Physical and chemical properties of polypyrrole–carbon fiber interphases formed by aqueous electrosynthesis

The properties of carbon fibers modified by aqueous electrochemical synthesis of pyrrole has been determined by using the dynamic contact angle analyzer (DCA), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). Electrochemical process parameters such as the initial pyrrole concentration, electrolyte concentration, applied voltage, electrolyte type, and reaction time were systematically varied, and their impact on the polypyrrole–carbon fiber interphases surface free energy and morphology was ascertained. The surface free energies of the polypyrrole–carbon fiber interphases were obtained by using single fiber filaments. SEM analysis of the interphases revealed several distinct surface structures, including smooth, porous, granular, microspheroidal, and leafoidal morphologies. The noncoated but commercially surface oxidized carbon fibers have smooth surface morphology with occasional longitudinal striations. FTIR analysis of the polypyrrole interphases confirmed that the counterions derived from the electrolytes were incorporated into the film. The surface free energies of the electrochemically formed polypyrrole–carbon fiber interphases equivalent to 60–75 dynes/cm, was determined to be up to 40% higher than that for the surface oxidized but unsized carbon fibers equivalent to 50 dynes/cm. This improvement in the surface free energies of the polypyrrole–carbon fiber interphases suggests easy wettability by polymer matrices such as epoxy resin, γ ˜ 47 dynes/cm and, polyimide matrix, γ ˜ 45 dynes/cm. © 1996 John Wiley & Sons, Inc.     

Morphology,mechanical and thermal properties of nano-structured full IPNs based on polyisoprene and PMMA

Morphology, mechanical properties, thermal stability and gas transport behaviour of interpenetrating polymer networks (IPNs) based on PI/PMMA have been investigated using various techniques. Crosslinking level of both phases and concentration of PMMA were found to have noticeable effects on the compatibility of immiscible components during IPN formation. Effect of crosslinking was studied by preparing IPNs with varying amount of crosslinker concentration in each phase. Crosslinking of both phases facilitated deeper interpenetrations between both networks, and certain degree of compatibility is attained during IPN formation. Nanometre-sized domains were observed for highly crosslinked IPN. Lower concentration of PMMA was found to favour phase mixing more effectively than others. DSC curve of 65/35 IPN showed a broad transition arising from the α and β-relaxations of PMMA due to the higher flexibility attained by mixing with the highly mobile PI chains. The mechanical properties of the IPNs were correlated to the morphology of the system and 50/50 composition showed maximum mechanical properties among the studied compositions. Mode of mechanical failure, thermal stability and gas transport behaviour were also analysed. IPNs having nanometre-sized domains showed least gas permeability among the studied samples.     

Alkali-promoted hydrothermal gasification of biomass food processing waste: A parametric study

A parametric study of alkali-promoted hydrogen gas production from by-products from food-based biomass, such as glucose, molasses and rice bran, under hydrothermal conditions has been carried out. Partial oxidation of the biomass samples was aided by the addition of hydrogen peroxide and experiments were carried out in the presence of sodium hydroxide. The effects of reaction temperature, reaction time and feed concentration on the conversion of glucose, molasses and rice bran to gaseous products under hydrothermal conditions were investigated. The reaction time and reaction temperature were investigated in the range of 0–120 min and 330–390 °C, respectively. The results confirmed the positive influence of NaOH in the production of hydrogen gas via the water–gas shift reaction. In the presence of the alkali, no tar/oil and char were observed. The hydrogen gas yield increased when the reaction temperature and reaction time increased. It was observed that higher reaction temperature led to an increase in the amount of methane gas produced. With increasing feed concentration, the yields of other gases such as CO, CO₂, CH₄ and C₂–C₄ increased, while hydrogen gas production decreased for all the biomass samples. The generation of gaseous products from the molasses and rice bran showed a similar trend to that of glucose, under identical test conditions.     

Effect of clay on the corrosion inhibition and dynamic mechanical properties of epoxy ester–polyurea–polysiloxane hybrid coatings

The corrosion resistance of polymeric coatings containing epoxy ester, polyurea, and polymethylhydrosiloxane was significantly improved by the addition of cloisite 15A organoclay. The weight percent of organoclay was varied from 0.5 to 10%. The presence of organoclay in the coatings was confirmed using the Fourier transformed infrared spectroscopy. The effect of organoclay on the surface energy of the coatings was analyzed by measuring contact angle with a video contact angle analyzer and using water and iodomethane as the probing liquids. The surface energy of the coatings increased with increasing organoclay concentration. The corrosion resistant properties were measured by direct current polarization technique. The addition of organoclay enhanced the corrosion resistance of the coatings, and the best corrosion resistance was shown by coating containing 1% organoclay. The dynamic mechanical property of the coatings was determined using the dynamic mechanical spectrometer. The glass transition temperature of the films decreased significantly with the addition of organoclay up to 1% after which it increased with additional increase in the wt% of organoclay. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Natural gas—International: China to supply huge natural gas growth

As the projected fastest-growing fossil fuel through 2030, natural gas is viewed as the “bridge” source to a more sustainable energy future. Combusted gas emits 30 percent less carbon dioxide (CO₂) than oil and 45 percent less than coal and has lower levels of nitrogen oxides, sulfur dioxide, and particulate matter.     

