Crystallisation is gaining a lot of interest in pharmaceutical industry to help designing active ingredients with tailored physicochemical properties. Many factors have been found to affect the crystallisation process, including process parameters and material attributes. Several studies in the literature have discussed the role of these parameters in the crystallisation process. A comprehensive study is still missing in this field where all the significant terms are taken into consideration, including the square effect and the interaction terms between different parameters. In this study, a thorough investigation into the main factors affecting crystallisation of a polymeric system, processed via injection moulding, was presented and a sample of response optimisation was introduced which can be mimicked to suite a specific need. Three grades of pure polyethylene oxide; 20K, 200K and 2M, were first characterised using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), powder X-ray diffraction (PXRD) and shear rheometry. The onset of degradation and the rate varied according to molecular weight of polyethylene oxide (PEO). The peak melting temperature and the difference in enthalpy between melting and crystallisation were both in a direct proportion with PEO molecular weight. PEO200K and PEO2M struggle to recrystallise to the same extent of the original state at the tested cooling rates, while PEO20K can retain up to a similar crystallinity degree when cooled at 1 °C/min. Onset of crystallisation temperature (Tc1) was high for PEO2M and the difference between the 20K and 200K were pronounced at low cooling rate (20K is higher than 200K). The rheometer study showed that PEO2M has a solid-like structure around melting point which explains the difficulty in processing this grade at a low temperature via IM. PEO20K was almost stable within the strain values studied (Newtonian behaviour). For higher grades, PEO showed a shear thinning behaviour. The complex viscosity for PEO2M is characterised by a steeper slope compared to PEO200K, which indicates higher shear thinning sensitivity due to higher entanglement of the longer chains. For binary blends of PEO, the enthalpy of crystallisation studied by DSC was in direct proportion to the lowest molecular weight PEO content (PEOL %) in PEO20K/200K and PEO20K/2M blends. The effect of PEOL% on Tc1 became slightly pronounced for PEO20K-2M blends where Tc1 exhibited slight inverse proportionality to PEOL% and it became more significant for PEO200K-2M blends. It was interesting to find that Tc1 for the blends did not necessarily lie between the values of the homopolymers. In all binary blends, Tc1 was inversely proportional to cooling rate for the set of cooling rates tested. Thermal analysis using hot stage polarised light microscopy yields different behaviours of various PEO grades against the first detection of crystals especially where the lowest grade showed highest detection temperature. Visual observation of PEO binary blends caplets processed at various conditions via injection moulding (IM) showed the low-quality caplets processed at mould temperature above Tc1 of the sample. The factors affecting crystallisation of injection moulded caplets were studied using response surface methodology for two responses; peak melting temperature (Tm) and relative change in crystallinity (∆Xc%) compared to an unprocessed sample. Mould temperature (Tmould) was the most significant factor in all binary blend models. The relationship between Tmould and the two responses was positive non-linear at the Tmould ˂ Tc1. Injection speed was also a significant factor for both responses in PEO20K-200K blends. For Tm, the injection speed had a positive linear relationship while the opposite trend was found for ∆Xc%. The interaction term found in the RSM study for all models was only between the injection speed and the PEOL % which shows the couple effect between these two factors. Molecular effect was considered a significant factor in all ∆Xc% models across the three binary blends. The order of ∆Xc% sensitivity to the change in PEOL% was 3, 5 and 7 % for 20K-200K, 200K-2M and 20K-2M.

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Practical restrictions on randomization are commonplace in industrial experiments due to the presence of hard-to-change or costly-to-change factors. Employing a split-plot design structure minimizes the number of required experimental settings for the hard-to-change factors. In this research, we propose classes of equivalent estimation second-order response surface split-plot designs for which the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. Designs that possess the equivalence property enjoy the advantages of best linear unbiased estimates and design selection that is robust to model misspecification and independent of the variance components. We present a generalized proof of the equivalence conditions that enables the development of several systematic design construction strategies and provides the ability to verify numerically that a design provides equivalent estimates, resulting in a broad catalog of designs. We explore the construction of balanced and unbalanced split-plot versions of the central composite and Box-Behnken designs. In addition, we illustrate the utility of numerical verification in generating D-optimal and minimal point designs, including split-plot versions of the Notz, Hoke, Box and Draper, and hybrid designs. Finally, we consider the practical implications of analyzing a near-equivalent design when a suitable equivalent design is not available. By simulation, we compare methods of estimation to provide a practitioner with guidance on analysis alternatives when a best linear unbiased estimator is not available. Our goal throughout this research is to develop practical experimentation strategies for restricted randomization that are consistent with the philosophy of traditional response surface methodology. / Ph. D.

