Towards ultrathick battery electrodes: aligned carbon nanotube-enabled architecture

Vapor deposition techniques were utilized to synthesize very thick (～1 mm) Li-ion battery anodes consisting of vertically aligned carbon nanotubes coated with silicon and carbon. The produced anode demonstrated ultrahigh thermal (>400 W·m(-1) ·K(-1)) and high electrical (>20 S·m(-1)) conductivities, high cycle stability, and high average capacity (>3000 mAh·g(Si) (-1)). The processes utilized allow for the conformal deposition of other materials, thus making it a promising architecture for the development of Li-ion anodes and cathodes with greatly enhanced electrical and thermal conductivities.     

Mechanical properties of ferrochromium slag in granular layers of flexible pavements

Ferrochromium slag is a waste material obtained from the manufacture of ferrochromium (FeCr). This article reports the results of experiments, aiming to identify the properties of ferrochromium slag when it is used as an artificial aggregate for preparation of granular layers of flexible pavements. The experimental program consisted of two stages: (1) study of the physical and chemical properties of slag; (2) study of the mechanical properties of specimens made with ferrochromium slag and limestone as aggregate. Laboratory prepared cylindrical specimens were tested in repeated load triaxial (RLT) test apparatus, developed at Süleyman Demirel University, Turkey. In addition, particle size analysis, abrasion test, frost resistance, compaction test, California Bearing Ratio (CBR) test and leaching test were performed on the materials prior to RLT testing. The results indicate that the physical and mechanical properties of air-cooled ferrochromium slag are as good or better than those of natural aggregates. Therefore, FeCr slag and SiFeCr slag have potential to be used as a pavement base layer material in applications where crushed limestone aggregate materials are traditionally used.     

Antimicrobial effect of PEG–PLA on food-spoilage microorganisms

Food Science and Biotechnology - Polyethylene glycol (PEG) and polyethylene glycol–polylactic acid (PEG–PLA) have an organic structure and no negative effect on human health. The...     

Prediction of Damage Factor in end Milling of Glass Fibre Reinforced Plastic Composites Using Artificial Neural Network

Glass fibre reinforced plastic (GFRP) composites are an economic alternative to engineering materials because of their superior properties. Some damages on the surface occur due to their complex cutting mechanics in cutting process. Minimisation of the damages is fairly important in terms of product quality. In this study, a GFRP composite material was milled to experimentally minimise the damages on the machined surfaces, using two, three and four flute end mills at different combinations of cutting parameters. Experimental results showed that the damage factor increased with increasing cutting speed and feed rate, on the other hand, it was found that the damage factor decreased with increasing depth of cut and number of the flutes. In addition, analysis of variance (ANOVA) results clearly revealed that the feed rate was the most influential parameter affecting the damage factor in end milling of GFRP composites. Also, in present study, Artificial Neural Network (ANN) models with five learning algorithms were used in predicting the damage factor to reduce number of expensive and time-consuming experiments. The highest performance was obtained by 4-10-1 network structure with LM learning algorithm. ANN was notably successful in predicting the damage factor due to higher R² and lower RMSE and MEP.     

A new approach for rebalancing of U-lines with stochastic task times using ant colony optimisation algorithm

In real world, line balancing involves existing lines in existing factories and the line typically needs to be rebalanced rather than balanced. Rebalancing of a U-line can be defined as a changeover process from its initial configuration to a new configuration for a while due to the reasons such as demand variations, changes in product design and changes in task times, etc. This study defines U-line rebalancing problem with stochastic task times and proposes a solution procedure based on ant colony optimisation. The objective of the proposed algorithm is to minimise total cost of rebalancing which is the sum of task transposition costs, workstation opening/closing costs and operating costs of workstations for a particular planning horizon. A comprehensive experiment is conducted to generate problem instances and to compare rebalancing costs of U-lines by means of several factors. A total of 6600 rebalancing solutions are obtained and several comparisons are performed.     

