Self-assembled films from WO(3): Electrochromism and lithium ion diffusion

WO(3)/chitosan and WO(3)/chitosan/poly(ethylene oxide) (PEO) films were prepared by the layer-by-layer method. The presence of chitosan enabled PEO to be carried into the self-assembled structure, contributing to an increase in the Li(+) diffusion rate. On the basis of the galvanostatic intermittent titration technique (GITT) and the quadratic logistic equation (QLE), a spectroelectrochemical method was used for determination of the ""optical"" diffusion coefficient (D(op)), enabling analysis of the Li(+) diffusion rate and, consequently, the coloration front rate in these host matrices. The D(op) values within the WO(3)/chitosan/PEO film were significantly higher than those within the WO(3)/chitosan film, mainly for higher values of injected charge. The presence of PEO also ensured larger accessibility to the electroactive sites, in accordance with the method employed here. Hence, this spectroelectrochemical method allowed us to separate the contribution of the diffusion process from the number of accessible electroactive sites in the materials, thereby aiding a better understanding of the useful electrochemical and electrochromic properties of these films for use in electrochromic devices. (C) 2010 Elsevier B.V. All rights reserved.

Self and cross-velocity correlation functions and diffusion coefficients in liquids: a molecular dynamics study of binary mixtures of soft spheres

Molecular dynamics simulation is applied to the study of the diffusion properties in binary liquid mixtures made up of soft-sphere particles with different sizes and masses. Self- and distinct velocity correlation functions and related diffusion coefficients have been calculated. Special attention has been paid to the dynamic cross correlations which have been computed through recently introduced relative mean molecular velocity correlation functions which are independent on the reference frame. The differences between the distinct velocity correlations and diffusion coefficients in different reference frames (mass-fixed, number-fixed, and solvent-fixed) are discussed.

Predicting diffusion of innovations with self-organisation and machine learning

The main subject of this master's thesis was predicting diffusion of innovations. The prediction was done in a special case: product has been available in some countries, and based on its diffusion in those countries the prediction is done for other countries. The prediction was based on finding similar countries with Self-Organizing Map~(SOM), using parameters of countries. Parameters included various economical and social key figures. SOM was optimised for different products using two different methods: (a) by adding diffusion information of products to the country parameters, and (b) by weighting the country parameters based on their importance for the diffusion of different products. A novel method using Differential Evolution (DE) was developed to solve the latter, highly non-linear optimisation problem. Results were fairly good. The prediction method seems to be on a solid theoretical foundation. The results based on country data were good. Instead, optimisation for different products did not generally offer clear benefit, but in some cases the improvement was clearly noticeable. The weights found for the parameters of the countries with the developed SOM optimisation method were interesting, and most of them could be explained by properties of the products.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Transdentinal diffusion and cytotoxicity of self-etching adhesive systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Electrochemical and spectroscopic characterization of screen-printed gold-based electrodes modified with self-assembled monolayers and Tc85 protein

This work investigates the formation of self-assembled monolayers (SAMs) of cystamine and cystamine-glutaraldehyde on a screen-printed electrode, and the immobilization of the Tc85 protein (from Trypanosoma cruzi) on these monolayers. The methods used included infrared techniques, cyclic voltammetry, and electrochemical impedance spectroscopy. The electrochemical studies were performed at pH 6.9 in 0.1 mol L(-1) phosphate buffer solution containing Fe(CN)(6)(-3/-4) redox species. The surface coverage (0) of the electrode was 0.10 (cystamine), 0.35 (cystamine-glutaraldehyde) and 0.84 (Tc85). Interpretation of electrochemical impedance spectroscopy results was based on a charge-transfer reaction involving Fe(CN)(6)(-3/-4) species at high frequencies, followed by a diffusion through the monolayers at lower frequencies. Estimates of the electrode surface coverage, active site radius, and distance between two adjacent sites assumed that charge transfer occurred at the active sites, and that there was a planar diffusion of redox species to these sites. (C) 2009 Elsevier B.V. All rights reserved.

Two-wave-mixing induced self-focusing in an active photorefractive oscillator

We derive a nonlinear wave equation for a signal beam which is coupled to a pump beam by two-wave-mixing in a photorefractive crystal. This equation describes self-focusing of the signal beam. We compare two-wave-mixing induced spatial self-focusing of single-pass experiments in a diffusion-type photorefractive crystal and of a photorefractive oscillator using the same crystal. We observe that the nonlinear refractive index change in the oscillator is decreased while increasing resonator losses.

