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Design and analysis of an alkaline fuel cell
No full textThis study provides a step-by-step, up-to-date fuel cell fundamentals, thermodynamic and electrochemical principles, and system evaluation factors via a case study of a 10-kW alkaline fuel cell designed to operate in space applications. The system also produces 100 kg of pure water and 5.5 kW of heat. The system is modelled using MATLAB and ANSYS Fluent. Then, the model is verified with theoretical and experimental results from the literature. A parametric study of various design and operating parameters, and material selection is carried out to optimize the overall performance. A net output voltage of 0.8 V is obtained at 150 mAcm-2 current density, which yields an overall efficiency of 75%. The results indicate that increasing the electrolyte thickness or operating temperature results in a lower net voltage output. Additionally, improving the performance of a fuel cell through the bipolar plate can be achieved by understanding the contribution of different parameters towards minimizing the pressure drop across the bipolar plate. It is found that implementing an optimized selection of fluid flow rate, channel width, channel depth, number of channels and current density minimize the pressure drop throughout the bipolar plate. Relative humidity has a significant effect on the pressure drop. Results indicate that increasing the relative humidity consequentially rises the pressure drop. Finally, the CFD simulation illustrates that the end-zones in the bipolar plate accumulates fluid due to the nature of stagnation at those locations. Thus, total pressure at those locations is the highest. One of the major contributions here is studying the effect of KOH concentration on the performance of the AFC at different operating temperatures. In addition, a wide range of design and operating parameters were analysed to understand their effect on the overall performance of the fuel cell
A Comparative Analysis of Numerical Methods for Solving the Leaky Fire and Integrate Model
No full textThe human nervous system is one of the most complex systems of the human body. Understanding its behavior is crucial in drug discovery and developing medical devices. One approach to understanding such a system is to model its most basic unit, neurons. The leaky integrate and fire (LIF) method models the neurons’ response to a stimulus. Given the fact that the model’s equation is a linear ordinary differential equation, the purpose of this research is to compare which numerical analysis method gives the best results for the simplified version of this model. Adams predictor and corrector (AB4-AM4) and Heun’s methods were then used to solve the equation. In addition, this study further researches the effects of different current input models on the LIF’s voltage output. In terms of the computational time, Heun’s method was 0.01191 s on average which is much less than that of the AB-AM4 method (0.057138) for a constant DC input. As for the root mean square error, the AB-AM4 method had a much lower value (0.0061) compared to that of Heun’s method (0.3272) for the same constant input. Therefore, our results show that Heun’s method is best suited for the simplified LIF model since it had the lowest computation time of 36 ms, was stable over a larger range, and had an accuracy of 72% for the varying sinusoidal current input model.American University of SharjahAlJalila FoundationAl Qasimi FoundationPatient’s Friends Committee of SharjahBiosciences and Bioengineering Research InstituteGCC Co-Fund ProgramTakamul programTechnology Innovation Pioneer (TIP) Healthcare AwardsSheikh Hamdan Award for Medical SciencesFriends of Cancer Patients (FoCP)Dana Gas Endowed Chair for Chemical Engineerin
INScription: Department of International Studies (INS) Issue #17 (October 26, 2023, Issue 3)
No full textCollege of Arts and SciencesDepartment of International Studie
The Impact of the SVB Collapse on Banking Industry
No full textA Master of Science thesis in Finance by Ye Xi entitled, “The Impact of the SVB Collapse on Banking Industry”, submitted in November 2023. Thesis advisor is Dr. Anis Samet and thesis co-advisor is Dr. Kimberly Gleason. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).School of Business AdministrationDepartment of FinanceMaster of Science in Finance (MSF
المجلة :ثقافة - ادب - ترجمة
No full textCollege of Arts and SciencesDepartment of Arabic and Translation Studie
Application of Biochar-Based Catalyst for The Upgrade of Pyrolysis Bio-Oil And Gas At A Wide Range Of Temperature
No full textA Master of Science thesis in Chemical Engineering by Ayman Mohamedelkhair entitled, “Application of Biochar-Based Catalyst for The Upgrade of Pyrolysis Bio-Oil And Gas At A Wide Range Of Temperature”, submitted in April 2023. Thesis advisor is Dr. Yassir Makkawi. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Chemical EngineeringMaster of Science in Chemical Engineering (MSChE
Rethinking water security in a warming climate: rainfall enhancement as an innovative augmentation technique
No full textRainfall enhancement has historically been overlooked as a key component of sustainability and climate change adaptation strategies. In this comment, we argue that rainfall enhancement is emerging as a viable contributor to addressing growing water security concerns in a warming climate. We specifically consider current progress and future directions for rainfall enhancement applications based on the experience of the United Arab Emirates (UAE) with its national decade-long operational cloud seeding program and its grant-based international research and development program.UAE Research Program for Rain Enhancement Science (UAEREP
Liposomes-Based Drug Delivery Systems of Anti-Biofilm Agents to Combat Bacterial Biofilm Formation
