Conversion of waste polystyrene through catalytic degradation into valuable products

Waste expanded polystyrene (EPS) represents a source of valuable chemical products like styrene and other aromatics. The catalytic degradation was carried out in a batch reactor with a mixture of polystyrene (PS) and catalyst at 450 °C for 30 min in case of Mg and at 400 °C for 2 h both for MgO and MgCO₃ catalysts. At optimum degradation conditions, EPS was degraded into 82.20±3.80 wt%, 91.60±0.20 wt% and 81.80±0.53 wt% liquid with Mg, MgO and MgCO₃ catalysts, respectively. The liquid products obtained were separated into different fractions by fractional distillation. The liquid fractions obtained with three catalysts were compared, and characterized using GC-MS. Maximum conversion of EPS into styrene monomer (66.6 wt%) was achieved with Mg catalyst, and an increase in selectivity of compounds was also observed. The major fraction at 145 °C showed the properties of styrene monomer. The results showed that among the catalysts used, Mg was found to be the most effective catalyst for selective conversion into styrene monomer as value added product.     

Metabolic profile biomarkers of metal contamination in a sentinel terrestrial species are applicable across multiple sites

In this study, we addressed the question of whether an omic approach could genuinely be useful for biomarker profile analysis across different field sites with different physicochemical characteristics. We collected earthworms (Lumbricus rubellus) from seven sites with very different levels of metal contamination and prevailing soil type and analyzed tissue extracts by 1H nuclear magnetic resonance spectroscopy. Pattern recognition analysis of the data showed that both site- and contaminant-specific effects on the metabolic profiles could be discerned. Zinc was identified as the probable major contaminant causing a metabolic change in the earthworms. Individual sites could be resolved on the basis of NMR spectral profiles by principal component analysis; these site differences may also have been caused by additional abiotic factors such as soil pH. Despite an inevitable degree of confounding between site and contaminant concentrations, it was possible to identify metabolites which were correlated with zinc across all different sites. This study therefore acts as a proof of principle for the use of NMR-based metabolic profiling as a diagnostic tool for ecotoxicological research in polluted field soils.     

Determination of Glyphosate and Its Metabolite AMPA (Aminomethylphosphonic Acid) in Cereals After Derivatization by Isotope Dilution and UPLC-MS/MS”

A straightforward analytical method has been developed for the determination of glyphosate and aminomethylphosphonic acid (AMPA), its major metabolite in cereals. This method entails a rapid extraction and derivatization with 9-fluorenylmethyl chloroformate followed by separation with a conventional reversed-phase rapid chromatography used in daily routine analysis and detection by electrospray ionization tandem mass spectrometry. To overcome matrix effects and compensate for any analyte losses during sample treatment, an isotopic dilution approach was used. Since 2010, the monitoring of cereals for the widely used herbicide glyphosate is obligatory to all European Union (EU)-member states, laid down in Commission Regulation (EC) No. 1213/2008. Hence, there is definitively a need for a reliable and easy-to-handle analytical method for monitoring of this compound. The proposed method can be run without having to make time-consuming changes on the equipment used for daily routine analysis. The analytical performance of the method was evaluated according to SANCO/10684/2009 criteria and demonstrated that this method is rugged and cost-effective, therefore suitable for monitoring purposes as well as legislative enforcements within the EU. The apparent recoveries of both analytes were between 97% and 113% with relative standard deviations less than 20%. The limits of quantification of glyphosate and AMPA were 0.02 mg/kg in cereal matrices. Finally, the accuracy of the method was assessed by analyzing a proficiency test material which was available from a previous round (EUPT-C4).     

The experience curve,option value,and the energy paradox

This paper develops a model to explain the ‘energy paradox,’ the inclination of households and firms to require very high internal rates of return in order to make energy-saving investments. The model abstracts from many features of such investments to focus on their irreversibility, the uncertainty of their future payoff streams, and the investor's anticipation of future technological advance. In this setting, the decision to invest in energy-saving technology can be delayed, providing option value. In addition, delay allows the potential investor to cash in on future experience-curve effects: With the passage of time, firms gain practical knowledge in producing and installing the energy-saving technology, enabling them to reduce the technology's up-front cost per unit of energy saved. We incorporate these fundamentals into a stochastic model where the investment's discounted benefits follow geometric Brownian motion. To demonstrate the model's capabilities, we generate simulation results for photovoltaic systems that highlight the experience-curve effect as a fundamental reason why households and firms delay making energy-saving investments until internal rates of return exceed values of 50% and higher, consistent with observations in the economics literature. We also explore altruistic motivations for energy conservation and the model's implications for both “additionality” and the design of energy-conservation policy.     