Tsunami and storm surge are two of the main destructive and costly natural hazards faced by coastal communities around the world. To enhance coastal resilience and to develop effective risk management strategies, accurate and efficient tsunami and storm surge prediction models are needed. However, existing physics-based numerical models have the disadvantage of being difficult to satisfy both accuracy and efficiency at the same time. In this dissertation, several surrogate models are developed using statistical and machine learning techniques that can rapidly predict a tsunami and storm surge without substantial loss of accuracy, with respect to high-fidelity physics-based models. First, a tsunami run-up response function (TRRF) model is developed that can rapidly predict a tsunami run-up distribution from earthquake fault parameters. This new surrogate modeling approach reduces the number of simulations required to build a surrogate model by separately modeling the leading order contribution and the residual part of the tsunami run-up distribution. Secondly, a TRRF-based inversion (TRRF-INV) model is developed that can infer a tsunami source and its impact from tsunami run-up records. Since this new tsunami inversion model is based on the TRRF model, it can perform a large number of tsunami forward simulations in tsunami inversion modeling, which is impossible with physics-based models. And lastly, a one-dimensional convolutional neural network combined with principal component analysis and k-means clustering (C1PKNet) model is developed that can rapidly predict the peak storm surge from tropical cyclone track time series. Because the C1PKNet model uses the tropical cyclone track time series, it has the advantage of being able to predict more diverse tropical cyclone scenarios than the existing surrogate models that rely on a tropical cyclone condition at one moment (usually at or near landfall). The surrogate models developed in this dissertation have the potential to save lives, mitigate coastal hazard damage, and promote resilient coastal communities. / Doctor of Philosophy / Tsunami and storm surge can cause extensive damage to coastal communities; to reduce this damage, accurate and fast computer models are needed that can predict the water level change caused by these coastal hazards. The problem is that existing physics-based computer models are either accurate but slow or less accurate but fast. In this dissertation, three new computer models are developed using statistical and machine learning techniques that can rapidly predict a tsunami and storm surge without substantial loss of accuracy compared to the accurate physics-based computer models. Three computer models are as follows: (1) A computer model that can rapidly predict the maximum ground elevation wetted by the tsunami along the coastline from earthquake information, (2) A computer model that can reversely predict a tsunami source and its impact from the observations of the maximum ground elevation wetted by the tsunami, (3) A computer model that can rapidly predict peak storm surges across a wide range of coastal areas from the tropical cyclone's track position over time. These new computer models have the potential to improve forecasting capabilities, advance understanding of historical tsunami and storm surge events, and lead to better preparedness plans for possible future tsunamis and storm surges.

In the past few years, the demands for high speed semiconductor integrated circuits have warranted new techniques in their fabrication process which will meet the ever-shrinking dimensions. The gaseous plasma assisted etching is one of these revolutionary processes. However, the plasma and the etch process are very complex in nature. It has been very difficult to understand various species present in the plasma and their role in the etch reaction. In addition, the submicron geometries also require interconnect materials which will satisfy the necessary properties such as thermal stability and low electrical resistance. Titanium (Ti) and titanium nitride (TiN) are widely used as barriers between aluminum (Al) and silicon (Si) to prevent the destructive intermixing of these two materials. The process of patterning of the interconnect containing Ti and TiN along with Al has been a challenge to the semiconductor process engineers. Therefore, complete characterization of the plasma etch process of Ti and TiN films and development of mathematical models to represent the responses such as the etch rate and uniformity is necessary for a good understanding of the etching process. A robust and well controlled metal etch process usually results in good die yield per wafer and hence can translate into higher profits for the semiconductor manufacturer. The objective of this dissertation is to characterize the plasma etch processes of Ti and TiN films in chlorine containing plasmas such as BCl₃ and Cl₂/N₂ and to develop mathematical models for the etch processes using statistical experimental design and analysis technique known as Response Surface Methodology (RSM). In this work, classical experiments are conducted on the plasma etch process of Ti and TiN films by varying the process parameters, such as gas flow, radio frequency (RF) power, reaction pressure, and temperature, one parameter at a time, while maintaining the other parameters constant. The variation in the etch rate with the change in the process parameter of the film is studied and the results were explained in terms of the concepts of plasma. These experiments, while providing very good understanding of the main effects of the parameters, yield little or no information on the higher order effects or interaction between the process parameters. Therefore, modern experimental design and analysis techniques using computerized statistical methods need to be employed for developing mathematical models for these complex plasma etch processes. The second part of this dissertation concentrates on the Design and Analysis of Experiments using Response Surface Methodology (RSM) and development of models for the etch rate and the etch uniformity of the Ti and TiN films in chlorine-containing plasmas such as Cl₂/N₂ and Cl₂/N₂/BCl₃. A complete characterization of the plasma etch process of Ti and TiN films is achieved with the RSM technique and a well fitting and statistically significant models have been developed for the process responses, such as the etch rate and the etch uniformity. These models also provide a means for quantitative comparison of main effects, which are also known as first order effects, second order effects and two factor interactions. The models, thus developed, can be effectively used for an etch process optimization, prediction of the responses without actually conducting the experiments, and the determination of process window. This dissertation work has achieved a finite study of the plasma etch process of Ti and TiN films. There is tremendous potential and scope for further research in this area, limited only by the available resources for wafer processing. A few of the possibilities for further research is discussed in the next few sentences. The optimized process derived from the RSM technique needs to be implemented in the actual production process of the semiconductor ICs and its effects on the wafer topography, etch residue and the resulting die yield have to be studied. More research studies are needed to examine the effect of process parameters such as temperature, the size and shape of the etch chamber, the quality of the film being etched, among other parameters. It is worth emphasizing in this respect that this dissertation marks beginning of research work into the ever-increasing complexities of gas plasma. / Ph. D.

