SYNTHESIS AND CHARACTERIZATION OF MAGNESIUM - TITANIUM COMPOSITES BY SEVERE PLASTIC DEFORMATION

Magnesium alloys are widely used in engineering applications, including aerospace and automobile industries, due to their desirable properties, such as lower density, high damping capacity, relatively high thermal conductivity, good machinability, and recyclability. Researchers have, therefore, been developing new magnesium materials. However, mechanical and corrosion properties are still limiting many commercial applications of magnesium alloys. In this Ph.D. thesis research, I developed Mg-Ti composite materials to offer some solutions to further improve the mechanical behavior of magnesium, such as titanium-magnesium (Ti-Mg) claddings, Mg-Ti multilayers, and Ti particle enforced Mg alloys. Low cost manufacturing processes, such as hot roll-bonding (RB) and accumulative roll-bonding (ARB) techniques, were used to produce Mg-Ti composites and sheets. The microstructural evolution and mechanical properties of composites were investigated using optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), electron backscatter diffraction (EBSD), nanoindentation, and tensile tests. In the first part of this study, I investigated the bonding strength of the AZ31/Ti to understand the mechanical properties of Mg/Ti composites. Using a single pass RB process, I fabricated AZ31/Ti multilayers with the thickness reduction in a range of 25% to 55%. The hot-rolled AZ31/Ti multilayers were heat-treated at 400 °C for 6, 12, and 24 hours, respectively, in an argon atmosphere. Tensile-shear tests were designed to measure the bonding strength between AZ31/Ti multilayers. Furthermore, the experimental results revealed good bonding of the AZ31/Ti multilayers without forming any intermetallic compounds in the as-rolled and heat-treated AZ31/Ti multilayers. The good bonding between Ti and AZ31 is the result of diffusion bonding whose thickness increases with increasing heat-treatment time and thickness reduction. The shear strength of the Ti/AZ31 multilayer increases with increasing bonding layer thickness. In the second part of this study, I characterized the microstructure and texture of three-layered Ti/AZ31/Ti clad sheets which were produced by single-pass hot rolling with a reduction of thickness 38% (sheet I) and 50% (sheet II). The AZ31 layer in sheets I and II exhibited shear bands and tensile twins {1012}⟨1001⟩ . The shear bands acted as local strain concentration areas which led to failure of the clad sheets with limited elongation. Heat treatment caused changes in the microstructure and mechanical properties of clad sheets due to static recrystallization (SRX) on twins and shear bands in the AZ31 layer. Recrystallized grains usually randomize the texture which causes weaken the strong deformed (0001) basal texture. Twins served as nucleation sites for grain growth during SRX. Tensile tests at room temperature showed significantly improved ductility of the clad sheets after heat treatment at 400°C for 12h. The results showed that the mechanical properties of clad sheets II are better than clad sheet I: The clad sheet II shows elongation 13% and 35% along the rolling direction (RD) for as-rolled and annealed clad sheet, respectively whereas the clad sheet I shows elongation 10% and 22% along RD for as-rolled and annealed clad sheet, respectively. In the final part of this study, I examined the effects of dispersed pure titanium particles (150 mesh) with 0, 2.3, 3.5, 4.9, and 8.6 wt. % on the microstructure and mechanical properties of AZ31-Mg alloy matrix. Mg-Ti composites were processed through three accumulative roll bonding (ARB) steps using thickness reductions of 50% in each pass followed by heat treatment at 400 °C for 12 h in an argon atmosphere. ARB is an efficient process to fabricate Mg-Ti composites. Mechanical properties of Mg- 0Ti and Mg-2.3Ti composite were enhanced by ~ 8% and 13 % in yield strength and ~ 30% and 32 % in ultimate tensile strength, respectively. Meanwhile, the elongation of the composites were decreased by 63% and 70%, respectively. After heat treatment, the results showed a decrease in yield strength and increase in elongation to fracture. The mechanical properties of the Mg-0 and Mg-2.3Ti composite were enhanced: ultimate tensile strength by 9% and 7%, and elongation by 40% and 67%, while the yield strength was decreased by 28% and 36% compared with the initial AZ31. Enhancements of strength and ductility were the results of two mechanisms: a random matrix texture by ARB and ductile titanium particle dispersion

