Chemical and Biomolecular Engineering Theses and Dissertations

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    Machine Learning Assisted Design of MXene Aerogels for Personal Thermal Management
    (2023) Kesavan, Meera; Chen, Po-Yen; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Personal thermal management is necessary in maintaining body temperature in humans through the use of building insulation, personal garments, and heating or cooling units. Electrically conductive aerogels can be used as a multifunctional material, where the aerogel structure is intrinsically thermally insulating, and the incorporation of electrically conductive components allows for Joule heating of these materials for wearable heaters. Ti3C2Tx (MXene) has been incorporated in materials for Joule heating due to its excellent electrical conductivity. Cellulose and gelatin based aerogels have been used as bio-based materials with good structural properties in aerogels. Due to the large range of possibilities in parameters for aerogel formation, from percentage of components in each sample to sample concentration and presence or absence of glutaraldehyde, it can be tedious to test a matrix of recipes and determine the effects of each component on the electrical properties. To assist in the design of highly conductive aerogels machine learning was used as it uses a data-driven approach to analyze the effect of inputs, sample composition in this case, to predict a set of inputs that will return a desired output, which is a highly conductive aerogel.Aerogels of various compositions were fabricated and their resistances and sensitivities to applied pressure were measured to screen for highly conductive recipes and for strain insensitive samples. Of these samples, a strain insensitive sample recipe and a strain sensitive sample recipe were selected for Joule heating tests. Low voltages of 2 Volts and below, were applied to the aerogel samples and the temperature increase was measured. The stability of these samples under multiple heating and cooling cycles were tested both with and without applied compression. Through these tests we determined a strain insensitive aerogel recipe for stable temperature control regardless of pressure applied. This aerogel recipe was found to have a thermal conductivity comparable to common insulating materials at a much lower density. A machine learning model was then trained from the aerogel compositions and measured resistance values, and a prediction model with a low mean relative error of 19% was developed to assist in conductive aerogel recipe formulation.
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    (2023) Davoudi, Omid; Klauda, Jeffery B; Sukharev, Sergei; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Divalent cations bound to anionic lipids are necessary co-factors for many signaling mechanisms taking place at both the inner and outer surfaces of the cytoplasmic membrane. Coordination of divalent ions jointly by phospholipid headgroups and specific protein domains mediates recognition and triggers secondary messenger cascades or membrane fusion events. Phosphoryl oxygens of phospholipids are common contributors to divalent ion coordination. With the aims of elucidating the affinities of the calcium ion Ca(2+) and its toxic competitor beryllium Be(2+) to different types of phosphate groups taking place in many ‘building blocks’ of the cell, improving simulation force fields and better understanding the nature of beryllium toxicity, here we use isothermal titration calorimetry (ITC) to study the thermodynamic parameters and coordination of these ions by phosphates. Particularly, we focus on the differences between phosphates in the phosphodiester configuration that connect the glycerol backbone with a headgroup (as in phosphatidylglycerol, PG) and terminal monoester phosphates such as in phosphatidic acid (PA) and most phosphorylated proteins. The comparison of small model compounds, dimethyl phosphate (DMP, mimicking phosphate in phosphatidyl glycerol) with glycerol-3-phosphate (Gly3P, emulating phosphate in phosphatidic acid) shows that the affinity of Be(2+) for Gly3P is about one order of magnitude higher than for DMP and may exhibit at least two binding configurations. The Be(2+) -DMP thermograms in most cases are well fitted with a one-site model. Upon completing the survey of small (model) compounds, we performed experiments to compare the binding parameters of Be(2+) to POPA and to POPG-containing liposomes with the parameters obtained on respective model compounds. We also present several pilot binding experiments performed with POPS liposomes; however, the fit is poor.
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    Assessing the Thermal Safety and Thermochemistry of Lithium Metal All-Solid-State Batteries Through Differential Scanning Calorimetry and Modeling
    (2023) Johnson, Nathan Brenner; Albertus, Paul; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Solid-state batteries are often considered to have superior safety compared to their liquid electrolyte counterparts, but further analysis is needed, especially because the desired higher specific energy of a solid-state lithium metal battery results in a higher potential temperature rise from the electrical energy in the cell. Safety is a multi-faceted issue that should be carefully assessed. We build "all-inclusive microcell" Differential Scanning Calorimetry samples that include all cell stack layers for a Li0.43CoO2 | Li7La3Zr2O12 | Li cell in commercially relevant material ratios (e.g. capacity matched electrodes) and gather heat flow data. From this data, we use thermodynamically calculated enthalpies of reactions for this cell chemistry to predict key points in cell thermal runaway (e.g., onset temperature, maximum temperature) and assess battery safety at the materials stage of cell development. We construct a model of the temperature rise during a thermal ramp test and short circuit in a large-format solid-state Li0.43CoO2 | Li7La3Zr2O12 | Li battery based on microcell heat flow measurements. Our model shows self-heating onset temperatures at ∼200-250°C, due to O2 released from the metal oxide cathode. Cascading exothermic reactions may drive the cell temperature during thermal runaway to ∼1000 °C in our model, comparable to temperature rise from high-energy Li-ion cells, but subject to key assumptions such as O2 reacting with Li. Higher energy density cathode materials such as LiNi0.8Co0.15Al0.05O2 in our model show peak temperatures >1300°C. Transport of O2 or Li through the solid-state separator (e.g., through cracks), and the passivation of Li metal by solid products such as Li2O, are key determinants of the peak temperature. Our work demonstrates the critical importance of the management of molten Li and O2 gas within the cell, and the importance of future modeling and experimental work to quantify the rate of the 2Li+1/2O2→Li2O reaction, and others, within a large format Li metal solid-state battery.
