Computational studies of polymer electrolyte complexes by molecular dynamics and molecular vibrations by principal component analysis.

The second part (Chapter 4 and 5) focuses on computing vibrational frequencies and modes by using a new technique, principal component analysis (PCA) which is broadly used in signal processing, pattern recognition, and multivariate analysis. The advantages of PCA to incorporate anharmonicity in the calculated spectra over the conventional normal mode analysis and Fourier transform are presented in Chapter 4. PCA-derived frequencies of harmonic, anharmonic (with a quartic term in the potential energy), and Langevin oscillators and water molecules are more accurate than the frequencies calculated by normal mode analysis and Fourier transforms, in comparison with analytical or experimental results. New procedures in order to improve the PCA method including the determination of the vibrational energy, removal of the translations and rotations from the trajectories, and the treatment of flexible molecules based on fragments are proposed. More test cases of water, methane, water dimer, and ethane are provided to show that the frequencies are greatly improved by applying these new procedures in addition to the original PCA method. The last chapter is a demonstration of one of PCA's abilities to study molecular vibrational problems. (Abstract shortened by UMI.)The first three chapters of this dissertation are concerned with the structural properties of solid polymer electrolyte systems. Model polymers of poly(ethylene oxide) (PEO) and poly(ethylenimine) (PEI) containing four repeat units were studied by using molecular dynamics simulations. The chain dimensions, dihedral angle distributions, triad conformations were analyzed for PEO, PEI, and PEO:salt systems. The special ability of PEI chains to form two kinds of intra-chain hydrogen bonding, the single and double hydrogen bonding, makes the conformations of PEI chains more compact than PEO chains. The structural properties of PEO:LiCF3SO3 (lithium triflate) and PEO:NaCF3SO3 (having an ether oxygen: salt ratio of 10:1) complexes including the effects of oxygen-salt coordination on the polymer conformations and the ionic aggregation were also analyzed. The results show that the PEO chains contribute fewer oxygens (1.6 to Li+ and 2.2 to Na+ at 300K) to the cations than the triflate ions (4.6 and 4.9) and high temperature weakens PEO chain-cation coordination further. The species and the populations of different ionic aggregates calculated from MD simulations agree well with experimental values. All the results will help the understanding of ionic conductivity mechanisms in polymers

Atomic resolution imaging at 2.5 GHz using near-field microwave microscopy

Atomic resolution imaging is demonstrated using a hybrid scanning tunneling/near-field microwave microscope (microwave-STM). The microwave channels of the microscope correspond to the resonant frequency and quality factor of a coaxial microwave resonator, which is built in to the STM scan head and coupled to the probe tip. We find that when the tip-sample distance is within the tunneling regime, we obtain atomic resolution images using the microwave channels of the microwave-STM. We attribute the atomic contrast in the microwave channels to GHz frequency current through the tip-sample tunnel junction. Images of the surfaces of HOPG and Au(111) are presented.Comment: 9 pages, 5 figures, submitted to Applied Physics Letter

Unreliable quantitation of species abundance based on high-throughput sequencing data of zooplankton communities

High-throughput sequencing (HTS) is rapidly becoming a popular and robust tool to characterize biodiversity of complex communities, especially for those dominated by microscopic species such as zooplankton. The popular use of HTS-based methods has prompted a possible method of inferring relative species abundance from sequencing data. However, these methods remain largely untested in many communities as to whether sequence data can reliably quantify relative species abundance. Here we tested the relationship between species abundance and sequence abundance in zooplankton using 2 methods: (1) spiking known amounts of indicator species into existing zooplankton communities, and (2) comparing results obtained from parallel replicates for the same natural zooplankton communities. Although we detected a general trend that low-abundance species usually corresponded to low-abundance sequence reads, further statistical analyses revealed that sequencing data could not reliably quantify relative species abundance, even for the same indicator species spiked into different zooplankton communities. The distribution of sequence reads statistically varied even between parallel replicates of the same natural zooplankton communities. Our study reveals that sequence abundance may generally qualitatively reflect species abundance as the general trend between these 2 variables exists; however, extra caution is required when using HTS-based approaches to make quantitative inferences regarding zooplankton communities

An efficient threshold dynamics method for topology optimization for fluids

We propose an efficient threshold dynamics method for topology optimization for fluids modeled with the Stokes equation. The proposed algorithm is based on minimization of an objective energy function that consists of the dissipation power in the fluid and the perimeter approximated by nonlocal energy, subject to a fluid volume constraint and the incompressibility condition. We show that the minimization problem can be solved with an iterative scheme in which the Stokes equation is approximated by a Brinkman equation. The indicator functions of the fluid-solid regions are then updated according to simple convolutions followed by a thresholding step. We demonstrate mathematically that the iterative algorithm has the total energy decaying property. The proposed algorithm is simple and easy to implement. A simple adaptive time strategy is also used to accelerate the convergence of the iteration. Extensive numerical experiments in both two and three dimensions show that the proposed iteration algorithm converges in much fewer iterations and is more efficient than many existing methods. In addition, the numerical results show that the algorithm is very robust and insensitive to the initial guess and the parameters in the model.Comment: 23 pages, 24 figure