A study on swelling behavior of poly(p‐chloro styrene) networks in some aromatic hydrocarbons and linear poly(p‐chloro styrene) solutions

Crosslinked networks (NPPCS) and linear polymers (LPPCS) of poly (p‐chloro styrene) were synthesized by free‐radical polymerization of p‐chloro styrene. NPPCS networks were swollen in four different molecular weights of LPPCS solutions in toluene at three different concentrations. The equilibrium swelling results were evaluated by means of Flory‐Rehner theory to obtain network–linear polymer interaction parameter, χ′₂₃ between NPPCS and LPPCS. It was concluded that the parameter χ′₂₃ decreased with molecular weight but increased with concentration of LPPCS in outer solution. The solvent independent interaction parameter between NPPCS and PPCS was estimated as 0.7 by extrapolation of the values of χ′₂₃ to zero value of the fraction ratio of solvent to linear polymer, ν₁/ν₃ inside the network. As well as, the binary interaction parameters, χ₁₂ of NPPCS with benzene, ethyl benzene, n‐propyl benzene and isopropyl benzene were obtained by means of Flory‐Rehner theory at temperatures between 25 and 55°C. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Highly-Directional,Highly-Efficient Solution-Processed Light-Emitting Diodes of All-Face-Down Oriented Colloidal Quantum Well Self-Assembly

Semiconductor colloidal quantum wells (CQWs) provide anisotropic emission behavior originating from their anisotropic optical transition dipole moments (TDMs). Here, solution-processed colloidal quantum well light-emitting diodes (CQW-LEDs) of a single all-face-down oriented self-assembled monolayer (SAM) film of CQWs that collectively enable a supreme level of IP TDMs at 92% in the ensemble emission are shown. This significantly enhances the outcoupling efficiency from 22% (of standard randomly-oriented emitters) to 34% (of face-down oriented emitters) in the LED. As a result, the external quantum efficiency reaches a record high level of 18.1% for the solution-processed type of CQW-LEDs, putting their efficiency performance on par with the hybrid organic-inorganic evaporation-based CQW-LEDs and all other best solution-processed LEDs. This SAM-CQW-LED architecture allows for a high maximum brightness of 19,800 cd m⁻² with a long operational lifetime of 247 h at 100 cd m⁻² as well as a stable saturated deep-red emission (651 nm) with a low turn-on voltage of 1.7 eV at a current density of 1 mA cm⁻² and a high J₉₀ of 99.58 mA cm⁻². These findings indicate the effectiveness of oriented self-assembly of CQWs as an electrically-driven emissive layer in improving outcoupling and external quantum efficiencies in the CQW-LEDs.     

An Efficient Internet Traffic Classification System Using Deep Learning for IoT

Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, Quality-of-Service provisioning, performance monitoring, resource provisioning, and traffic engineering require traffic classification. Due to the ineffectiveness of traditional classification schemes, such as port-based and payload-based methods, researchers proposed machine learning-based traffic classification systems based on shallow neural networks. Furthermore, machine learning-based models incline to misclassify internet traffic due to improper feature selection. In this research, an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet traffic. To examine the performance of the proposed technique, Moore-dataset is used for training the classifier. The proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network (DNN). In particular, the maximum entropy classifier is used to classify the internet traffic. The experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification, i.e., 99.23%. Furthermore, the proposed algorithm achieved the highest accuracy compared to the support vector machine (SVM) based classification technique and k-nearest neighbours (KNNs) based classification technique.     

Facile synthesis of novel 6-methyl-5-phenyl-2-sulfido-1,2,3,5-tetrahydro-4H[1,2] oxazolo[4′,5′:5,6]pyrano[2,3-d][1,3,2]diazaphosphinines

A number of 6-methyl-5-phenyl-2-sulfido-1,2,3,5-tetrahydro-4H[1,2]oxazolo[4′,5′: 5,6]pyrano[2,3-d][1,3,2]diazaphosphinines 4–11 were synthesized via an interaction of tetraphosphorus decasulfide and Lawesson’s reagent under different conditions with 6-amino-3-methyl-4-phenyl-4H-pyrano[3,2-d][1,2]oxazole-5-carbonitrile (3). The reaction mechanisms for these products were discussed. Structures of the newly synthesized products were established on the basis of elemental analysis and spectral data.     

