ME Theses and Dissertations

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    Exploring the synthesis of boron nitride at low temperature
    (Wichita State University, 2023-12) Yara, Nikhil Kumar; Wei, Wei
    Boron nitride (BN) is one of the most advanced ceramic materials that have appealing properties such as electrical insulation, mechanical strength, and high thermal conductivity. There are a lot of methods to synthesize BNs. In this work, the chemical vapor deposition (CVD) which requires temperatures around 1000°C was used. This thesis work aimed to design and develop a lower- temperature CVD method for the production of BN to improve efficiency and reduce costs. B, MgO and Fe2O3 were used as the precursors in the ratio of 2:1:1 respectively. Along with this, He and NH3 gases were used to carry out the reaction to produce the BN as the end product which has nanotubes, flakes, hair-like structures, and bubbles. Various temperatures in the range of 800 to 1000ºC with varying reactions, flow rates of gases, and pressure were investigated. There was an effect on BN production by varying the flow rate and reaction time. XRD and SEM were employed to characterize the obtained BN. It showed that BNNTs were obtained at 800ºC, 850ºC and 900ºC with a shorter reaction time between 30 to 45 mins and an NH3 flow rate of 1.00 - 1.25 L/min. At various higher temperatures, BN with flakes, hair-like structures and bubbles were obtained. Under less optimal parameters, amorphous boron nitride nanostructures were formed. This thesis demonstrates a promising energy-efficient CVD route for BN and also synthesized BN with some structures like nanotubes, flakes and bubbles. Usually, these BNNTs are synthesized at very high temperatures but this work was able to produce BNs at about 200°C below the conventional temperatures. The results provide new insight into the relationships between temperature, flow rates, duration, and BN yield. Further work will be needed to improve nanotube purity and density. Nonetheless, the technique developed represents progress toward greener, more cost-effective BNNT production.
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    Dye-sensitized photosupercapacitor with carbon-based materials as the intermediate electrode
    (Wichita State University, 2023-12) Bishop, Victoria I.; Wei, Wei
    Due to the growing environmental crisis, developing new methods of generating and storing renewable energy is more important than ever. Solar is among the most promising renewable methods; however, it has some critical weaknesses. To addresses these weaknesses, methods of storing energy in the form of batteries and supercapacitors have been evaluated. The overall goal for such devices is to integrate the solar cell and storage device into a single electronic device that can account for power fluctuations, and provide energy when requirements are the highest. Third generation solar cells are ideal for the potential applications these devices would have. This generation includes dye-sensitized solar cells (DSSCs), perovskite solar cells, organic solar cells, and quantum-dot solar cells. Supercapacitors are a developing technology that are also ideal for the potential applications. Combining third generation solar cells like DSSCs with supercapacitors would result in an inexpensive device capable of converting and storing solar energy in a simple way. In this thesis, four commercial carbon materials were investigated as electrodes for monolithic DSSC-supercapacitor devices and directly compared for the first time. The objective of this research is to determine if inexpensive carbon-based materials are effective and competitive as electrodes in these devices. The four materials chosen are activated carbon, mesoporous carbon, graphite, and graphene. Of these four materials, graphite had the poorest power conversion efficiency after integration at 1.43%, and graphene had the lowest mass specific capacitance of $13.0 F g^{-1}$, attributed to the simplistic fabrication methods. In comparison, Mesoporous Carbon achieved the best integrated performance with an integrated power conversion efficiency of 3.10%, a photocurrent of 1.37 mA, and a post-integration mass specific capacitance of $40.0 F g^{-1}$.