This dissertation addresses the surging global demand for sustainable energy alternatives and biobased products, driven by population growth and the imperative to shift away from finite fossil fuels amidst climate change. The research centers on the catalytic upgrading of rice straw bio-oil, employing bimetallic magnetic nano-catalysts on rice straw-derived biochar to align with the imperative for environmentally conscious energy solutions. In the initial phase, the study systematically explores upgrading processes using varied alcohols, specifically ethanol, and butanol, under mild conditions to enhance bio-oil quality. The detailed evaluation of catalyst composition reveals a notable reduction in oxygen content, coupled with a significant increase in energy density and calorific value. The upgraded bio-oil not only exhibits heightened stability but also undergoes a substantial shift towards a more desirable hydrocarbon-rich composition. The second part of the research optimizes upgrading process parameters catalyst concentration, reaction holding time, and reaction temperature using Response Surface Methodology based on the Box-Behnken experimental design. This optimization refines the catalytic upgrading process, enhancing its efficiency and reliability. Beyond catalytic efficacy, the study considers the magnetic recovery of catalysts for potential reuse, emphasizing sustainability on a broader scale. Set against the backdrop of global energy challenges, this research significantly contributes to advancing the understanding of bimetallic magnetic nano-catalysts. The dissertation unfolds in two parts, with the first segment focusing on Catalytic Upgrading of Rice Straw Bio-Oil via Esterification in Supercritical Ethanol Over Bimetallic Catalyst (CuO-Fe3O4/AcB), involving the variation of Cu and Fe metals on Rice Straw Biochar without hydrogen gas. The exploration continues with the Upgrading of Rice Straw Bio-Oil in Butanol and hydrogen gas Over a Sustainable Magnetic Bimetallic Nano-Catalyst (ZrO2-Fe3O4/AcB). The integrated analytical approach, utilizing XRD, SEM, FT-IR for synthesized catalysts, alongside GC-MS and the Bomb Calorimeter for bio-oil samples, establishes a nuanced understanding crucial for optimizing catalytic performance in sustainable biofuel production.

Ces derniers temps, des procédés commerciaux basés sur la technologie photocatalytique, sont arrivés sur le marché, afin de satisfaire la demande croissante du traitement de l’air intérieur. L’objectif de ce présent travail est de développer une nouvelle méthodologie pour évaluer l’efficacité de ce nouveau procédé. Pour l’étude de l’application de la photocatalyse au traitement de l’air intérieur, un dispositif expérimental a été mis au point et deux méthodes analytiques ont été développées (ATD-GCMS et GC-PDHID). La performance de la dégradation photocatalytique du 2-propanol et du toluène à faibles concentrations (ppbv) a été étudiée. L’influence des différents paramètres (humidité relative, débit, concentration initiale, etc.) et leurs interactions sur la conversion, la formation des intermédiaires et la minéralisation au CO2 a été établie / Many commercial systems based in the photocatalytic technology have reached the market recently in order to address the growing demand for improve poor indoor air qualities. The present work deals with the development of a new methodology in order to evaluate the efficiency of this process. For the study of photocatalytic oxidation for indoor air applications, an experimental set-up was designed and two analytical tools (ATD-GC-MS and GC-PDHID) were developed. The performance of the photocatalytic treatment of 2-propanol and toluene at indoor air concentrations levels (ppbv) were realised. The influence of several parameters and their interactions effects on the conversion, by-product formation and mineralization to CO2 were established