Spectroelectrochemical Properties and Lithium Ion Storage in Self-Assembled Nanocomposites from TiO(2)

Layer-by-layer (LbL) nanocomposite films from TiO(2) nanoparticles and tungsten-based oxides (WO(x)H(y)), as well as dip-coating films of TiO(2) nano particles, were prepared and investigated by electrochemical techniques under visible light beams, aiming to evaluate the lithium ion storage and chromogenic properties. Atomic force microscopy (AFM) images were obtained for morphological characterization of the Surface of the materials, which have similar roughness. Cyclic voltammetry and chronoamperometry measurements indicated high storage capacity of lithium ions in the LbL nanocomposite compared with the dip-coating film, which was attributed to the faster lithium ion diffusion rate within the self-assembled matrix. On the basis of the data obtained from galvanostatic intermittent titration technique (GITT), the values of lithium ion diffusion coefficient (D(Li)) for TiO(2)/WO(x)H(y) were larger compared with those for TiO(2). The rate of the coloration front in the matrices was investigated using a spectroelectrochemical method based oil GITT, allowing the determination of the ""optical"" diffusion coefficient (D(op)) as a function of the amount of lithium ions previously inserted into the matrices. The Values of D(Li) and D(op) suggested the existence of phases with distinct contribution to lithium ion diffusion rates and electrochromic efficiency. Moreover, these results aided a better understanding of the temporal change of current density and absorbance during the ionic electro-insertion, which is important for the possible application of these materials in lithium ion batteries and electrohromic devices.

Percutaneous absorption of sunscreen agents from liquid paraffin: Self-association of octyl salicylate and effects on skin flux

This study provides an investigation of the availability of octyl salicylate (OS), a common sunscreen agent, from liquid paraffin and the effect of OS on skin permeability. A model membrane system to isolate the vehicle effect from membrane permeability has been developed. Partitioning of OS between liquid paraffin and aqueous receptor phases was conducted. Partition coefficients increased with increase in OS concentration. A range of OS concentrations in liquid paraffin was diffused across human epidermis and synthetic membranes into 4% bovine serum albumin in phosphate-buffered saline and 50% ethanol. Absorption profiles of OS obtained from silicone and low-density polyethylene (LDPE) membranes were similar to each other but higher than for the high-density polyethylene [HDPE (3 times)] membrane and human epidermis (15 times). The steady state fluxes and apparent permeability coefficients (K-p') obtained from the diffusion studies showed the same trends with all membranes, except for the HDPE membrane which showed greater increase in flux and K-p' at concentrations above 30%. IR spectra showed that several bands of OS were shifted with concentrations, and the molecular models further suggested that the main contribution to the self-association is from non-1,4 van der Waals interactions.

Measuring macromolecular diffusion using heteronuclear multiple-quantum pulsed-field-gradient NMR

We have previously shown that H-1 pulsed-field-gradient (PFG) NMR spectroscopy provides a facile method for monitoring protein self-association and can be used, albeit with some caveats, to measure the apparent molecular mass of the diffusant [Dingley et al. (1995) J. Biomol. NMR, 6, 321-328]. In this paper we show that, for N-15-labelled proteins, selection of H-1-N-15 multiple-quantum (MQ) coherences in PFG diffusion experiments provides several advantages over monitoring H-1 single-quantum (SQ) magnetization. First, the use of a gradient-selected MQ filter provides a convenient means of suppressing resonances from both the solvent and unlabelled solutes. Second, H-1-N-15 zero-quantum coherence dephases more rapidly than H-1 SQ coherence under the influence of a PFG. This allows the diffusion coefficients of larger proteins to be measured more readily. Alternatively, the gradient length and/or the diffusion delay may be decreased, thereby reducing signal losses from relaxation. In order to extend the size of macromolecules to which these experiments can be applied, we have developed a new MQ PFG diffusion experiment in which the magnetization is stored as longitudinal two-spin order for most of the diffusion period, thus minimizing sensitivity losses due to transverse relaxation and J-coupling evolution.

Could cell membranes produce acoustic streaming? Making the case for synechococcus self-propulsion

Sir James Lighthill proposed in 1992 that acoustic streaming occurs in the inner ear, as part of the cochlear amplifier mechanism. Here we hypothesize that some of the most ancient organisms use acoustic streaming not only for self-propulsion but also to enhance their nutrient uptake. We focus on a motile strain of Synechococcus, a yanobacteria whose mechanism for self-propulsion is not known. Molecular motors could work like piezoelectric transducers acting on the crystalline structure surrounding the outer cell membrane. Our calculations show that a traveling surface acoustic wave (SAW)could account for the observed velocities. These SAW waves will also produce a non-negligible Stokes layer surrounding the cell: motion within this region being essentially chaotic. Therefore, an AS mechanism would be biologically advantageous, enhancing localized diffusion processes and consequently, chemical reactions. We believe that acoustic streaming, produced by nanometer scale membrane vibrations could be widespread in cell biology. Other possible instances are yeast cells and erythrocytes. Flows generated by acoustic streaming may also be produced by silica coated diatoms along their raphe. We note that microelectromechanical (MEMS) acoustic streaming devices were first introduced in the 1990’s. Nature may have preceded this invention by 2.7 Gyr.