Synthesis and electrochemical capacitance of binderless nanocomposite electrodes formed by dispersion of carbon nanotubes and carbon aerogels

Novel nanocomposite carbon aerogel (CAG)-multi-walled carbon nanotubes (MWNT) materials have been synthesized and studied in 5 M KOH for electrochemical capacitor applications. The amount of MWNT in the nanocomposite was varied from 3 to 10 wt%. High specific surface areas ranging between 670 and 710 m² g⁻¹ were obtained as measured by nitrogen gas adsorption method, whereas the average pore diameter ranged between 1 and 4 nm.     

Classification of Honey According to Geographical and Botanical Origins and Detection of Its Adulteration Using Voltammetric Electronic Tongue

Main possible honey fraud is the addition of various sugar syrups. But, there are also other types of fraud, such as deception on the geographical and/or botanical origin product. Providing a product of the hive with full authenticity is therefore crucial for the preservation of beekeeping. In this pursuit, voltammetric electronic tongue (VE-tongue) was employed to classify honey samples from different geographical and botanical origins. Furthermore, VE-tongue was used to detect adulterants such as glucose syrup (GS) and saccharose syrup (SS) in honey. The data obtained were analyzed by three-pattern recognition techniques: principal component analysis (PCA), support vector machines (SVMs), and hierarchical cluster analysis (HCA). These methods enabled the classification of 18 honeys of different geographical origins and 7 honeys of different botanical origins. Excellent results were obtained also in the detection of adulterated honey. Therefore, this simple method based on VE-tongue could be useful in the honey packaging and commercialization industry.     

Optimizing bag-of-tasks scheduling on cloud data centers using hybrid swarm-intelligence meta-heuristic

The Journal of Supercomputing - Usually, a large number of concurrent bag-of-tasks (BoTs) application execution requests are submitted to cloud data centers (CDCs), which needs to be optimally...     

A comparative study of the adsorption and desorption of o-xylene onto bentonite clay and alumina

In this paper, adsorptive performance of natural clay of bentonite type has been investigated as a potential VOC adsorbent on the basis its promising physical-chemical and morphological properties which were compared to commercial gamma-Al(2)O(3) solid. The vapour-solid adsorption isotherms of xylene were measured at different temperatures ranging from 300 to 373 K using dynamical method and the obtained data confronted to classical models such as Langmuir and Freundlich. On the other hand, the solids physico-chemical characteristics and adsorptive performances were correlated to some cost aspects because of their importance for design and engineering of adsorption plant. The results shows the interest of a local clay natural of bentonite type for treatment of VOCs emitted in working places regarding its performances and lower cost.     

Thermal conductivity and thermal boundary resistance of nanostructures

   

We present a fabrication process of low-cost superlattices and simulations related with the heat dissipation on them. The influence of the interfacial roughness on the thermal conductivity of semiconductor/semiconductor superlattices was studied by equilibrium and non-equilibrium molecular dynamics and on the Kapitza resistance of superlattice's interfaces by equilibrium molecular dynamics. The non-equilibrium method was the tool used for the prediction of the Kapitza resistance for a binary semiconductor/metal system. Physical explanations are provided for rationalizing the simulation results.     

Enhanced Sintering of TiNi Shape Memory Foams under Mg Vapor Atmosphere

TiNi alloy foams are promising candidates for biomaterials to be used as artificial orthopedic implant materials for bone replacement applications in biomedical sector. However, certain problems exist in their processing routes, such as formation of unwanted secondary intermetallic phases leading to brittleness and deterioration of shape memory and superelasticity characteristics; and the contamination during processing resulting in oxides and carbonitrides which affect mechanical properties negatively. Moreover, the eutectic reaction present in Ti-Ni binary system at 1391?K (1118?°C) prevents employment of higher sintering temperatures (and higher mechanical properties) even when equiatomic prealloyed powders are used because of Ni enrichment of TiNi matrix as a result of oxidation. It is essential to prevent oxidation of TiNi powders during processing for high-temperature (>1391?K i.e., 1118?°C) sintering practices. In the current study, magnesium powders were used as space holder material to produce TiNi foams with the porosities in the range of 40 to 65?pct. It has been found that magnesium prevents secondary phase formation and contamination. It also prevents liquid phase formation while enabling employment of higher sintering temperatures by two-step sintering processing: holding the sample at 1373?K (1100?°C) for 30?minutes, and subsequently sintering at temperatures higher than the eutectic temperature, 1391?K (1118?°C). By this procedure, magnesium may allow sintering up to temperatures close to the melting point of TiNi. TiNi foams produced with porosities in the range of 40 to 55?pct were found to be acceptable as implant materials in the light of their favorable mechanical properties.