Multifunctional Cooling Garment for Space Suit Environmental Control

Future manned space exploration missions will require space suits with capabilities beyond the current state of the art. Portable Life Support Systems for these future space suits face daunting challenges, since they must maintain healthy and comfortable conditions inside the suit for long-duration missions while minimizing weight and water venting. We have demonstrated the feasibility of an innovative, multipurpose garment for thermal and humidity control inside a space suit pressure garment that is simple, rugged, compact, and lightweight. The garment is a based on a conventional liquid cooling and ventilation garment (LCVG) that has been modified to directly absorb latent heat as well as sensible heat. This hybrid garment will prevent buildup of condensation inside the pressure garment, prevent loss of water by absorption in regenerable CO2 removal beds, and conserve water through use of advanced lithium chloride absorber/radiator (LCAR) technology for nonventing heat rejection. We have shown the feasibility of this approach by sizing the critical components for the hybrid garment, developing fabrication methods, building and testing a proof-of-concept system, and demonstrating by test that its performance is suitable for use in space suit life support systems

London Partsong Clubs and Masculinities, 1750-1830

My dissertation, “London Partsong Clubs and Masculinities, 1750–1830,” examines how the musical activities of all-male singing clubs in London played a key role in the formation of English masculine identities during the eighteenth and early nineteenth centuries. This particular time frame usefully demarcates a period of significant transformation from the fluid gender personae of early eighteenth-century society to the rigid gender binaries of the Victorian era. The partsongs sung during the private, weekly club meetings were harmonized settings of English texts (often 3–5 vocal parts) performed without accompaniment. As a genre written primarily by and for men within social settings, partsong serves as a unique lens for understanding how singing reinforced club members’ perceptions of gender identity and male friendship. Chapter one locates the rituals and conviviality of partsong clubs within underlying contexts of Parliamentarianism and Freemasonry. Chapter two argues that the inclusion of Elizabethan madrigals within eighteenth-century collections of glees was an attempt to establish newly-composed club music as the culmination of a longstanding English musical canon, relating to burgeoning ideas of antiquarianism and nationalism. Chapter three applies both eighteenth- and twenty-first-century philosophies of sympathy, sentimentality, and gender to the analysis of commemorative glees written upon the deaths of club members. Finally, chapter four considers how the growing prevalence of women as patrons, consumers, and performers of partsong influenced song material and performance practices. In concluding with women, my project argues that the realization of emergent ideas concerning masculinity was partially dependent upon contemporaneous views on femininity. | 206 page

Interactions of CO₂ Anion Radicals with Electrolyte Environments from First-Principles Simulations

Successful transformation of carbon dioxide (CO2) into value-added products is of great interest, as it contributes in part to the circular carbon economy. Understanding chemical interactions that stabilize crucial reaction intermediates of CO2 is important, and in this contribution, we employ atom centered density matrix propagation (ADMP) molecular dynamics simulations to investigate interactions between CO2– anion radicals with surrounding solvent molecules and electrolyte cations in both aqueous and nonaqueous environments. We show how different cations and solvents affect the stability of the CO2– anion radical by examining its angle and distance to a coordinating cation in molecular dynamics simulations. We identify that the strength of CO2– interactions can be tailored through choosing an appropriate cation and solvent combination. We anticipate that this fundamental understanding of cation/solvent interactions can facilitate the optimization of a chemical pathway that results from selective stabilization of a crucial reaction intermediate

Recent approaches in designing bioadhesive materials inspired by mussel adhesive protein

Marine mussels secret protein-based adhesives, which enable them to anchor to various surfaces in a saline, intertidal zone. Mussel foot proteins (Mfps) contain a large abundance of a unique, catecholic amino acid, Dopa, in their protein sequences. Catechol offers robust and durable adhe-sion to various substrate surfaces and contributes to the curing of the adhesive plaques. In this article, we review the unique features and the key functionalities of Mfps, catechol chemistry, and strategies for preparing catechol-functionalized poly- mers. Specifically, we reviewed recent findings on the contributions of various features of Mfps on interfacial binding, which include coacervate formation, surface drying properties, control of the oxidation state of catechol, among other features. We also summarized recent developments in designing advanced biomimetic materials including coacervate-forming adhesives, mechanically improved nano- and micro-composite adhesive hydrogels, as well as smart and self-healing materials. Finally, we review the applications of catechol-functionalized materials for the use as biomedical adhesives, therapeutic applications, and antifouling coatings