Hyperbolic reaction-diffusion equations for a forest fire model

Forest fire models have been widely studied from the context of self-organized criticality and from the ecological properties of the forest and combustion. On the other hand, reaction-diffusion equations have interesting applications in biology and physics. We propose here a model for fire propagation in a forest by using hyperbolic reaction-diffusion equations. The dynamical and thermodynamical aspects of the model are analyzed in detail

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Diffusion of Administrative Innovation: TQM Implementation and Effectiveness in a Global

The main objective of this dissertation is to create new knowledge on an administrative innovation, its adoption, diffusion and finally its effectiveness. In this dissertation the administrative innovation is approached through a widely utilized management philosophy, namely the total quality management (TQM) strategy. TQM operationalizes a self-assessment procedure, which is based on continual improvement principles and measuring the improvements. This dissertation also captures the theme of change management as it analyzes the adoption and diffusion of the administrative innovation. It identifies innovation characteristics as well as organisational and individual factors explaining the adoption and implementation. As a special feature, this study also explores the effectiveness of the innovation based on objective data. For studying the administrative innovation (TQM model), a multinational Case Company provides a versatile ground for a deep, longitudinal analysis. The Case Company started the adoption systematically in the mid 1980s in some of its units. As part of their strategic planning today, the procedure is in use throughout the entire global company. The empirical story begins from the innovation adoption decision that was made in the Case Company over 22 years ago. In order to be able to capture the right atmosphere and backgrounds leading to the adoption decision, key informants from that time were interviewed, since the main target was to clarify the dynamics of how an administrative innovation develops. In addition, archival material was collected and studied, available memos and data relating to the innovation, innovation adoption and later to the implementation contained altogether 20500 pages of documents. A survey was furthermore conducted at the end of 2006 focusing on questions related to the innovation, organization and leadership characteristics and the response rate totalled up to 54%. For measuring the effectiveness of the innovation implementation, the needed longitudinal objective performance data was collected. This data included the profit unit level experience of TQM, the development of the self assessment scores per profit unit and performance data per profit unit measured with profitability, productivity and customer satisfaction. The data covered the years 1995-2006. As a result, the prerequisites for the successful adoption of an administrative innovation were defined, such as the top management involvement, support of the change agents and effective tools for implementation and measurement. The factors with the greatest effect on the depth of the implementation were the timing of the adoption and formalization. The results also indicated that the TQM model does have an effect on the company performance measured with profitability, productivity and customer satisfaction. Consequently this thesis contributes to the present literature (i) by taking into its scope an administrative innovation and focusing on the whole innovation implementation process, from the adoption, through diffusion until its consequences, (ii) because the studied factors with an effect on the innovation adoption and diffusion are multifaceted and grouped into individual, organizational and environmental factors, and a strong emphasis is put on the role of the individual change agents and (iii) by measuring the depth and consistency of the administrative innovation. This deep analysis was possible due to the availability of longitudinal data with triangulation possibilities.

Acceleration of Solar Energetic Particles in coronal shocks through self-generated turbulence

The acceleration of solar energetic particles (SEPs) by flares and coronal mass ejections (CMEs) has been a major topic of research for the solar-terrestrial physics and geophysics communities for decades. This thesis discusses theories describing first-order Fermi acceleration of SEPs through repeated crossings at a CME-driven shock. We propose that particle trapping occurs through self-generated Alfvén waves, leading to a turbulent trapping region in front of the shock. Decelerating coronal shocks are shown to be capable of efficient SEP acceleration, provided seed particle injection is sufficient. Quasi-parallel shocks are found to inject thermal particles with good efficiency. The roles of minimum injection velocities, cross-field diffusion, downstream scattering efficiency and cross-shock potential are investigated in detail, with downstream isotropisation timescales having a major effect on injection efficiency. Accelerated spectra of heavier elements up to iron are found to exhibit significantly harder spectra than protons. Accelerated spectra cut-off energies are found to scale proportional to (Q/A)^1.5, which is explained through analysis of the spectral shape of amplified Alfvénic turbulence. Acceleration times to different threshold energies are found to be non-linear, indicating that self-consistent time-dependent simulations are required in order to expose the full extent of acceleration dynamics. The well-established quasilinear theory (QLT) of particle scattering is investigated by comparing QLT scattering coefficients with those found via full-orbit simulations. QLT is found to overemphasise resonance conditions. This finding supports the simplifications implemented in the presented coronal shock acceleration (CSA) simulation software. The CSA software package is used to simulate a range of acceleration scenarios. The results are found to be in agreement with well-established particle acceleration theory. At the same time, new spatial and temporal dynamics of particle population trapping and wave evolution are revealed.