Structural modification and characterization of lignosulfonate by a reaction in an alkaline medium for its incorporation into phenolic resins

We studied the enhancement of lignin reactivity in an alkaline medium, using sodium hydroxide in a microreactor set. The chemical composition and structural characterization of the reacted lignosulfonate in terms of the phenolic hydroxyl groups, aromatic protons, weight‐average molecular weight, number‐average molecular weight, and lignosulfonate content of all reacted lignins were determined. The techniques that we used were ultraviolet spectroscopy, proton nuclear magnetic resonance spectroscopy, and aqueous gel permeation chromatography. Using response surface methodology, we studied how the temperature and reaction time affected the lignin properties. The reaction conditions were temperatures between 116 and 180°C and reaction times between 18 and 103 min. Modeled response surfaces showed that the two factors affected the lignin properties within the studied ranges. The phenolic hydroxyl groups, aro matic protons, and lignosulfonate content increased when the severity of the treatment increased. The weight‐average molecular weight, number‐average molecular weight, and solid yield (%) decreased when the severity of the treatment increased. The reactivity of the modified lignins was studied with a formaldehyde reactivity test: more severe conditions produced greater improvements in the formaldehyde reactivity. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3286–3292, 2006     

Neural network based defect detection and depth estimation in TNDE

For many years, applications of the TNDE (Thermographic NonDestructive Evaluation) technique has been limited due to the complex non-linearity nature of related inversion problems such as defect depth estimation. Artificial neural networks have recently obtained success in revealing and providing quantitative information concerning defects in TNDE. In this paper, a three dimensional thermal model for non-homogenous materials such as carbon fiber reinforced plastic (CFRP) is first given. The modeling results are compared with the analytical solution based on Duhamel's theorem. Two back propagation neural networks (NN) as defect detector and depth estimator are then presented. Finally, simulated and experimental results are presented and discussed.     

Infrared multiphoton dissociation tandem charge detection-mass spectrometry of single megadalton electrosprayed ions

This work presents the implementation of tandem mass spectrometry for experiments on single electrosprayed ions from compounds of megadalton (MDa) molecular weight, using two charge detection devices. The first mass spectrometry stage (first charge detection device) combined with an ion gate allows both mass-to-charge ratio and charge selections of the megadalton ion of interest. The second stage is based on an electrostatic ion trap and consists of an image charge detection tube mounted between two ion mirrors. Single MDa ions can be stored for several dozen milliseconds. During the trapping time, single ions can be irradiated by a continuous wavelength CO(2) laser. We observe stepwise changes in the charge of a single trapped ion owing to multiphoton activation. Illustration of infrared multiphoton dissociation tandem mass spectrometry are given for single megadalton ions of poly(ethylene oxide)s and DNAs.     

Interactive computation and rendering of Finite-time Lyapunov Exponent fields

In this paper, we present a novel technique that allows for the coupled computation and visualization of salient flow structures at interactive frame rates. Our approach is built upon a hierarchical representation of the Finite-time Lyapunov Exponent (FTLE) field, which is adaptively sampled and rendered to meet the need of the current visual setting. The performance of our method allows the user to explore large and complex data sets across scales and to inspect their features at arbitrary resolution. The paper discusses an efficient implementation of this strategy on graphics hardware and provides results for an analytical flow and several CFD simulation data sets.     

Acceptor formation in Mg-doped,indium-rich GaxIn1?xN: evidence for p-type conductivity

We report on the Mg-doped, indium-rich Ga_xIn_1−xN (x < 30). In the undoped material, the intrinsic electron density is very high and as a result there is no detectable photoconductivity (PC) signal within the range of temperatures of 30 <T < 300 K. In the Mg-doped material however, where the conductivity is reduced, there is a strong PC spectrum with two prominent low-energy peaks at 0.65 and 1.0 eV and one broad high-energy peak at around 1.35 eV. The temperature dependence of the spectral photoconductivity under constant illumination intensity, at T > 150 K, is determined by the longitudinal-optical phonon scattering together with the thermal regeneration of non-equilibrium minority carriers from traps with an average depth of 103 ± 15 meV. This value is close to the Mg binding energy in GaInN. The complementary measurements of transient photoluminescence at liquid He temperatures give the e-A⁰ binding energy of approximately 100 meV. Furthermore, Hall measurements in the Mg-doped material also indicate an activated behaviour with an acceptor binding energy of 108 ± 20 meV.