materials for lithium-based batteries: silicon (Si) and metal lithium (Li). It will focus on
studying the mechanical behaviors of the two materials during charge and discharge and
understanding how these mechanical behaviors may affect their electrochemical
performance.
In the first part, amorphous Si anode will be studied. Despite many existing studies
on silicon (Si) anodes for lithium ion batteries (LIBs), many essential questions still exist
on compound formation, composition, and properties. Here it is shown that some
previously accepted findings do not truthfully reflect the actual lithiation mechanisms in
realistic battery configurations. Furthermore the correlation between structure and
mechanical properties in these materials has not been properly established. Here, a rigorous
and thorough study is performed to comprehensively understand the electrochemical
reaction mechanisms of amorphous-Si (a-Si) in a realistic LIB configuration. In-depth
microstructural characterization was performed and correlations were established between
Li-Si composition, volumetric expansion, and modulus/hardness. It is found that the
lithiation process of a-Si in a real battery setup is a single-phase reaction rather than the
accepted two-phase reaction obtained from in-situ TEM experiments. The findings in this
dissertation establish a reference to quantitatively explain many key metrics for lithiated a
Si as anodes in real LIBs, and can be used to rationally design a-Si based high-performance
LIBs guided by high-fidelity modeling and simulations.
In the second part, Li metal anode will be investigated. Problems related to dendrite
growth on lithium metal anodes such as capacity loss and short circuit present major
barriers to the next-generation high-energy-density batteries. The development of
successful mitigation strategies is impeded by the incomplete understanding of the Li
dendrite growth mechanisms. Here the enabling role of plating residual stress in dendrite
initiation through novel experiments of Li electrodeposition on soft substrates is confirmed,
and the observations is explained with a stress-driven dendrite growth model. Dendrite
growth is mitigated on such soft substrates through surface-wrinkling-induced stress
relaxation in deposited Li film. It is demonstrated that this new dendrite mitigation
mechanism can be utilized synergistically with other existing approaches in the form of
three-dimensional (3D) soft scaffolds for Li plating, which achieves superior coulombic
efficiency over conventional hard copper current collectors under large current density.
The pads were created using varying amounts of LM and matrix materials ranging from copper microspheres to diamond powder mixed into PDMS using a high-speed mixer. The material was then cast into molds and cured to create the pads. Once the pads were created, the difficulty came in quantifying their thermal properties. A stepped bar apparatus (SBA) following ASTM D5470 was created to measure the thermal resistance of the pads but it was determined that thermal conductivity was a more usable metric of the pads’ performance. This meant that the pad’s in-situ thickness was needed during testing, prompting the installation of a linear encoder to measure the thickness. The design and analysis of the necessary modification and proposed future design is further detailed in the following paper.
Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0–19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.
Background: Chemistry and particularly enzymology at surfaces is a topic of rapidly growing interest, both in terms of its role in biological systems and its application in biocatalysis. Existing protein immobilization approaches, including noncovalent or covalent attachments to solid supports, have difficulties in controlling protein orientation, reducing nonspecific absorption and preventing protein denaturation. New strategies for enzyme immobilization are needed that allow the precise control over orientation and position and thereby provide optimized activity.
Methodology/Principal Findings: A method is presented for utilizing peptide ligands to immobilize enzymes on surfaces with improved enzyme activity and stability. The appropriate peptide ligands have been rapidly selected from high-density arrays and when desirable, the peptide sequences were further optimized by single-point variant screening to enhance both the affinity and activity of the bound enzyme. For proof of concept, the peptides that bound to β-galactosidase and optimized its activity were covalently attached to surfaces for the purpose of capturing target enzymes. Compared to conventional methods, enzymes immobilized on peptide-modified surfaces exhibited higher specific activity and stability, as well as controlled protein orientation.
Conclusions/Significance: A simple method for immobilizing enzymes through specific interactions with peptides anchored on surfaces has been developed. This approach will be applicable to the immobilization of a wide variety of enzymes on surfaces with optimized orientation, location and performance, and provides a potential mechanism for the patterned self-assembly of multiple enzymes on surfaces.
The large-scale use of antivirals during influenza pandemics poses a significant selection pressure for drug-resistant pathogens to emerge and spread in a population. This requires treatment strategies to minimize total infections as well as the emergence of resistance. Here we propose a mathematical model in which individuals infected with wild-type influenza, if treated, can develop de novo resistance and further spread the resistant pathogen. Our main purpose is to explore the impact of two important factors influencing treatment effectiveness: i) the relative transmissibility of the drug-resistant strain to wild-type, and ii) the frequency of de novo resistance. For the endemic scenario, we find a condition between these two parameters that indicates whether treatment regimes will be most beneficial at intermediate or more extreme values (e.g., the fraction of infected that are treated). Moreover, we present analytical expressions for effective treatment regimes and provide evidence of its applicability across a range of modeling scenarios: endemic behavior with deterministic homogeneous mixing, and single-epidemic behavior with deterministic homogeneous mixing and stochastic heterogeneous mixing. Therefore, our results provide insights for the control of drug-resistance in influenza across time scales.