Diffusion of pentane isomers in faujasite-type zeolites : NMR and molecular dynamics study

Diffusion of pentane isomers in zeolites NaX has been investigated using pulsed field gradient nuclear magnetic resonance (PFG-NMR) and molecular dynamics (MD) techniques respectively. Temperature and concentration dependence of diffusivities have been studied. The diffusivities obtained from NMR are roughly an order of magnitude smaller than those obtained from MD. The dependence of diffusivity on loading at high temperatures exhibits a type I behavior according to the classification of Karger and Pfeifer 1]. NMR diffusivities of the isomers exhibit the order D(n-pentane) > D(isopentane) > D(neopentane). The results from MD suggest that the diffusivities of the isomers follow the order D(n-pentane) < D(isopentane) < D(neopentane). The activation energies from NMR show E-a(n-pentane) < E-a(isopentane) < E-a(neopentane) whereas those from MD suggest the order E-a(n-pentane) > (isopentane) > E-a(neopentane). The latter follows the predictions of levitation effect whereas those of NMR appears to be due to the presence of defects in the zeolite crystals. The differences between diffusivities estimated by NMR and MD are attributed to the longer time and length scales sampled by the NMR technique, as compared to MD. (C) 2012 Elsevier Inc. All rights reserved.

A multichannel sampling method for 2-D finite-rate-of-innovation signals

We address the problem of sampling and reconstruction of two-dimensional (2-D) finite-rate-of-innovation (FRI) signals. We propose a three-channel sampling method for efficiently solving the problem. We consider the sampling of a stream of 2-D Dirac impulses and a sum of 2-D unit-step functions. We propose a 2-D causal exponential function as the sampling kernel. By causality in 2-D, we mean that the function has its support restricted to the first quadrant. The advantage of using a multichannel sampling method with causal exponential sampling kernel is that standard annihilating filter or root-finding algorithms are not required. Further, the proposed method has inexpensive hardware implementation and is numerically stable as the number of Dirac impulses increases.

Generalized eigenvalue decomposition of the field autocorrelation in correlation diffusion of photons in turbid media

We propose a novel numerical method based on a generalized eigenvalue decomposition for solving the diffusion equation governing the correlation diffusion of photons in turbid media. Medical imaging modalities such as diffuse correlation tomography and ultrasound-modulated optical tomography have the (elliptic) diffusion equation parameterized by a time variable as the forward model. Hitherto, for the computation of the correlation function, the diffusion equation is solved repeatedly over the time parameter. We show that the use of a certain time-independent generalized eigenfunction basis results in the decoupling of the spatial and time dependence of the correlation function, thus allowing greater computational efficiency in arriving at the forward solution. Besides presenting the mathematical analysis of the generalized eigenvalue problem on the basis of spectral theory, we put forth the numerical results that compare the proposed numerical method with the standard technique for solving the diffusion equation.

Growth of Phases and Diffusion of Components in the W-Pt System

Growth kinetics, phase boundary compositions, interdiffusion coefficients and the relative mobilities of the components are determined in the W-Pt system. The measured phase boundary compositions for the gamma phase are found to be different from the reported phase diagram. The interdiffusion coefficient and the activation energy decrease in the Pt(W) solid solution with increasing W content. An estimation of the parabolic growth constants and average interdiffusion coefficients in the gamma phase indicates that the diffusion process should be explained based on the estimation of diffusion parameters, which otherwise could lead to a wrong conclusion. The estimation of the relative mobilities of the components in the gamma phase indicates that Pt has a much higher diffusion rate than W. This is explained with the help of the crystal structure and the possible point defects present on different sublattices.

Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle

The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.

Diffusion of components via different modes during growth of the A15-V(3)Gaphase

Based on an interdiffusion study using an incremental diffusion couple in the V-Ga binary system, we have shown that V diffuses via the lattice, whereas Ga does so via grain boundaries, for the growth of the V3Ga phase. We estimate the contributions from the two different mechanisms, which are usually difficult to delineate in an interdiffusion study. Available tracer diffusion studies and the atomic arrangement in the crystal structure have been considered for a discussion on the diffusion mechanisms.