No full textAll currently approved antibiotics are being met by some degree of resistance by the bacteria they target. Biofilm formation is one of the crucial enablers of bacterial resistance, making it an important bacterial process to target for overcoming antibiotic resistance. Accordingly, several drug delivery systems that target biofilm formation have been developed. One of these systems is based on lipid-based nanocarriers (liposomes), which have shown strong efficacy against biofilms of bacterial pathogens. Liposomes come in various types, namely conventional (charged or neutral), stimuli-responsive, deformable, targeted, and stealth. This paper reviews studies employing liposomal formulations against biofilms of medically salient gram-negative and gram-positive bacterial species reported recently. When it comes to gram-negative species, liposomal formulations of various types were reported to be efficacious against Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, and members of the genera Klebsiella, Salmonella, Aeromonas, Serratia, Porphyromonas, and Prevotella. A range of liposomal formulations were also effective against gram-positive biofilms, including mostly biofilms of Staphylococcal strains, namely Staphylococcus aureus, Staphylococcus epidermidis, and Staphylococcus saprophyticus subspecies bovis, followed by Streptococcal strains (pneumonia, oralis, and mutans), Cutibacterium acnes, Bacillus subtilis, Mycobacterium avium, Mycobacterium avium subsp. hominissuis, Mycobacterium abscessus, and Listeria monocytogenes biofilms. This review outlines the benefits and limitations of using liposomal formulations as means to combat different multidrug-resistant bacteria, urging the investigation of the effects of bacterial gram-stain on liposomal efficiency and the inclusion of pathogenic bacterial strains previously unstudied.American University of Sharja
Insights into rechargeable Zn-air batteries for future advancements in energy storing technology
No full textOwing to its high theoretical specific energy density, low cost, abundance and environmental friendliness, the rechargeable Zn-Air batteries (ZAB) are becoming the most prevalent candidate as energy storage devices for consumer electronics, and electric vehicles. Nevertheless, the interaction of O2 as a fuel with the components of ZAB is highly challenging for practical implementations of this technology. The underlying electrochemical reactions in ZAB involving multi-electron transfer, adsorption/evolution of O2, and dissolution of Zn metal in electrolyte, need robust-electrocatalyst and stable Zn/electrolyte interface. This prominently evokes the need for an in-depth study of electrocatalytic reactions occurring at the electrode/electrolyte interphases as well as the physiochemical features of membranes in ZAB. Therefore, this review provides significant insights into the fundamentals of Zn air battery system in terms of the underlying electrochemical mechanism, composition/structural performance relationship of different battery components. A detailed section has been devoted in summarizing the evaluating factors for battery performance including power density, polarization curves, columbic efficiency and correlation of catalyst's redox activity (Eonset, Ehalf-way, and Jd) with the device performance parameters (OCV, Ohmic losses, and Pmax). Moreover, representative studies of in-situ/operando characterizations have also been summarized to reveal the structural stability, reaction kinetics, formation of by-products, and morphological evolution. The intriguing advanced features of ZABs including flexibility, photo-recharge ability, economic feasibility, fast charging, high energy density, improved stability and hybrid Zn battery systems are particularly discussed. For the accomplishment of these functionalities, the chemical heterogeneity and structural modifications of materials (electrode, electrolyte and membranes) with improved electrical conductivity, reduced energy barrier, increased reactive surface area, and improved mass transport behavior at the nanoscale have been anticipated. This material survey could be highly beneficial for the development and modification of new catalysts in the field of electrocatalysis. Additionally, for the prospect of green energy technology, the economic viability and environmental sustainability of ZAB are also highlighted. Lastly, based on the discussion of recent achievements, some challenges and outlooks for maturing the rechargeable Zn air battery technology at the academic level and at the industrial scale are also set forth.American University of Sharja
Machine Learning Assisted Approach to Design Lattices With Prescribed Bandgap Characteristics
No full textA Master of Science thesis in Mechanical Engineering by Mohamed Shendy entitled, “Machine Learning Assisted Approach to Design Lattices With Prescribed Bandgap Characteristics”, submitted in March 2023. Thesis advisor is Dr. Maen Alkhader and thesis co-advisor is Dr. Bassam Abu-Nabah. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).Lattice-based metamaterials belong to the phononic crystals class of materials which are known for their ability to interact with, direct, and block elastic waves. These properties made lattice-based metamaterials appealing in wave guiding, noise filtering, and vibration isolation applications. However, capitalizing on the full potential of lattice-based materials in isolation and filtering applications has been hindered by the lack of systematic and efficient design methodologies capable of producing a lattice with pre-set band gap characteristics. Existing design methodologies utilize timeconsuming iterative computational schemes and often move towards geometrically complex lattices whose fabrication requires expensive additive manufacturing techniques. This work proposes an artificial intelligent-assisted design methodology that integrates sinusoidal perturbations and the easy-to-fabricate double-wall hexagonal lattice. In the proposed approach, sinusoidal perturbations with different frequencies and amplitudes are superposed on the double-wall hexagonal lattice to increase the number and bandwidth of its band gaps. Finite element analysis is used to determine the band gaps in the perturbed lattices. By using five perturbation frequencies, five amplitudes, and six lattice porosities, the perturbed lattices delivered a band gap at each frequency in the range of 0 to 1000kHz. Machine learning, namely deep neural networks, is used to model the relationships among the perturbation parameters, lattice porosity, and the corresponding band gap characteristics. Three parallel neural network models are developed. These predict the maximum number of band gaps and the width and centroid of the band gap with maximum bandwidth. Results showed that the developed neural network models had an average accuracy of 90%. The developed neural network models constitute the core of the proposed design methodology. They are used to determine the coarse design parameters (i.e., porosity and perturbation parameters) required to realize prescribed band gap characteristics. The coarse design parameters are subsequently refined using finite element analysis. This approach accelerates the design process and eliminates the need for time-expensive iterative processes. A case study is presented to demonstrate the efficiency and practicality of the proposed design process.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME