Stability enhancement of polypyrrole thin film ammonia sensor by camphor sulfonic acid dopant

Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin...     

An Approximate Model of Multistage Automatic Transfer Lines with Possible Scrapping Of Workpieces

We consider multistage automatic transfer lines with unreliable stages, finite interstage buffer storages, and possible scrapping of workpieces. It is assumed that the first stage never idles and the last stage never becomes blocked. Assuming that uptimes and downtimes of a stage are geometrically distributed, an approximate model is developed to compute different performance measures of the transfer line. The results obtained through the approximate model are compared to the exact results for three-stage transfer lines and to simulation results for longer transfer lines. It is observed that the approximate results are good in almost all cases considered.     

Signature analysis and defect detection in layered manufacturing of ceramic sensors and actuators

This paper presents the concept of a process signature for the use of online signature analysis and defect detection in the layered manufacturing (LM) of ceramic sensors and actuators. To achieve the high quality of parts built by the fused deposition of ceramics (FDC), an online process-monitoring system is implemented to detect the processing defects. Using a process signature extracted from the image of a layer captured by the monitoring system, an ideal image is created that is then compared to the original image to detect and identify the defects. Some results of signature analysis and defect detection for single-material and multi-material parts are also presented.Received: 22 July 1999, Accepted: 21 October 2001, Published online: 29 October 2003 Correspondence to: Mohsen A. JafariThis work was supported by the Office of Naval Research under grant # N-0014-96-1-1175. Ref. US Patent # S-5738817, April 14, 1998.     

Thermal modeling in cylindrical coordinates using effective conductivity

Predictive thermometry, utilizing minimally invasive sampling techniques, is an essential ingredient in the development of hyperthermia treatment planning capabilities. The authors demonstrate a powerful, but simple approach toward predicting temperature distributions in tissues, based on analytic solution, using in cylindrical symmetry, of the heat diffusion equation. Conduction and localized perfusion effects are combined as an effective conductivity term, readily measurable, and parametrized in a general exponential form. The proposed approach allows a first-order approximation to modeling three typical situations: hypoxic or necrotic tumor core with homogeneously perfused periphery; highly perfused periphery (in rapidly growing tumors); or perfused central cover with a less well-supplied periphery (such as for some invasive tumors). The utility and strength of this approach is that it provides a rapid, accurate model of directly observing the technical quality to be expected for different heating methods, making it possible to optimally configure source distributions in a treatment planning setting.     

Effect of Adding Transition Metals to Copper on the Dehydrogenation Reaction of Ethanol

The present work aims to investigate the effect adding Ag, Co, Ni, Cd and Pt to copper on ethanol dehydrogenation. The catalysts synthesized by deposition–precipitation method were characterized using various physicochemical methods such as N₂ adsorption–desorption, TPR, SEM–EDX, XRD, XPS and TGA–DSC-MS. Catalytic evaluation results revealed that the predominant product of the reaction was acetaldehyde. Monometallic copper or mixed with Cd, Ag or Co show good catalytic performances. Adding nickel to copper improves the process conversion but reduces acetaldehyde selectivity, giving rise to methane in produced hydrogen. Pt-Cu/SiO₂ catalyst guides the reaction towards diethyl ether. Time on stream tests performed during 12 h at 260 °C, showed that adding Cd to Cu enhances its stability by over 30% of conversion, this is explained by the reduction of copper crystallites sintering, which makes Cd-Cu/SiO₂ a promising catalyst for the production of acetaldehyde by ethanol dehydrogenation.

Graphic Abstract

     

Compatibilizing Effects on the Phase Morphology and Thermal Properties of Polymer Blends Based on PTT and m-LLDPE

Summary Morphology and thermal characteristics of poly (trimethylene terephthalate) (PTT)/ metallocene linear low-density polyethylene (m-LLDPE) blends with different amounts of a terpolymer based on glycidyl methacrylate (GMA), employed as a possible compatibilizer, were systematically examined. DMTA results show two distinct peaks for all neat blends associated with each phase. Melt crystallization degree of both phases in all the blends was observed to be reduced compared to pure components, except for that of PTT-rich phase in those blends with PTT as the matrix which slightly increases. Addition of the terpolymer to the system is found to effectively reduce the droplet size of the dispersed phase and increase phase adhesion. Also it increases the crystallinity of PTT in the system with PTT as the matrix. The influence of the compatibilizer is ascribed to the chemical interaction of PTT functional end groups with GMA functionalities. The efficiency of the terpolymer as a compatibilizer beyond 5 wt% content decreases which can be ascribed to the interface saturation and formation of micelles in the bulk phases.     