Carbon fiber-polyaniline composites: Kinetics of electrodeposition of polyaniline onto carbon fibers by cyclic voltammetry

Homogeneous and uniform coatings of polyaniline were successfully deposited on carbon fibers by an aqueous electrodeposition technique using p-toluene sulfonic acid as the electrolyte. Electrochemical deposition of aniline was carried out by cyclic voltammetry in the potential range of ?0.2 V to 1.0 V versus saturated calomel electrode (SCE). The electrochemical deposition parameters such as the number of cycles, scan rate (SR), initial monomer ([M]), and electrolyte concentration ([E]) were systematically varied. The amount of composite coatings on carbon fibers was dependent on the electrochemical deposition parameters. From a weight gain analysis, the rate of the reactions (R p ) was calculated. As the aniline concentration was increased up to 0.35 M and electrolyte concentration up to 0.5 M, the deposition rate also increased, whereas an increase in scan rate decreased the deposition rate. Kinetic analysis showed that the rate equation for the p-toluene sulfonic acid system is R p ∝SR ?1.25 [M] 0.73 [E] 0.95 . IR spectra also showed an increase in the deposition of polyaniline coatings on carbon fibers with a decrease in the scan rate and an increase in both monomer and electrolyte concentration. The ratio of two oxidation states of polyaniline obtained during electrodeposition, namely emeraldine and pernigraniline, can be varied by changing the electrochemical deposition parameters.     

In situ growth of multilayered crystals in amorphous matrix: Thermal,dynamic mechanical,and morphological analysis of nylon‐6/epoxy composites

A new procedure for processing of epoxy/polyamide blend was explored via solution polymerization of ε‐caprolactam in N‐methylpyrollidone (NMP), which resulted in a suspension of nylon‐6 in solvent at room temperature. The suspension was blended with water based epoxy resin using mechanical stirring at room temperature. Several films were prepared from blend by varying the amount of nylon‐6 without curing agent. All films were fully characterized for thermal and dynamic mechanical properties using differential scanning calorimetry and dynamic mechanical analysis. The addition of nylon‐6 had a plasticizing effect on epoxy evident by decrease in glass transition temperature (T_g). The reaction between nylon‐6 and epoxy was studied using Fourier transform infrared spectroscopy by following the characteristic epoxy peak (914 cm^?1). The growth of nylon‐6 crystals in epoxy matrix lead to spherulitic multiphase morphology, which was observed under scanning electron microscope. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 3319–3327, 2013     

Dynamically adding symbolically meaningful nodes to knowledge-based neural networks

Traditional connectionist theory-refinement systems map the dependencies of a domain-specific rule base into a neural network, and then refine this network using neural learning techniques. Most of these systems, however, lack the ability to refine their network's topology and are thus unable to add new rules to the (reformulated) rule base. Therefore, with domain theories that lack rules, generalization is poor, and training can corrupt the original rules — even those that were initially correct. The paper presents TopGen, an extension to the KBANN algorithm, which heuristically searches for possible expansions to the KBANN network. TopGen does this by dynamically adding hidden nodes to the neural representation of the domain theory, in a manner that is analogous to the adding of rules and conjuncts to the symbolic rule base. Experiments indicate that the method is able to heuristically find effective places to add nodes to the knowledge bases of four real-world problems, as well as an artificial chess domain. The experiments also verify that new nodes must be added in an intelligent manner. The algorithm showed statistically significant improvements over the KBANN algorithm in all five domains.     

Creating Advice-Taking Reinforcement Learners

Learning from reinforcements is a promising approach for creating intelligent agents. However, reinforcement learning usually requires a large number of training episodes. We present and evaluate a design that addresses this shortcoming by allowing a connectionist Q-learner to accept advice given, at any time and in a natural manner, by an external observer. In our approach, the advice-giver watches the learner and occasionally makes suggestions, expressed as instructions in a simple imperative programming language. Based on techniques from knowledge-based neural networks, we insert these programs directly into the agent's utility function. Subsequent reinforcement learning further integrates and refines the advice. We present empirical evidence that investigates several aspects of our approach and shows that, given good advice, a learner can achieve statistically significant gains in expected reward. A second experiment shows that advice improves the expected reward regardless of the stage of training at which it is given, while another study demonstrates that subsequent advice can result in further gains in reward. Finally, we present experimental results that indicate our method is more powerful than a naive technique for making use of advice.     

Symbolic and Neural Learning Algorithms: An Experimental Comparison

Despite the fact that many symbolic and neural network (connectionist) learning algorithms address the same problem of learning from classified examples, very little is known regarding their comparative strengths and weaknesses. Experiments comparing the ID3 symbolic learning algorithm with the perception and backpropagation neural learning algorithms have been performed using five large, real-world data sets. Overall, backpropagation performs slightly better than the other two algorithms in terms of classification accuracy on new examples, but takes much longer to train. Experimental results suggest that backpropagation can work significantly better on data sets containing numerical data. Also analyzed empirically are the effects of (1) the amount of training data, (2) imperfect training examples, and (3) the encoding of the desired outputs. Backpropagation occasionally outperforms the other two systems when given relatively small amounts of training data. It is slightly more accurate than ID3 when examples are noisy or incompletely specified. Finally, backpropagation more effectively utilizes a distributed output encoding.