Alignment, Clustering and Extraction of Structured Motifs in DNA Promoter Sequences

A simple motif is a short DNA sequence found in the promoter region and believed to act as a binding site for a transcription factor protein. A structured motif is a sequence of simple motifs (boxes) separated by short sequences (gaps). Biologists theorize that the presence of these motifs play a key role in gene expression regulation. Discovering these patterns is an important step towards understanding protein-gene and gene-gene interaction thus facilitates the building of accurate gene regulatory network models. DNA sequence motif extraction is an important problem in bioinformatics. Many studies have proposed algorithms to solve the problem instance of simple motif extraction. Only in the past decade has the more complex structured motif extraction problem been examined by researchers. The problem is inherently challenging as structured motif patterns are segmented into several boxes separated by variable size gaps for each instance. These boxes may not be exact copies, but may have multiple mismatched positions. The challenge is extenuated by the lack of resources for real datasets covering a wide range of possible cases. Also, incomplete annotation of real data leads to the discovery of unknown motifs that may be regarded as false positives. Furthermore, current algorithms demand unreasonable amount of prior knowledge to successfully extract the target pattern. The contributions of this research are four new algorithms. First, SMGenerate generates simulated datasets of implanted motifs that covers a wide range of biologically possible cases. Second, SMAlign aligns a pair of structured motifs optimally and efficiently given their gap constraints. Third, SMCluster produces multiple alignment of structured motifs through hierarchical clustering using SMAlign\u27s affinity score. Finally, SMExtract extracts structured motifs from a set of sequences by using SMCluster to construct the target pattern from the top reported two-box patterns (fragments), extracted using an existing algorithm (Exmotif) and a two-box template. The main advantage of SMExtract is its efficiency to extract longer degenerate patterns while requiring less prior knowledge, about the pattern to be extracted, than current algorithms

Budget impact analysis of upadacitinib for the management of moderate-to-severe atopic dermatitis in patients treated with systemic therapies in the United States

Objective: This study evaluated the budget impact of introducing upadacitinib for patients with uncontrolled moderate-to-severe atopic dermatitis (AD) from a United States (U.S.) private payer perspective. Methods: The model estimated costs before and after the adoption of upadacitinib for a hypothetical one million covered lives over 3 years. The model included immunosuppressant agents and dupilumab. Market uptake was assumed to be 2% per year. Treatments incur a cost for drug acquisition, and the costs associated with drug administration, laboratory testing, and clinic visits. The model calculated the impact on the budget in 2022 U.S. dollars. Various assumptions on market uptake were analyzed, and a sensitivity analysis was performed. Results: For one million covered lives with an estimated 3607 people receiving immunosuppressant agents or dupilumab, the total cost after introducing upadacitinib increased by $3.5,$7.0, and $10.5 million in years 1–3, respectively, resulting in a cumulative increase of$21.1 million over 3 years. The incremental per member per year costs were $3.52,$7.04, and $10.59 in years 1–3, respectively, resulting in an increase in per member per month costs of$0.29 in year 1, $0.59 in year 2, and$0.88 in year 3. The incremental per treated member per month costs were $70.77,$140.72, and $210.67 in years 1–3, respectively. Scenario and sensitivity analyses confirmed the model robustness. Conclusions: The introduction of upadacitinib had a high impact on the U.S. private payer budget. The use of upadacitinib may increase the cost of treating patients with uncontrolled moderate-to-severe AD

Determining the performance characteristics of flat plate and photovoltaic thermal collector for sustainable cooling systems integration

