Radiation-induced modification of dielectric relaxation spectra of polyolefins: polyethylenes vs. polypropylene

The molecular relaxation behaviour of polyolefins exposed to high-energy radiation has been investigated by dielectric loss (tan δ) analysis. Therefore, low-density polyethylene, high-density polyethylene (HDPE), and isotactic polypropylene (iPP) were gamma-irradiated in air to various absorbed doses (up to 700 kGy). All relaxation zones (α, β, γ, and δ in the order of decreasing temperature), between 25 K and melting temperature, were studied. The radiation-induced changes observed in the dielectric relaxation spectra were related to the modifications in the structural and morphological parameters attributed to exposure of the polyolefins to radiation. Wide-angle X-ray diffraction, infrared spectroscopy, and gel measurements were used to determine the radiation-induced changes in the crystalline structure, oxidative degradation, and the degree of network formation, respectively. The present study reveals high dielectric and/or relaxation sensitivity of polyolefins to gamma radiation. Disappearance of some relaxations (such as β relaxation in HDPE and low temperature γ and δ relaxations in iPP) is clearly observed with irradiation. For the other relaxations, besides the large changes in the relaxation intensity, radiation also induces smaller/larger changes in the distribution of relaxation times, peak position, and activation energy.     

A kinetic spectrophotometric method for simultaneous determination of phenol and its three derivatives with the aid of artificial neural network

A novel kinetic spectrophotometric method was developed for determination of pyrocatechol, resorcin, hydroquinone and phenol based on their inhibitory effect on the oxidation of Rhodamine B (RhB) in acid medium at pH = 3.0. A linear relationship was observed between the inhibitory effect and the concentrations of the compounds. The absorbance associated with the kinetic reactions was monitored at the maximum wavelength of 557 nm. The effects of different parameters such as pH, concentration of RhB and KBrO₃, and temperature of the reaction were investigated and optimum conditions were established. The linear ranges were 0.22-3.30, 0.108-0.828, 0.36-3.96 and 1.52-19.76 μg mL⁻¹ for pyrocatechol, resorcin, hydroquinone and phenol, respectively, and their corresponding detection limits were 0.15, 0.044, 0.16 and 0.60 μg mL⁻¹. The measured data were processed by several chemometrics methods, such as principal component regression (PCR), partial least squares (PLS) and artificial neural network (ANN), and a set of synthetic mixtures of these compounds was used to verify the established models. It was found that the prediction ability of PLS, PCR and RBF-ANN was similar, however, the RBF-ANN model did perform somewhat better than the other methods. The proposed method was also applied satisfactorily for the simultaneous determination of pyrocatechol, resorcin, hydroquinone and phenol in real water samples.     

Deep Anomaly Detection on Tennessee Eastman Process Data

This paper provides the first comprehensive evaluation and analysis of modern (deep-learning-based) unsupervised anomaly detection methods for chemical process data. We focus on the Tennessee Eastman process dataset, a standard litmus test to benchmark anomaly detection methods for nearly three decades. Our extensive study will facilitate choosing appropriate anomaly detection methods in industrial applications. From the benchmark, we conclude that reconstruction-based methods are the methods of choice, followed by generative and forecasting-based methods.     

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.     

Photocatalytic degradation of C.I. Acid Orange 7 by TiO2 nanoparticles immobilized onto/into chitosan‐based hydrogel

Photocatalytic degradation of dye C.I. Acid Orange 7 in aqueous solution using TiO₂/hydrogel nanocomposite under solar light simulating source was studied. Hydrogel based on chitosan, itaconic and methacrylic acid was modified with colloidal TiO₂ nanoparticles synthetized by acidic hydrolysis of TiCl₄ and commercial Degussa P25 TiO₂ nanoparticles. SEM/EDX analysis confirmed the presence of TiO₂ nanoparticles onto/into hydrogel. It was found that both types of photocatalysts efficiently removed the dye from solution, but sorption rates and photodegradation efficiency were higher in the case of colloidal TiO₂ nanoparticles. They ensured complete discoloration of dye solution. The efficiency of the reused TiO₂/hydrogel nanocomposite showed that photodegradation activity was maintained at satisfactory level after three repeated cycles of illumination. POLYM. COMPOS., 35:806–815, 2014. © 2013 Society of Plastics Engineers     

整饰新技术是drupa的主要话题

在drupa 2004印刷展览会上，主题之一将是整饰技术。实际上，高质量包装印刷的机上整饰是零件印刷厂极为感兴趣的话题。这是因为印件要求特殊的整饰和超常的质量，又要频繁地改动设计。这些印件的印数越来越小，现在的价格也让客户承受得起，而且能够以非常短的印制周期生产出来。     

Impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 μm, whereas metal concentrations in finer size range of <1-75 μm were not affected. As practical implications, solids <1 μm and organic matter from 1 - >300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from <1 - >300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.     

Synthesis and characterization of the SBA-15/carbon cryogel nanocomposites

The ordered mesoporous silica SBA-15 materials were synthesized using Pluronic P123 (non-ionic triblock copolymer, EO₂₀PO₇₀O₂₀), under acidic conditions. SBA-15/carbon cryogel composites were obtained by sol–gel polycondensation of resorcinol and formaldehyde followed by freeze drying, and subsequent pyrolysis, in the presence of different amounts of SBA-15. For comparison purpose, SBA-15/carbon composite was also prepared using sucrose as carbon source. These materials were characterized by room temperature nitrogen adsorption–desorption measurement, X-ray diffraction, scanning electron microscopy (SEM) and Fourier transform infrared (FT-IR) spectroscopy. It was revealed that the samples have amorphous structure, high specific surface area (350–520 m² g^?1) and developed meso- as well as microporosity. The porosity of structure depends on the carbon source and Si/C ratio which can be easily controlled by varying concentration of starting solution.