Finite‐volume stress analysis in multi‐material linear elastic body

Correct calculation of stresses at the interface of bonded or otherwise joined materials plays a significant role in many applications. It is therefore important that traction at the material interface is calculated as accurately as possible. This paper describes procedures that can be employed to achieve this goal by using centre‐based finite‐volume method. Total traction at the interface is calculated by decomposing it into normal and tangential components, both being calculated at each side of the interface, and applying the continuity assumption. The way in which the traction approximation is achieved depends on calculation of tangential gradient of displacement at the interface. To this end, three different methods are proposed and validated against problems with known solutions. It was shown that all methods can be successfully used to simulate problems with multi‐material domains, with the procedure based on finite area method being most accurate. Copyright © 2012 John Wiley & Sons, Ltd.     

A multivariate Poisson-lognormal regression model for prediction of crash counts by severity, using Bayesian methods

Numerous efforts have been devoted to investigating crash occurrence as related to roadway design features, environmental factors and traffic conditions. However, most of the research has relied on univariate count models; that is, traffic crash counts at different levels of severity are estimated separately, which may neglect shared information in unobserved error terms, reduce efficiency in parameter estimates, and lead to potential biases in sample databases. This paper offers a multivariate Poisson-lognormal (MVPLN) specification that simultaneously models crash counts by injury severity. The MVPLN specification allows for a more general correlation structure as well as overdispersion. This approach addresses several questions that are difficult to answer when estimating crash counts separately. Thanks to recent advances in crash modeling and Bayesian statistics, parameter estimation is done within the Bayesian paradigm, using a Gibbs Sampler and the Metropolis–Hastings (M–H) algorithms for crashes on Washington State rural two-lane highways. Estimation results from the MVPLN approach show statistically significant correlations between crash counts at different levels of injury severity. The non-zero diagonal elements suggest overdispersion in crash counts at all levels of severity. The results lend themselves to several recommendations for highway safety treatments and design policies. For example, wide lanes and shoulders are key for reducing crash frequencies, as are longer vertical curves.     

Impact of frying on key fatty acid ratios of canola oil

The study was carried out to investigate the changes in saturated (SFA), monoene (MUFA), trans (TFA), and polyunsaturated (PUFA) fatty acids and the key fatty acid ratios (SFA/UFA, cis PUFA/SFA, C18:2/C16:0 and C18:3/C16:0) during potato chips frying in canola oil using single bounce attenuated total reflectance FTIR (SB‐ATR‐FTIR) spectroscopy. The data obtained from GC‐FID were used as reference. The calibration of main fat groups and their key fatty acid ratios were developed by partial least square (PLS) regression coefficients using 4000 to 650 cm^?1 spectral range. FTIR PLS regression for the predicted SFA, MUFA, TFA, and PUFA were found 0.999, 0.998, 0.998, and 0.999, respectively, whereas for SFA/UFA, cis PUFA/SFA, C18:2/C16:0 and C18:3/C16:0 the regression coefficients were 0.991, 0.997, 0.996, and 0.994, respectively. We conclude that FTIR‐PLS could be used for rapid and accurate assessment of changes in the main fat groups and their key fatty acid ratios ratio during the frying process. Practical applications: FTIR‐ATR method is very simple, rapid, and environmentally friendly. No sample preparation is required and one drop of oil is enough for FTIR analysis. The proposed method could be applied for quick determination of key fatty acid ratios in the food processing industry.     

Effect of bark beetle infestation on secondary organic aerosol precursor emissions

Bark beetles are a potentially destructive force in forest ecosystems; however, it is not known how insect attacks affect the atmosphere. The emissions of volatile organic compounds (VOCs) were sampled i.) from bark beetle infested and healthy lodgepole pine (Pinus contorta var. latifolia) trees and ii.) from sites with and without active mountain pine beetle infestation. The emissions from the trunk and the canopy were collected via sorbent traps. After collection, the sorbent traps were extracted with hexane, and the extracts were separated and detected using gas chromatography/mass spectroscopy. Canister samples were also collected and analyzed by a multicolumn gas chromatographic system. The samples from bark beetle infested lodgepole pine trees suggest a 5- to 20-fold enhancement in total VOCs emissions. Furthermore, increases in the β-phellandrene emissions correlated with bark beetle infestation. A shift in the type and the quantity of VOC emissions can be used to identify bark beetle infestation but, more importantly, can lead to increases in secondary organic aerosol from these forests as potent SOA precursors are produced.