Improvement of the overall performance of solar cooling systems is achievable by optimising inlet conditions for the highest thermal efficiency of solar collectors such as flat plate collectors (FPC) and photovoltaic thermal collectors (PVT). This study has highlighted the recent advances in the field of solar absorption cooling systems from the point of view of the solar collector's types and has conducted an extensive review of the use of FPC and PVT for absorption cooling systems. The aim of this study is to investigate and optimise the thermal efficiency of FPC and PVT for sustainable cooling systems. The effect of inlet temperature (Tin) and flowrate (m ̇) on thermal efficiency (η_th) of FPC was investigated. Computational Fluid Dynamics (CFD) was employed to simulate a FPC and the results validated with experimental data from literature. Increasing inlet water temperature of FPC from 298 K to 370 K reduced thermal efficiency by 30%. There was no significant impact when the total flowrate of FPCs exceeded 36.4 x10-3 kg/s/m2. CFD was also employed to simulate a PVT and was validated by the literature. The effect of Tin and m ̇ on thermal efficiency(η_th) and electrical efficiency (η_elc) for the PVT was investigated. Increasing inlet water temperature of PVT from 273 K to 373 K reduced thermal efficiency by 7% while there was a significant reduction in electrical efficiency by 45% due to the increase in photovoltaic layer temperature. There was no significant impact when the total flowrate of the PVT exceeded 35 x10-3 kg/s/m2. The inlet conditions of FPC and PVT were optimised for the highest efficiency in accordance with the minimum absorption cooling driving temperature currently available in the market. A multi-objective optimisation study was applied to the computational model of the FPC by employing the response surface optimisation method in ANSYS16.1. The optimum flowrate of the FPC was m ̇=0.0067 kg/s/m2 with an inlet temperature of 321 K for thermal efficiency of 84 %. A multi-objective optimisation study was also applied to the computational PVT model. The optimum flowrate of the PVT was m ̇=0.0165 kg/s/m2 with an inlet temperature of 337.36 K for thermal and electrical efficiency of 81.32 % and 11.26 % respectively. The study has managed to optimise inlet conditions for FPC and PVT coupled with a cooling system at specified conditions. Optimising the inlet conditions has a significant impact to increase solar coefficient of performance (SCOP)

Determining the performance characteristics of flat plate and photovoltaic thermal collector for sustainable cooling systems integration

Improvement of the overall performance of solar cooling systems is achievable by optimising inlet conditions for the highest thermal efficiency of solar collectors such as flat plate collectors (FPC) and photovoltaic thermal collectors (PVT). This study has highlighted the recent advances in the field of solar absorption cooling systems from the point of view of the solar collector's types and has conducted an extensive review of the use of FPC and PVT for absorption cooling systems. The aim of this study is to investigate and optimise the thermal efficiency of FPC and PVT for sustainable cooling systems. The effect of inlet temperature (Tin) and flowrate (m ̇) on thermal efficiency (η_th) of FPC was investigated. Computational Fluid Dynamics (CFD) was employed to simulate a FPC and the results validated with experimental data from literature. Increasing inlet water temperature of FPC from 298 K to 370 K reduced thermal efficiency by 30%. There was no significant impact when the total flowrate of FPCs exceeded 36.4 x10-3 kg/s/m2. CFD was also employed to simulate a PVT and was validated by the literature. The effect of Tin and m ̇ on thermal efficiency(η_th) and electrical efficiency (η_elc) for the PVT was investigated. Increasing inlet water temperature of PVT from 273 K to 373 K reduced thermal efficiency by 7% while there was a significant reduction in electrical efficiency by 45% due to the increase in photovoltaic layer temperature. There was no significant impact when the total flowrate of the PVT exceeded 35 x10-3 kg/s/m2. The inlet conditions of FPC and PVT were optimised for the highest efficiency in accordance with the minimum absorption cooling driving temperature currently available in the market. A multi-objective optimisation study was applied to the computational model of the FPC by employing the response surface optimisation method in ANSYS16.1. The optimum flowrate of the FPC was m ̇=0.0067 kg/s/m2 with an inlet temperature of 321 K for thermal efficiency of 84 %. A multi-objective optimisation study was also applied to the computational PVT model. The optimum flowrate of the PVT was m ̇=0.0165 kg/s/m2 with an inlet temperature of 337.36 K for thermal and electrical efficiency of 81.32 % and 11.26 % respectively. The study has managed to optimise inlet conditions for FPC and PVT coupled with a cooling system at specified conditions. Optimising the inlet conditions has a significant impact to increase solar coefficient of performance (SCOP)