Computational tools for materials design: applications in dynamic covalent chemistry, polymers, and electrochemical systems

Modern materials chemistry covers a huge chemical space, from hydrogels to metal organic frameworks. The development of all this array of materials has been based on a variety of experimental, analytical, and computational techniques. Computational techniques have become increasingly vital to both material design and data analysis as technological advances in computation and automation have made scientific computation easier and data sets larger. This thesis discusses a variety of simulation, modeling, and data analysis techniques as applied to the fields of dynamic covalent chemistry, polymers, and electrochemistry. The first chapter provides a broad overview of computational techniques. The second chapter discusses the use of rule-based models to understand error correction and assembly in dynamic covalent chemistry systems. Chapter three focuses on how rule-based models can aid in understanding depolymerization mechanisms. In chapter four, electrochemical processes are modeled using density functional theory. Chapter five introduces the use of machine learning and density functional theory for monomer discovery. The final chapter provides a summary of these projects and the outlook for computational techniques in materials design. Rule-based models are ideal for dynamic covalent chemistry because rational design of large scale 3D molecular structures (covalent organic frameworks, molecular cages, etc.) is currently limited by our understanding of how the individual molecular constituents assemble into the larger structure. The most efficient routes to large scale 3D molecular structures depend on reversible interactions (either covalent or non-covalent), which can disconnect misplaced bonds (error correction), and reach the thermodynamic minimum product. However, error correction can be stymied by kinetic traps, which are persistent reaction intermediates. Kinetic traps are most common with multivalent precursors and slow exchange chemistries. With simple systems or very fast chemistries thermodynamic modeling is often sufficient to predict reaction outcomes. As complexity increases or exchange speeds slow, kinetic modeling is also necessary to understand the time course of the reaction and predict kinetic traps. Rule-based models can successfully capture the critical aspects of a dynamic reaction and predict error correction time. These models can give guidance to the planning of a dynamic covalent synthesis by predicting time to maximum yield of a desired product based on rate coefficients and valency. They can also capture details of the reaction network and provide an estimate of reaction kinetics that are challenging to directly measure. This type of modeling approach is particularly well suited to dynamic chemistries as a few simple rules can capture all the reactivity of the system, and the reaction networks are generated algorithmically. Another application for rule-based models is in understanding depolymerization mechanisms. Polymers that can degrade upon exposure to a specific trigger are of great interest as they could reduce plastic waste, make up transient electronics, act as biodegradeable medical implants, or as environmental sensors. There are a wide variety of chemistries used for triggered degradation, including those that are irreversible and those that fully depolymerize back down to monomer. As any triggered degradation has the trigger reaction and then an unzipping reaction, it can be quite challenging to experimentally measure the kinetics of each reaction. We apply rule-based models to determine the kinetic parameters that correctly model experimental data, to distinguish between mechanisms, and to probe the effect of mechanism, rate, and molecular weight on overall degradation behavior. We also develop new techniques to properly model dispersity based on experimental size-exclusion chromatography data and to directly calculate molecular weight within the model. The models here are directly tied to specific chemical systems, but they are also solid backbones for anyone desiring to build rule-based models for their own systems. Electrochemistry is vital to developing a green energy economy, whether it is through converting carbon dioxide in the atmosphere to value added chemicals, or through creating innovative new batteries. Optimizing reaction conditions or designing battery materials requires detailed understanding of the molecular and atomic level interactions between electrolytes, solvents, and reaction intermediates. Chapter four covers three approaches for using density functional theory (DFT) to gain insight into the behavior of electrochemical systems. First, we use dynamic DFT to probe interactions between carbon dioxide reduction reaction intermediates and surrounding solvent and electrolyte molecules. We show how different cations and solvents affect the stability of the [CO2]- radical anion by examining its angle and distance to cation in dynamic simulations. We identify that the strength of [CO2]- interactions can be tailored through choosing an appropriate cation and solvent combination. Second, we use static DFT to probe the relationship between cluster complexation energy and electrochemical behavior. We show that complexation energy can be easily predicted using machine learning and a database of over 300 complexes. Third, we develop a database of reduction potentials for divalent metal complexes of interest for designing beyond lithium batteries. We calculated the 1e- and 2e- reduction potentials for 78 different complexes in 22 different solvents, analyze the data trends, and identify which complexes are unstable upon reduction. These three studies use atomistic modeling to provide guidance on which systems are suitable and stable for specific applications, and worth further experimental study. Thermoset polymers and composites are widely used in airplanes, cars, and structural components due to their strength, stiffness, and low density. However, traditional thermosets require large amounts of energy to cure. Frontal ring-opening metathesis polymerization (FROMP) only requires a small initial thermal or photo stimulus which triggers a self-propagating exothermic reaction that fully cures the monomer to polymer. Currently, there are only a small number of monomers that can sustain FROMP. We use machine learning to identify the key aspects of a monomer that contribute to its FROMP behavior. We developed a large pool of over eleven million candidate monomers, and created a representative sample of those candidates. We did density functional theory calculations and scored for synthetic accessibility scores for all the representative sample. We discuss the active learning model that can be built from the known monomers and the candidate monomers to identify new FROMP monomers. The computational methods discussed here are quite varied, but they share the basic hypothesis that modeling system and applying systematic data analysis can provide vital information to understand complex chemical systems. As shown in this dissertation, the future of chemical discovery relies on the interweaving of chemical knowledge, experimental results, theory, simulation, and data science.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-05-01The student, Morgan Cencer, accepted the attached license on 2022-02-18 at 08:25.The student, Morgan Cencer, submitted this Dissertation for approval on 2022-02-18 at 08:42.This Dissertation was approved for publication on 2022-03-02 at 13:37.DSpace SAF Submission Ingestion Package generated from Vireo submission #17507 on 2022-11-11 at 12:18:1