ELLIPSE FITTING USING FINITE RATE OF INNOVATION PRINCIPLES

We address the problem of parameter estimation of an ellipse from a limited number of samples. We develop a new approach for solving the ellipse fitting problem by showing that the x and y coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals. Uniform samples of x and y coordinate functions of the ellipse are modeled as a sum of weighted complex exponentials, for which we propose an efficient annihilating filter technique to estimate the ellipse parameters from the samples. The FRI framework allows for estimating the ellipse parameters reliably from partial or incomplete measurements even in the presence of noise. The efficiency and robustness of the proposed method is compared with state-of-art direct method. The experimental results show that the estimated parameters have lesser bias compared with the direct method and the estimation error is reduced by 5-10 dB relative to the direct method.

Ellipse Fitting Using the Finite Rate of Innovation Sampling Principle

Standard approaches for ellipse fitting are based on the minimization of algebraic or geometric distance between the given data and a template ellipse. When the data are noisy and come from a partial ellipse, the state-of-the-art methods tend to produce biased ellipses. We rely on the sampling structure of the underlying signal and show that the x- and y-coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals, and that their parameters are estimable from partial data. We consider both uniform and nonuniform sampling scenarios in the presence of noise and show that the data can be modeled as a sum of random amplitude-modulated complex exponentials. A low-pass filter is used to suppress noise and approximate the data as a sum of weighted complex exponentials. The annihilating filter used in FRI approaches is applied to estimate the sampling interval in the closed form. We perform experiments on simulated and real data, and assess both objective and subjective performances in comparison with the state-of-the-art ellipse fitting methods. The proposed method produces ellipses with lesser bias. Furthermore, the mean-squared error is lesser by about 2 to 10 dB. We show the applications of ellipse fitting in iris images starting from partial edge contours, and to free-hand ellipses drawn on a touch-screen tablet.

Molecular dynamics-based approach to study the anisotropic self-diffusion of molecules in porous materials with multiple cage types: Application to H-2 in losod

Van den Berg, A. W. C., Flikkema, E., Lems, S., Bromley, S. T., Jansen, J. C. (2006). Molecular dynamics-based approach to study the anisotropic self-diffusion of molecules in porous materials with multiple cage types: Application to H-2 in losod. Journal of physical chemistry b, 110 (1), 501-506. RAE2008

Modeling the diffusion of solid copper into liquid solder alloys

During the soldering process, the copper atoms diffuse into liquid solders. The diffusion process determines integrity and the reworking possibility of a solder joint. In order to capture the diffusion scenarios of solid copper into liquid Sn–Pb and Sn–Cu solders, a computer modeling has been performed for 10 s. An analytical model has also been proposed for calculating the diffusion coefficient of copper into liquid solders. It is found that the diffusion coefficient for Sn–Pb solder is 2.74 × 10− 10 m2/s and for Sn–Cu solder is 6.44 × 10−9 m2/s. The modeling results reveal that the diffusion coefficient is one of the major factors that govern the rate at which solid Cu dissolve in the molten solder. The predicted dissolved amounts of copper into solders have been validated with the help of scanning electron microscopic analysis.

Developing a model of innovation implementation for UK SMEs: A path analysis and explanatory case analysis

Continuous large-scale changes in technology and the globalization of markets have resulted in the need for many SMEs to use innovation as a means of seeking competitive advantage where innovation includes both technological and organizational perspectives (Tapscott, 2009). However, there is a paucity of systematic and empirical research relating to the implementation of innovation management in the context of SMEs. The aim of this article is to redress this imbalance via an empirical study created to develop and test a model of innovation implementation in SMEs. This study uses Structural Equation Modelling (SEM) to test the plausibility of an innovation model, developed from earlier studies, as the basis of a questionnaire survey of 395 SMEs in the UK. The resultant model and construct relationship results are further probed using an explanatory multiple case analysis to explore ‘how’ and ‘why’ type questions within the model and construct relationships. The findings show that the
effects of leadership, people and culture on innovation implementation are mediated by business improvement activities relating to Total Quality Management/Continuous Improvement (TQM/CI) and product and process developments. It is concluded that SMEs have an opportunity to leverage existing quality and process improvement activities to move beyond continuous
improvement outcomes towards effective innovation implementation. The article concludes by suggesting areas suitable for further research.