3D Modelling and Simulation of Reactive Fluidized Beds for Conversion of Biomass with Discrete Element Method

The use of biomass as a CO2–neutral renewable energy source gains more importance due to the decreasing resources of fossil fuels and their impact on the global warming. The thermochemical conversion of biomass in fluidized beds offers an economic and sustainable contribution to the global energy supply. Although the fluidized bed has reached a commercial status since many decades ago, its hydrodynamic behaviour is not completely understood. The availability of detail experimental information from real facilities is extremely difficult because the lack of accessibility, the measurement costs and the associated inevitable reduction in production. The numerical simulation provides an effective complement to the costly measurements. This requires besides the calculation of a gas-solid flow, an accurate description of particle–particle/wall collisions. Furthermore, kinetic models for pyrolysis, homogenous reactions, heterogeneous reactions and the related heat and mass transfer processes should be considered. Basically, there are two different methods for the representation of the gas–solid flow, viz. Euler–Euler and Euler–Lagrange models. The solid phase is treated as a continuum in the Euler–Euler model, while each particle trajectory is determined in the Euler–Lagrange model. In the Euler–Euler approach, the single particle-particle or particle-wall collision can be considered using additional assumptions. In the Euler–Lagrange approach, the particle-particle/wall collisions can be stochastically modeled or deterministically detected. The aim of this study is to develop a 3D program for the numerical simulation of biomass conversion in fluidized beds. The particle–particle/wall and gas–solid interactions are modeled by tracking all individual particles. For this purpose, the deterministic Euler–Lagrange/discrete element method (DEM) is applied and further developed. The fluid–particle interaction is studied using a new procedure, known as the offset method. The proposed method is highly precise in determining the interaction values, thus improving the simulation accuracy up to an order of magnitude. In this work, an additional grid, so-called particle grid, in which the physical values of solid phase is computed, is introduced. The suggested procedure allows the variation of the fluid grid resolution independent of the particle size and consequently improves the calculation accuracy. The collision detection between particle–particle/wall is performed with the aid of the particle search grid method. The use of the particle search grid method enhances the efficiency of collision detection between collision partners. The improved Euler–Lagrange/DEM model is validated towards the measurements obtained from a cold quasi–2D fluidized bed. The results suggest that the extended Euler–Lagrange/DEM model can predict accurately the motion of particles and the gas bubble expansion in the bed. The received results from the DEM model are also compared with other numerical approaches, namely the Euler-Euler and stochastic Euler–Lagrange models. Compared to measurements, the results show that the Euler–Euler model underestimates the bubble sizes and the bed expansions, while the stochastic Euler–Lagrange model reaches faster the maximum bed expansions. The efficiency and accuracy of the Euler–Lagrange/DEM model is investigated in detail. Parameter studies are carried out, in which stiffness coefficient, fluid time step and processor number are varied for different particle numbers and diameters. The obtained results are compared with the measurements in order to derive the optimum parameters for Euler–Lagrange/DEM simulations. The results suggest that the application of higher stiffness coefficients (more than 10^5 N/m) improves the simulation accuracy slightly, however, the average computing time increases exponentially. For time intervals larger than five milliseconds, the results show that the average computation time is independent of applied fluid time step, while the simulation accuracy decreases extremely by increasing the size of fluid time step. The use of fluid time steps smaller than five milliseconds leads to negligible improvements in the simulation accuracy, but to exponential rise in the average computing time. The parallel calculation accelerates the Euler–Lagrange/DEM simulation if the critical number of domain decomposition is not reached. Exceeding this number, the performance is not anymore proportional to the number of processors and the computational time increases again. The critical number of domain decomposition depends on particle numbers. An increase in solid contents results in a shift of critical decomposition number to higher numbers of CPUs. The local concentrations of solid and gaseous species, the local gas and particle temperatures, the local heat release and heat transfer rates can also be calculated with the developed program. In combination with the simulation of the gas–solid flow, it is possible to model the biomass conversion in the fluidized bed. Three series of warm simulations in a quasi–2D fluidized bed model are performed, viz. combustion with fuel gas without and with inert sand particles as well as combustion with solid fuel (a mixture of inert sand and pine wood particles). The received results realise the coupling of the Euler–Lagrange/DEM model with chemical reaction mechanism. The extended Euler–Lagrange/DEM model under the consideration of thermochemical reaction model is able to simulate, by the same token, the conversion of other solid fuels such as coal in fluidized beds