A localization algorithm for large scale mobile wireless sensor networks: a learning approach

Localization is a crucial problem in wireless sensor networks and most of the localization algorithms given in the literature are non-adaptive and designed for fixed sensor networks. In this paper, we propose a learning based localization algorithm for mobile wireless sensor networks. By this technique, mobility in the network will be discovered by two crucial methods in the beacons: position and distance checks methods. These two methods help to have accurate localization and constrain communication just when it is necessary. The proposed method localizes the nodes based on connectivity information (hop count), which doesn’t need extra hardware and is cost efficient. The experimental results show that the proposed algorithm is scalable with a small set of beacons in large scale network with a high density of nodes. The given algorithm is fast and free from a pre-deployment requirement. The simulation results show the high performance of the proposed algorithm.     

A trust-based service suggestion system using human plausible reasoning

Nowadays, there is a growing need to manage trust in open systems as they may contain untrustworthy service providers. Agent Trust Management (ATM) tries to address the problem of finding a set of the most trusted agents in multi agent systems. This paper presents ScubAA, a novel generic ATM framework based on the theory of Human Plausible Reasoning (HPR). For each user’s request, ScubAA determines a ranked list of the most trusted service agents, within the context of the request, and forwards the request to those trusted services only. ScubAA determines an agent’s degree of trust in terms of a single personalized value derived from several types of evidences such as user’s feedback, history of user’s interactions, context of the submitted request, references from third party users as well as from third party service agents, and structure of the society of agents. ScubAA is able to utilize more trust evidences towards a more accurate value of trust. We also propose a function to figure out how similar two users are in a given context. We apply the proposed HPR-based ATM framework to the domain of Web search. The resulting ATM system recommends to the user a list of the most trusted search engines ranked according to the retrieval precision of documents returned in response to the user’s query as well as the degree of trust of the search engines have gained by interacting with other related users within the context of the query. In addition, we conduct a statistical analysis of ScubAA based on ANOVA and by using a data set of forty queries in different domains. This analysis clearly reveals that ScubAA is able to successfully assess the trustworthiness of service agents.     

Activating pulp toward acetylation by chemical or mechanical means

Activation of pulps during acetylation, by prior mechanical or chemical treatment, has been investigated. The effect of degree of beating on the acetylation rate of wood and bagasse pulps has been studied. It is found that the acetylation rate of pulps increases when the degree of beating of pulps is increased to a definite degree, after which it slows down. The maximum reactivity of bagasse pulp is obtained at 50°SR, while that of wood pulp is observed at 30°SR. The effect of grafting of acrylonitrile onto bagasse and wood pulps on their reactivity during acetylation has been also studied. The results indicate that grafting of acrylonitrile onto pulps has a favorable effect on their acetylation rate. This is dependent on the degree of grafting as well as the origin of pulp fibers. The most suitable method of activation during acetylation reaction is dependent on the origin of the pulp. The reactivity of bagasse pulp during acetylation is influenced more by beating of pulp, prior to the reaction, than by the grafting of acrylonitrile onto pulp. On the other hand, the acetylation reaction of wood pulp is activated by grafting rather than by beating. Also the effect of the activation process, mechanical or chemical, on the strength properties of the paper sheets produced from acetylated pulps has been investigated. Chemical activation of wood pulp prior to acetylation resulted in pulp with slightly higher strength properties than that activated by mechanical means. But, in the case of bagasse pulp, mechanical activation resulted in a pulp with strength superior to that produced by chemical activation.     

CFD simulation and evaluation of controllable parameters effect on thermomagnetic convection in ferrofluids using Taguchi technique

In the present attempt a CFD simulation capable of coupling behaviors from the nano-scale through the full-scale system in which a ferrofluid containing magnetite particles suspended in kerosene carrier liquid is presented. The main objective of the work was to simulate the thermodiffusion and also to evaluate the factors influence on this phenomenon in a cylindrical geometry. In simulations a two-phase mixture model was used to predict the behavior of the system. To optimize the thermomagnetic effect, different parameters including temperature difference across the layer, initial magnetic phase concentration, aspect ratio of the geometry, magnetic field magnitude and diameter of magnetic particles were examined using L₁₆ orthogonal array of Taguchi at four levels. Analysis of the simulation data indicate that the magnetic Soret effect can even be higher than the conventional one and its strength depends on the magnetic field strength, confirmed experimentally by Völker and Odenbach [Völker T, Odenbach S. Thermodiffusion in magnetic fluids. J Magn Magn Mater 2005;289:289-91]. The statistic evaluation shows that temperature and initial concentration of magnetic phase have the maximum and minimum contribution on the thermodiffusion, respectively. According to the results temperature difference 80 K, initial concentration of magnetic phase 0.08, aspect ratio 0.2, magnetic field strength 100 kA/m and magnetic particles diameter 100 nm were obtained as optimum conditions in the presence of natural convection. The same result was gained in the lack of natural convection except the magnetic field strength was 160 kA/m. Finally, based on the primary results, a verification test was also performed to confirm the validity of the used statistical method.