Millimeterstora och svårupptäckta defekter kan uppstå internt i stora och komplexa gjutgods av Ti-6Al-4V, ibland går dessa oupptäckta tills detaljen genomgått mekanisk bearbetning och en stor kostnad redan har gått in i den. Dessa defekter och andra industriella olyckshändelser leder till ett behov av additiva reparationsmetoder där den för tillfället rådande metoden är TIG-svetsning. Denna metod reparerar defekterna men leder till oacceptabla restspänningar vilka kan åtgärdas med värmebehandling som i sin tur kan orsaka ytdefekten alpha case. Därav finns ett industriellt behov av reparationsmetoder som leder till mindre eller negligerbara restspänningsnivåer i reparerad detalj. Detta arbete utfört hos GKN Aerospace – Engine Products Sweden i Trollhättan analyserar eventuella förhållanden mellan parametrarna Effekt, Spot size, och Svetshastighet och de resulterande restspänningarna i ett lågparameterområde på materialet Ti-6Al-4V. En parameterrymd uppspänd av 17 parameteruppsättningar etablerades, svetsades och analyserades med mikrografi. Ur denna rymd simulerades de 8 yttre parametrarna med hjälpa av Finita Elementmetoden i svetssimuleringsmjukvaran MARC och ett förhållande mellan ingående parametrar och resulterande restspänningar undersöktes. En statistiskt säkerställd trend erhölls för att en minskad Svetshastighet leder till minskade tvärspänningar i mitten på en 20mm lång svetssträng. Detta är applicerbart för svetsar nyttjande start och stopplåtar. Det noterades även att en ökning i Effekt eller Spot size, eller en minskning utav svetshastigheten leder till att det av restspänningar utsatta området ökar i storlek. Detta är har implikationer för efterföljande värmebehandling i avgörandet av form och storlek på området som skall värmebehandlas. / Minute defects may occur in large complex Ti-6Al-4V castings, sometimes these are unnoticed until after machining and a high cost has been sunk into the part. These defect and other potential manufacturing mishaps render a need for additive repair methods. The state of the art method TIG welding can repair the parts but may leave unacceptable residual stresses, where the state of the art solution of Post Weld Heat Treatment might create a surface defect known as alpha case. Therefore there is a need for a repair weld method that results in lesser or negligible residual stresses. This thesis, carried out at GKN Aerospace – Engine Products Sweden, Trollhättan analyses the potential relationships between the laser welding parameters Power, Spot size, and Weld speed and the resulting residual stresses in a low energy parameter area on the material Ti-6Al-4V. A parameter box of 17 parameter sets was established, laid down and analyzed under micrograph, of this box the outer 8 parameter sets were simulated via the Finite Element Analysis welding simulation software MARC and a relationship between the input parameters and their resulting residual stresses was analyzed. A statistically significant trend was found supporting the claim that a decrease in transversal stresses in the center of a 20mm weld line is caused by an increase in Weld speed. This has implications for welds using run-on & run-of plates. It was also noted that an increase in Power or Spot size, or a decrease in Weld speed increases the area under residual stress; both as individual parameters and in synergy. This has implications for Post Weld Heat Treatment in determining the size and shape of the area in need of treatment.

New GC-MS method combined with SPE preconcentration step has been developed and optimized for the determination of selected fluorotelomer alcohols in aqueous samples by advanced statistical method in this thesis. 1H,1H,2H,2H-perfluoro-1-octanol (6:2 FTOH) and 1H,1H,2H,2H-perfluoro-1-decanol (8:2 FTOH) have been selected as the analytes. The influence of several factors, such as the sample volume, the carrier gas pressure, the sampling time and the injector temperature on the system response have been studied during the optimization. Utilizing the statistical software Minitab 16 and series of experiments, the optimal values of relevant factors and a suitable type of ionization were found for both analytes. Limits of detection of GC-MS method are 0.24 ng/mL for 6:2 FTOH and 0.42 ng/mL for 8:2 FTOH. Several factors, such as the type and the volume of conditioning agent, the speed of conditioning, the speed of sample flow, the method of column drying, the type and the volume of eluent have been tested for SPE. The optima of these factors were determined using Minitab 16 software. The extraction efficiency dependence on the concentration and volume of the stock solution was used to set the limitation of SPE for the determination of fluorotelomer alcohols. The maximum volume of sample equals to 400 mL...