Translational use of homing peptides: Tumor and placental targeting

HypothesisTissue-specific homing peptides have been shown to improve chemotherapeutic efficacy due to their trophism for tumor cells. Other sequences that selectively home to the placenta are providing new and safer therapeutics to treat complications in pregnancy. Our hypothesis is that the placental homing peptide RSGVAKS (RSG) may have binding affinity to cancer cells, and that insight can be gained into the binding mechanisms of RSG and the tumor homing peptide CGKRK to model membranes that mimic the primary lipid compositions of the respective cells.ExperimentsFollowing cell culture studies on the binding efficacy of the peptides on a breast cancer cell line, a systematic translational characterization is delivered using ellipsometry, Brewster angle microscopy and neutron reflectometry of the extents, structures, and dynamics of the interactions of the peptides with the model membranes on a Langmuir trough.FindingsWe start by revealing that RSG does indeed have binding affinity to breast cancer cells. The peptide is then shown to exhibit stronger interactions and greater penetration than CGKRK into both model membranes, combined with greater disruption to the lipid component. RSG also forms aggregates bound to the model membranes, yet both peptides bind to a greater extent to the placental than cancer model membranes. The results demonstrate the potential for varying local reservoirs of peptide within cell membranes that may influence receptor binding. The innovative nature of our findings motivates the urgent need for more studies involving multifaceted experimental platforms to explore the use of specific peptide sequences to home to different cellular targets

Modeling and Optimization of a Photoelectrochemical Solar Hydrogen Cell with TiO2 as a Photo-anode

A photoelectrochemical (PEC) cell model for solar hydrogen production with titanium dioxide (TiO2) as a photo anode and platinum (Pt) as a cathode is developed. Despite the wide bandgap of TiO2 resulting in limited photon absorption from the sun, it is still a good candidate due to its stability in liquid electrolytes and reasonable cost. In this model, Beer-Lambert law is used in conjunction with the empirical diode equation to calculate the electron/hole pair generation rate in the photo-anode, and the external current reaching the cathode to estimate and optimize the hydrogen generation rate evolving at the cathode with TiO2 and ITO thicknesses as optimization variables. The model revealed an optimal solution of TiO2 thickness of 3230 nm at 400 nm ITO thickness, with optimal external current value of 26.9 A/m2, hydrogen generation rate of 1.394x10-4 mol/(m2s), and an overall cell efficiency of 3.4 %

Discovering novel immune-modulatory monosaccharides using high-throughput screening strategies