Mumford-Shah model for one-to-one edge matching.

This paper presents a new algorithm based on the Mumford-Shah model for simultaneously detecting the edge features of two images and jointly estimating a consistent set of transformations to match them. Compared to the current asymmetric methods in the literature, this fully symmetric method allows one to determine one-to-one correspondences between the edge features of two images. The entire variational model is realized in a multiscale framework of the finite element approximation. The optimization process is guided by an estimation minimization-type algorithm and an adaptive generalized gradient flow to guarantee a fast and smooth relaxation. The algorithm is tested on T1 and T2 magnetic resonance image data to study the parameter setting. We also present promising results of four applications of the proposed algorithm: interobject monomodal registration, retinal image registration, matching digital photographs of neurosurgery with its volume data, and motion estimation for frame interpolation.     

Interactions of Fibroblasts with Different Morphologies Made of an Engineered Spider Silk Protein

Spider silk has been investigated for decades due to the intriguing mechanical and also biomedical properties of the silk fibers. Previously, it has been shown that recombinant silk proteins can also be processed into other morphologies. Here, we characterized scaffolds made of the recombinant spider silk protein eADF4(C16) concerning their surface interactions with fibroblasts. Studies of BALB/3T3 cells on hydrogels and films made of eADF4(C16) showed low cell adhesion without observable duplication. Electro‐spun non‐woven scaffolds made of eADF4(C16), however, enabled both their adhesion and proliferation. Since eADF4(C16) lacks specific motifs for cell attachment, fibroblasts cannot generate focal adhesions with the material's surface, and, therefore, other cell–interface interactions such as topographical anchorage or cell attachment mediated by adhesion of extracellular matrix proteins are discussed in this paper. On non‐woven meshes protrusion of filopodia and/or lamellipodia between individual fibers increase the surface contact area, which depends on the diameter of the fibers of the non‐woven meshes. In contrast, at flat (film) or microstructured surfaces (hydrogels) such interactions seem to be precluded.     

The BER analysis of OFDMA and SC‐FDMA under pilot‐assisted channel estimation and pilot jamming in rayleigh slow‐fading channel

In this paper, the authors derived the analytical bit error rate expressions for orthogonal frequency division multiple access and single‐carrier frequency‐division multiple access (SC‐FDMA) in Rayleigh slow‐fading channel for binary phase‐shift keying/quadrature phase‐shift keying/16‐quadrature amplitude modulations under pilot jamming and pilot symbol‐assisted channel estimation. Beginning with the bit error rate analysis from the general case of pilot symbol‐assisted channel estimation technique in Rayleigh slow‐fading channel, the expressions are first modified for different modulations and then further customized to account for the Zero‐Forcing equalization in frequency or time direction with application respectively to orthogonal frequency division multiple access or SC‐FDMA without and with pilot jamming. Piecewise‐linear interpolation is used for its simplicity. The simulation results match perfectly with the theoretical predictions except for some discrepancies with SC‐FDMA, which imply that the generalized equations developed here have to be further modified to account for system‐specific features like discrete Fourier transform precoding for SC‐FDMA. Copyright © 2016 John Wiley & Sons, Ltd.     

Material requirements for the adoption of unconventional silicon crystal and wafer growth techniques for high‐efficiency solar cells

Silicon wafers comprise approximately 40% of crystalline silicon module cost and represent an area of great technological innovation potential. Paradoxically, unconventional wafer‐growth techniques have thus far failed to displace multicrystalline and Czochralski silicon, despite four decades of innovation. One of the shortcomings of most unconventional materials has been a persistent carrier lifetime deficit in comparison to established wafer technologies, which limits the device efficiency potential. In this perspective article, we review a defect‐management framework that has proven successful in enabling millisecond lifetimes in kerfless and cast materials. Control of dislocations and slowly diffusing metal point defects during growth, coupled to effective control of fast‐diffusing species during cell processing, is critical to enable high cell efficiencies. To accelerate the pace of novel wafer development, we discuss approaches to rapidly evaluate the device efficiency potential of unconventional wafers from injection‐dependent lifetime measurements. Copyright © 2015 John Wiley & Sons, Ltd.