Effect of amphiphilic compatibilizers on the filler dispersion and properties of polyethylene—thermally reduced graphene nanocomposites

Compatibilizers of different chemical structures and specifications were used to enhance the filler exfoliation in nanocomposites of polyethylene and thermally reduced graphene prepared by melt mixing route. The mechanical performance of the compatibilized nanocomposites was observed to be better than PE/G nanocomposites due to enhanced extent of filler exfoliation and distribution. Highest increase of 45% in tensile modulus and 13% in peak stress was observed in the composites. Overall, from the mechanical, rheological, thermal, and calorimetric properties, the compatibilizers with best performance were ethylene acrylic acid (EAA) copolymer and chlorinated polyethylene (CPE25). Furthermore, the extent of filler exfoliation was observed to increase with increasing EAA content thus confirming positive interactions between EAA and thermally reduced graphene, though no specific chemical interactions could be detected. The composite properties were observed to reach maximum around 7.5 wt % EAA content, followed by reduced performance due to extensive matrix plasticization. The observed behaviors were a result of interplay of opposing factors like filler exfoliation due to compatibilizer addition and matrix plasticization due to its lower molecular weight, thus the observed optimum comaptibilizer amount was specific to the compatibilizer. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42484.     

Effect of Li<Subscript>2</Subscript>O on the Refractive Index and Optical Band Gap of Cadmium Phosphate Glasses

A series of lithium cadmium phosphate glasses having composition (mol %) xLi₂O-(50 ? x)CdO-50P₂O₅ were prepared in a platinum crucible by the melt quenching technique. The quantity x varies in the range 0–40. The mass density and refractive index of these glasses were found in the ranges 3.95–2.89 g/cm₃ and 1.55–1.40, respectively. The optical absorbance studies were also carried out on these glasses to measure their energy gaps. The absorption spectra of these glasses were recorded in the UV-visible range. No sharp edges were found in the optical spectra, which verifies the amorphous nature of these glasses. The optical band gap energies for these glasses were found to be in the range 2.58–3.5 eV. It was observed that the density, the refractive index, and the optical band gap energy decrease with increasing amount of lithium oxide. The band tailing, worked out from the Urbach plots, shows an increase with increasing Li₂O content and lies in the range 0.47–0.78 eV. The absorption coefficient is observed to show an exponential dependence on the photon energy.     

Desorption kinetics of trichloroethylene and perchloroethylene from aged dense nonaqueous phase liquid-contaminated soil

Batch experiments were conducted to investigate the desorption kinetics of a contaminated soil collected from a field site at Hill Air Force Base (AFB), Utah. The site has been contaminated with many dense nonaqueous phase liquids (DNAPLs), primarily trichloroethylene (TCE) and perchloroethylene (PCE), for more than 60 years. Similar desorptive behaviour of both TCE and PCE was observed: a stage of fast release of the contaminant at the start followed by a very slow stage. Moreover, it is suggested that not all the contaminant in the solid phase may be released to the aqueous phase, apparently due to the age factor. Local variations were observed in the effective diffusivity and other sorption-related parameters across the site due to aquifer heterogeneity. Experimental results were then simulated using a numerical code based on the intraparticle diffusion model. Good agreement was found between both results.     

Architecture and Physical Implementation of a Third Generation 65 nm, 16 Core, 32 Thread Chip-Multithreading SPARC Processor

This third-generation Chip-Multithreading (CMT) SPARC processor consists of 16 cores with shared memory architecture and supports a total of 32 main threads plus 32 scout threads. It is targeted for high-performance servers, and is optimized for both single- and multi-threaded applications. The 396 mm² chip is fabricated in an 11 metal layer 65-nm CMOS process and operates at a nominal frequency of 2.3 GHz, consuming a maximum power of 250 W at 1.2 V. This paper provides an overview of the architectural highlights and describes the physical implementation challenges and solutions including circuit innovations in memory arrays, register files, and floating-point hardware that boost the performance and circuit robustness with low area overhead.     

The 12<Superscript>th</Superscript> World Conference on Titanium presents research and applications of “wonder metal”

The International Conference on Titanium was begun in 1968 to assess the national significance attached to the development of titanium in relation to the technical needs of the participating countries. The conference, held every four years, attracts strong international participation. This article reviews the 12^th World Conference on Titanium, hosted by the Nonferrous Society of China and held in Beijing, China, 19–24 June 2011.     

Classifying Construction Contractors Using Unsupervised-Learning Neural Networks

Contractor prequalification involves the screening of contractors by a project owner to determine their competence to complete the project on time, within budget, and to expected quality standards. The process of prequalification involves a large number of contractors, each being represented by many attributes. A neural network model was applied to aid in the prequalification process by classifying contractors into groups based on similarity in performance using the financial ratios of liquidity, activity, profitability, and leverage. Contractors are represented in this model by patterns in four-dimensional space. Patterns of similar performance tend to form clusters intercepting regions of low pattern density in between. A neuron with weights is used as a classifier to set a decision boundary between clusters. The method basically iterates the neuron weights to move the decision boundary to a place of low pattern density. Then, the statistical hypothesis testing of the mean difference of two independent samples was used to validate the classification of the parent class to the two child classes considering the four ratios separately. The method was used hierarchically to classify a group of 245 contractors into classes of small numbers. Finally, the inferred procedure of classification proves that the neural network model classified the four-dimension pattern representing contractors efficiently.