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    (2023) Mao, Chun-Ning; Asa-Awuku, Akua; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Polymeric nanoparticles affect many aspects of human life. They directly absorb or scatter sunlight, or indirectly act as cloud condensation nuclei (CCN) to change the Earth’s climate. Additionally, micro-plastics released into the environment have the potential to degrade into nano-size particles. Plastic nanoparticles' sizes, number concentration, and hygroscopicity are important properties to understanding nano-plastics’ fates. In this work, I explored aerosol measurement techniques, aerosol hygroscopicity, and polymer nanoparticles to understand subsequent effects in the environment and on human health. The project was divided into three objectives:For the first objective, I developed the single-parameter hygroscopicity model for polymeric aerosols with Flory-Huggins Köhler theory. Traditional hygroscopicity, derived from Raoult’s law, depends on the molecular volume of the solute. For polymers with a high molecular volume, the predicted hygroscopicity from traditional Köhler theory is zero. However, the experimental results showed that polymers could take up water and readily act as CCN. I developed the expression of the hygroscopicity for polymers and showed the relation between the polymer-water interaction parameter and the water-uptake ability. I also considered water-insoluble polymers and the water-adsorption model combined with Köhler theory to define water-uptake. Thus the CCN activity of polystyrene and surface modified polystyrene particles were also measured. For the second objective, I predicted the fraction of the multiply charged particles, showing that the extinction cross section measured by Cavity Ring Down Spectroscopy (CRD) was influenced by a small amount of multiply charged particles using a Differential Mobility Analyzer (DMA). The initial results indicated that ~4% to ~6% of the total number concentration are triply and quadruply charged particles at 200 nm electrical mobility. This small percentage if neglected could induce errors greater than 5% in subsequent extinction cross section measurements. Thus, the errors induced with commercially available DMAs in the extinction cross section measurement were evaluated. For the third objective, I studied the fate of the nano-plastics in the environment. Results showed that low density polyethylene (LDPE) powders generated particles less than 100 nm at temperatures above 40 oC. I quantified the number concentration of 5 materials in water via traditional atmospheric aerosol measurement techniques. The five materials are cellulose, SiO2, LDPE, polyethylene terephthalate (PET), and polyvinyl chloride (PVC). They were all common materials used for food packaging. Furthermore, the hygroscopicities of the nano-plastics were measured. I demonstrated that the nano-plastics could act as CCN under a supersaturated environment and hence affect the climate. The results showed that the plastic materials (LDPE, PVC, PET) were more hygroscopic than cellulose. The nano-plastics could travel further and be found in remote and cold areas like Antarctica, the Arctic, and high mountains. The work in this objective provided evidence of wet deposition being a possible route for nano-plastics to come to the ground. Plastics are relatively new materials compared to papers, clays, and glasses, but have already been massively produced. The work in this thesis contributed to our understanding of the impact on nano-plastics to the environment. The interaction of the water and nano-plastics in the environment was studied. The measurements of size distribution and hygroscopicity of nano-plastics can be applied in the climate model to reduce the uncertainties in the indirect effect of the aerosols in future studies.
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    (2022) Gohil, Kanishk; Asa-Awuku, Akua A; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Aerosols can affect the net radiation budget and global climate of the Earth either “directly” – through their radiative properties, or “indirectly” – through their cloud-forming abilities by acting as Cloud Condensation Nuclei (CCN). The interactions between aerosols and clouds are the most significant sources of uncertainty in the overall radiative forcing from due to a lack of understanding related to the droplet formation mechanism of aerosols. These uncertainties are majorly associated with the carbonaceous aerosols present in the atmosphere, notably due to their compositional diversity, vastly variable physicochemical properties, and unique water uptake characteristics. In this dissertation, new lab-based measurement techniques and computational methods have been developed to resolve the CCN activity and water uptake behavior of pure and mixed carbonaceous aerosol particles.The first part of this dissertation accomplishes two goals: 1. The development and application of a new CCN measurement method, and 2. The formulation of a new computational framework for CCN activity analysis of aerosols. The results in this dissertation demonstrate the significance of size-resolved morphology and dissolution properties of aerosol particles in improving their CCN activity analysis under varying ambient conditions. Furthermore, these results suggest that in the future, more comprehensive CCN analysis frameworks can be developed by explicitly treating other physical and chemical properties of the aerosols to further improve their CCN activity analysis. The second part of this dissertation focuses on large-scale analysis. The CCN analysis framework is implemented into a climate model to quantify the water uptake behavior of carbonaceous aerosols, and then study the subsequent variabilities associated with the physical and radiative properties of ambient aerosols and clouds. Statistical techniques are also developed in this work for chemical characterization of ambient aerosols. The characterization results show large regional compositional variations in ambient aerosol populations. These results also suggest that the knowledge of chemical species is necessary to quantify the water uptake properties of the aerosol population.