supply chains, biomass-to-biofuel (as the main focus), biomass-to-bioelectricity and biomass-to-hydrogen routes are studied within the context of this thesis. To solve these problems, mathematical programming, especially mixed integer linear programming (MILP), models and solution approaches are developed. Regarding the biofuel supply chains, deterministic, spatially-explicit, static optimisation models are developed first based on single economic objective considering first and hybrid generation systems. A “neighbourhood” flow approach is also proposed for the solution of these models. This approach provides significant computational savings when compared to similar models in literature. The single objective modelling framework is then extended to a multi-objective optimisation model which considers economic and environmental objectives simultaneously. The multi-objective model can provide insight into the trade-offs between the two conflicting objectives. Finally, the single objective static model is further developed into deterministic and stochastic multi-period modelling frameworks to incorporate temporal effects such as change of demand and biomass availability with time as well as uncertainty related to different aspects such as biomass availability. Regarding the bioelectricity supply chains, a deterministic, spatially-explicit, static, multi-objective mathematical programming model is developed based on mixed integer nonlinear optimisation. This considers electricity generation through biomass enhanced carbon capture and storage (BECCS) systems. The model aims to address issues such as carbon tax levels required to incentivise decarbonisation in the power sector as well as the potential impacts of biomass availability and commodity (carbon and coal) prices. The biomass-to-hydrogen route is considered as one of the possible conversion pathways within a deterministic, spatially-explicit, multi-period model developed for the optimal strategic design of future hydrogen supply chains. A two-step hierarchical solution approach is also proposed to increase computational efficiency during the solution of the large scale problem. The model results provide insight into the optimal evolution of a hydrogen supply chain through time.