Technological regimes, Schumpeterian patterns of innovation and firm-level productivity growth

The article investigates the relationships between technological regimes and firm-level productivity performance, and it explores how such a relationship differs in different Schumpeterian patterns of innovation. The analysis makes use of a rich dataset containing data on innovation and other economic characteristics of a large representative sample of Norwegian firms in manufacturing and service industries for the period 1998–2004. First, we decompose TFP growth into technical progress and efficiency changes by means of data envelopment analysis. We then estimate an empirical model that relates these two productivity components to the characteristics of technological regimes and a set of other firm-specific factors. The results indicate that: (i) TFP growth has mainly been achieved through technical progress, while technical efficiency has on average decreased; (ii) the characteristics of technological regimes are important determinants of firm-level productivity growth, but their impacts on technical progress are different from the effects on efficiency change; (iii) the estimated model works differently in the two Schumpeterian regimes. Technical progress has been more dynamic in Schumpeter Mark II industries, while efficiency change has been more important in Schumpeter Mark I markets.

A multi-agent-based evolution model of innovation networks in dynamic environments

An innovation network can be considered as a complex adaptive system with evolution affected by dynamic environments. This paper establishes a multi-agent-based evolution model of innovation networks under dynamic settings through computational and logical modeling, and a multi-agent system paradigm. This evolution model is composed of several sub-models of agents' knowledge production by independent innovations in dynamic situations, knowledge learning by cooperative innovations covering agents' heterogeneities, decision-making for innovation selections, and knowledge update considering decay factors. On the basis of above-mentioned sub-models, an evolution rule for multi-agent based innovation network system is given. The proposed evolution model can be utilized to simulate and analyze different scenarios of innovation networks in various dynamic environments and support decision-making for innovation network optimization.

Diffusion of the synthetic pyrethroid permethrin into bed-sediments

Bed-sediments are a sink for many micro-organic contaminants in aquatic environments. The impact of toxic contaminants on benthic fauna often depends on their spatial distribution, and the fate of the parent compounds and their metabolites. The distribution of a synthetic pyrethroid, permethrin, a compound known to be toxic to aquatic invertebrates, was studied using river bed-sediments in lotic flume channels. trans/cis-Permethrin diagnostic ratios were used to quantify the photoisomerization of the trans isomer in water. Rates were affected by the presence of sediment particles and colloids when compared to distilled water alone. Two experiments in dark/light conditions with replicate channels were undertaken using natural sediment, previously contaminated with permethrin, to examine the effect of the growth of an algal biofilm at the sediment-water interface on diffusive fluxes of permethrin into the sediment. After 42 days, the bulk water was removed, allowing a fine sectioning of the sediment bed (i.e., every mm down to 5 mm and then 5-10 mm, then every 10 mm down to 50 mm). Permethrin was detected in all cases down to a depth of 5-10 mm, in agreement with estimates by the Millington and Quirk model, and measurements of concentrations in pore water produced a distribution coefficient (K-d) for each section, High K-d's were observed for the top layers, mainly as a result of high organic matter and specific surface area. Concentrations in the algal biofilm measured at the end of the experiment under light conditions, and increases in concentration in the top 1 mm of the sediment, demonstrated that algal/bacterial biofilm material was responsible for high K-d's at the sediment surface, and for the retardation of permethrin diffusion. This specific partition of permethrin to fine sediment particles and algae may enhance its threat to benthic invertebrates. In addition,the analysis of trans/cis-permethrin isomer ratios in sediment showed greater losses of trans-permethrin in the experiment under light conditions, which may have also resulted from enhanced biological activity at the sediment surface.