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    Developing electrospun fibers for hydrogen storage applications
    (Wichita State University, 2023-05) Mohammed, Qamar Saberi; Asmatulu, Eylem
    The primary objective of this research was to produce an electrospun nanofiber for the application of hydrogen storage, and the absorption kinetics of the highly porous nanocomposite fiber mats. One of the critical components of advancing hydrogen, and fuel cell technologies advancement is successfully storing hydrogen for use in various industries, like transportation, defense, compact gadgets, and energy. Hydrogen energy is the future because of its highest energy density, availability, and environmental and health benefits. Currently, enterprises are searching for a solution for energy distribution management and hydrogen gas storage. In this way, there is a need to develop a hydrogen storage innovation that might be considered for later use in aviation applications. It is being researched that functional nanocomposite fibers incorporated with hydrogen-sensitive inclusions will increase hydrogen storage capacity, and absorption/desorption kinetics of hydrogen gas at lower temperatures and pressures. Here, the electrospinning method has been used to produce polymeric nanofibers with different nanoscale metal hydrides, and conductive particles that can store hydrogen under a controlled environment, and enhance thermal properties. Selected polymeric materials for hydrogen storage that have been investigated are polyacrylonitrile (PAN), poly (methyl methacrylate) (PMMA), and sulfonated polyether ether ketone (SPEEK) in combination with metallic hydrides, and multi-walled carbon nanotubes. On testing, it was observed that hydrogen capacity with SPEEK, which includes 4% MWCNT and 4% MH (Mmni4.5Fe0.5) shows significant H2 uptake compared to PAN/PMMA polymer.
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    Predictive machine learning model for the future trend of energy consumption in fully electricity homes considering occupancy status of the building
    (Wichita State University, 2023-07) Hosseini, Amin; Kim, Yang-Seon
    HVAC unit is one of the most power-intensive loads in buildings. It is also very significant for residential customers because indoor temperature must be maintained within an acceptable range of occupant’s comfort. To minimize energy consumption while providing a comfortable environment for the occupants, Building Energy Simulation (BES) gained considerable attention in recent years. Available BES calculates building energy consumption during the design phase and therefore, they optimize building energy consumption in this stage. However, there are still deficiencies that prevent BES from achieving higher efficiencies. Using a fixed occupancy schedule, not considering complexities in the occupant’s interactions with indoor appliances and HVAC unit are some of the setbacks that reduce the accuracy of the BES tools. Introduction of smart thermostats, made it possible for researchers to study the trend of changes in different measurable variables in the indoor environment like temperature, humidity, the runtime of the HVAC system, occupancy schedule, cooling and heating set point temperatures, etc. Data obtained from smart thermostat can be used to build a predictive model using a machine learning technique. Machine learning techniques help to estimate future trends of indoor variables like occupancy schedule, set point temperature and building energy consumption. Feeding the predicted variables by machine learning to the BES software helps to create a more accurate model for the energy simulation of buildings. This study presents a novel predictive model based on a co-simulation method using EnergyPlus and machine learning technique to better manage the energy consumption in the residential buildings. The proposed approach, which combines neural network and physic-based energy modeling, successfully estimates the total energy consumption in buildings with CV(CV(RMSE)) of 2.22% and NMBE of 5.65% on hourly basis.
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    Dielectric relaxations in soy protein-dimethyl sulfoxide mixtures
    (Wichita State University, 2023-05) Tan, Zhao Heng; Li, Bin
    Plant proteins have been extensively studied as promising bioresources for sustainable materials applications, because of their abundance in nature and remarkable tunability in structures and properties, in face of the rising environmental and socioeconomic concerns of petrochemicals. A tremendous number of studies have explored their potential applications in packaging, composites, and biomedical applications, etc... However, unlike synthetic polymers and another popular biopolymer from natural resources, i.e., cellulose, proteins have complex structures and diverse functional groups, and they exhibited sophisticated, but insufficiently understood, interactions with chemical environment, which are vital to their aggregated structures, and eventually applications. To successfully apply proteins to practical materials applications, a better understanding of protein structures and behaviors, subjected to chemical environment, is needed. Among various plant proteins, soy protein has received the greatest attention, due to its richness in nature as the product of the major economic crop, soybeans. This project focused on soy protein isolate (SPI), and its interactions with dimethyl sulfoxide (DMSO), one of the most popular organic solvents in materials and biological research. Pure SPI exhibited 3 relaxation processes, α, β, γ relaxations, related to segmental chain motions, conductivity relaxation, and the fast local motions of protein chain subunits, respectively. The unique interactions between sulfoxide groups in DMSO and amine groups in SPI apparently had an enhancing effect on both β and γ relaxations, besides the plasticizing effects on all three relaxations. The absorbed moisture introduced a new relaxation process between β and α relaxations. With increasing temperature, the coupling of β and γ relaxations with α relaxation became prominent, leading to apparent merge with α relaxation.