Introduction: New strategies for immunomodulation and immunotherapy to fight infections, allergic diseases and cancer have shown real promise in recent years. Dendritic cells (DCs) are considered gatekeepers of the immune system and act as a bridge between innate and adaptive immune systems. Upon antigen uptake in peripheral tissues, DCs migrate to the lymph nodes and interact with T cells where they guide T cell polarisation towards distinct inflammatory or regulatory phenotypes. Their ability in shaping adaptive immune responses makes DCs ideal targets for immune modulation. The immune-instructive properties of DCs upon encountering T cells are dependent on their cytokine profile and the co-stimulatory molecules expressed. In this project, I used a high throughput screening strategy to investigate immune modulatory properties of a combinatorial library of immobilised synthetic monosaccharides with a particular focus on their ability to modulate key phenotypic and functional properties of human DCs. I also investigated the modulatory properties of these monosaccharides in particulate form, using gold nanoparticles (AuNPs) coated with monosaccharides, and studied their impact on DCs phenotype and function as well as identifying sugar moieties that enhance uptake of the AuNPs. Results: A selection of immobilised carbohydrates including 100%1-amino-1-deoxy--Dgalactose (Gal1), 100%2-amino-2-deoxy--D-galactose (Gal2), 90%2-amino-2-deoxy--Dgalactose+10%1-amino-1-deoxy--D-mannose (Gal2-Man1), 2-amino-2-deoxy--Dgalactose+10%2-amino-2-deoxy--D-mannose (Gal2-Man2), 40%1-amino-1-deoxy--Dmannose + 60%2-amino-2-deoxy--D-mannose (Man1-Man2) and 50%1-amino-1-deoxy-- D-galactose +50%2-amino-2-deoxy--D-galactose (Gal1-Gal2), significantly downregulated LPS induced CD40 expression, compared to LPS alone, upregulated CD274 but had no significant changes in the expression of CD86 compared to unconditioned LPS stimulated controls. This was accompanied by a significant decrease in the activity of key immune regulatory enzyme 2,3 indoleamine dioxygenase (IDO) and production of interleukin (IL)-12, a signature pro-inflammatory cytokine. Furthermore, DCs stimulated with the same combinations of carbohydrates showed a significant increase in production of prototypic regulatory cytokine IL-10. Collectively these data suggest an anti-inflammatory/regulatory phenotype for DCs treated with these carbohydrates. Furthermore, DCs conditioned with a selection of anti-inflammatory carbohydrates (Gal1-Gal2 and Gal1) induced naïve T cell polarisation towards regulatory phenotype while other carbohydrate combinations shown to increase IL-12 production (Man1-Man2, Gal2-Man1 and Gal2-Man2) induced T-helper 1 phenotype confirming the anti and prof inflammatory DC phenotypes respectively. Moreover, an increase in IL-17 and RORγt expression confirmed presence of TH17 in conditions treated with Gal1 and Gal1-Gal2 while a decrease in the latter was noted in Man1-Gal2. This was also confirmatory in the allergy module where Gal1-Gal2 maintained production of IL-17 and Man1-Gal2 had significant reduction in IL-17 clearly showing the carbohydrates potential in immunomodulation. Carbohydrate coated AuNPs showed differential uptake by DCs where 100%fucose, 100%mannose, 90%mannose+10%Galactose and 80%mannose+20%Galactose coated AuNPs had highest internalization. Flow cytometry showed increased lysosomal and endosomal localisation for AuNPs coated with 100%fucose over the other conditions compared to uncoated AuNPs. Investigations of the fate of the particles showed significant increased co-localization of AuNPs with lysosomes for 100%fucose, 80%fucose+20%galactose and 70%galactose+20%mannose compared to other conditions. On the other hand, co-localization of AuNPs with endosomes for 100%mannose was significantly higher than other conditions. An understanding of receptor mediated endocytosis (active uptake) and micropinocytosis (passive uptake) mechanisms was assessed using Methyl-β-cyclodextrins where there was a significant reduction of uptake between Methyl-β-cyclodextrins treated and untreated conditions suggesting the predominant mechanism of internalization of the AuNPs is active uptake. Conclusions: Collectively these observations show the potential immunomodulatory effects of immobilised monosaccharides in priming DCs and skewing immune responses towards different functional pro- or anti-inflammatory/regulatory phenotypes. It also provides insights into using monosaccharides to optimize cellular uptake of nanoparticles as well as guiding trafficking towards different intracellular compartments. This understanding could pave the way for utilising simple monosaccharides in the development of anti-inflammatory coatings for graft implants and reduction of chronic inflammatory and autoimmune responses as well as potent drug delivery platforms guided towards antigen delivery and RNA silencing therapies