PARP-1 to the Rescue: A Biphasic Mechanism of UVB-Induced DNA Damage and Repair in Cultured Human Lens Epithelial Cells

It has been shown that UVB light damages the DNA of cells; however, it has yet to be shown how this occurs in lens epithelial cells (LECs) found on the anterior surface of the eye’s lens. The purpose of this research project was to explore UVB-induced DNA damage to LECs along with investigation of a related DNA repair complex. A DNA repair process for LECs is hypothesized to involve two components referred to as poly(ADP-ribose) polymerase-1 (PARP- 1) and poly(ADP-ribose) (PAR). The exact mechanisms for UVB induced DNA damage and its repair are not yet confirmed. To study these two events, cultured human LECs were exposed to UVB light and then incubated for various times after UVB exposure. Various assays were conducted to visualize the processes of DNA damage and repair. These assays included cell viability (MTT assay), the comet assay to detect single strand DNA breaks, reactive oxygen species (ROS) and superoxide anion indicators, as well as fluorescence immunocytochemistry with antibodies to PARP-1 and PAR and apoptosis detection. The goal was to discover how the lens DNA repair complex works in response to UVB induced cellular damage. The benefits of this project include a contribution to existing eye and cataract research

Unraveling the Mechanisms of Apical Cadherin-Based Adhesion in Brush Border and Junction Assembly

Transporting epithelia of the kidney and small intestine utilize actin-supported cell surface protrusions, known as microvilli, to expand surface area available for solute transport. Microvilli found on the surface of these epithelia constitute a well-organized “brush border” made up of thousands of protrusions connected via a tip-localized intermicrovillar adhesion complex (IMAC) composed of cadherins CDHR2 and CDHR5. Experiments in this dissertation project revealed that at time points early in differentiation, epithelial cells present two general populations of microvilli: (1) a marginal population at the edges of cells, characterized by high protrusion density, and (2) a medial population characterized by much lower protrusion density. Strikingly, marginal microvilli extend across cell-cell junctions to physically contact microvilli on neighboring cells, using “transjunctional” IMACs. Additionally, transjunctional IMACs are more stable than those bridging medial clusters of microvilli and serve as an anchoring point for nascent microvilli at cell margins. Given the stabilizing nature of transjunctional IMACs, basolateral junctions may be influenced by apical CDHR2/CDHR5 transjunctional contacts. Indeed, in a CDHR2 KO mouse model and in CDHR2 KO CL4 and CACO-2BBE cells, endogenous signal of tight and adherens junction proteins and non-muscle myosin 2-c are reduced. As a result, CDHR2 KO cells exhibit abnormal cell morphologies, increased junction permeability, and impaired collective cell migration. Overall, these findings suggest a new, adhesion-based mechanism for the stabilization of microvilli and support of cell junctions, changing the established understanding of how transporting epithelial cells utilize cell-cell contacts to create optimal tissue structure