Separation of CO2 from CH4 by pure PSF and PSF/PVP blend membranes: Effects of type of nonsolvent,solvent, and PVP concentration

Complete CO₂/CH₄ gas separation was aimed in this study. Accordingly, asymmetric neat polysulfone (PSF) and PSF/polyvinylpyrrolidone (PVP) blend membranes were prepared by wet/wet phase inversion technique. The effects of two different variables such as type of external nonsolvent and type of solvent on morphology and gas separation ability of neat PSF membranes were examined. Moreover, the influence of PVP concentration on structure, thermal properties, and gas separation properties of PSF/PVP blend membrane were tested. The SEM results presented the variation in membrane morphology in different membrane preparation conditions. Atomic forced microscopic images displayed that surface roughness parameters increased significantly in higher PVP loading and then gas separation properties of membrane improved. Thermal gravimetric analysis confirms higher thermal stability of membrane in higher PVP loading. Differential scanning calorimetric results prove miscibility and compatibility of PSF and PVP in the blend membrane. The permeation results indicate that, the CO₂ permeance through prepared PSF membrane reached the maximum (275 ± 1 GPU) using 1‐methyl‐2‐pyrrolidone as a solvent and butanol (BuOH) as an external nonsolvent. While, a higher CO₂/CH₄ selectivity (5.75 ± 0.1) was obtained using N‐N‐dimethyl‐acetamide (DMAc) as a solvent and propanol (PrOH) as an external nonsolvent. The obtained results show that PSF/PVP blend membrane containing 10 wt % of PVP was able to separate CO₂ from CH₄ completely up to three bar as feed pressure. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 130: 1139‐1147, 2013     

Development of solution-gated graphene transistor model for biosensors

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters (I_ds and V_gmin) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system.     

Roll compaction of maize powder

This paper presents a study of a roll compaction process as a dry granulation method for typical food materials such as maize powder. This process is widely applied in industry as it can continuously produce large quantities of granular product at comparatively low cost. The objectives of this work were to predict the roll compaction performance from a simple measurement involving uniaxial die compaction using the classical Johanson model. This involved determination of the optimum operating conditions for the production of granules as evaluated by apparent density.In the current work, a smooth counter-rotating rolling mill with a roller diameter of 0.08 m and a roller width of 0.20 m was used. The operating conditions for the rolling mill are shown to be influenced by parameters such as the roll gap, the roll speed, the feed powder amount, and the friction ratio. Material properties such as the compressibility factor and the angle of wall friction were investigated using uniaxial die compaction. The angle of wall friction was analysed using both contact mechanical and continuum mechanical approaches.The results indicated that this simplified approach can be used to provide a quantitative prediction of the extent of the roll compaction performance, and can be used to design optimal roller geometries and operating conditions.     

A Metaheuristic Technique for Cluster-Based Feature Selection of DNA Methylation Data for Cancer

Epigenetics is the study of phenotypic variations that do not alter DNA sequences. Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers. One of these alterations is DNA methylation; an epigenetic process that regulates gene expression and often occurs at tumor suppressor gene loci in cancer. Therefore, studying this methylation process may shed light on different gene functions that cannot otherwise be interpreted using the changes that occur in DNA sequences. Currently, microarray technologies; such as Illumina Infinium BeadChip assays; are used to study DNA methylation at an extremely large number of varying loci. At each DNA methylation site, a beta value (β) is used to reflect the methylation intensity. Therefore, clustering this data from various types of cancers may lead to the discovery of large partitions that can help objectively classify different types of cancers as well as identify the relevant loci without user bias. This study proposed a Nested Big Data Clustering Genetic Algorithm (NBDC-GA); a novel evolutionary metaheuristic technique that can perform cluster-based feature selection based on the DNA methylation sites. The efficacy of the NBDC-GA was tested using real-world data sets retrieved from The Cancer Genome Atlas (TCGA); a cancer genomics program created by the National Cancer Institute (NCI) and the National Human Genome Research Institute. The performance of the NBDC-GA was then compared with that of a recently developed metaheuristic Immuno-Genetic Algorithm (IGA) that was tested using the same data sets. The NBDC-GA outperformed the IGA in terms of convergence performance. Furthermore, the NBDC-GA produced a more robust clustering configuration while simultaneously decreasing the dimensionality of features to a maximum of 67% and of 94.5% for individual cancer type and collective cancer, respectively. The proposed NBDC-GA was also able to identify two chromosomes with highly contrasting DNA methylations activities that were previously linked to cancer.     

An aggregation technique for optimal decision-making in materials selection

Materials selection is an onerous but very important activity in the design process. An inappropriate choice of material(s) can adversely affect the productivity and profitability and hence reputation of a manufacturing organization. The complexity of materials selection makes multi-criteria analysis an invaluable tool in the engineering design process. However, the application of various multi-criteria decision making (MCDM) methods can yield different results, especially when alternatives lead to similar performance. Therefore, an aggregation technique is proposed in this paper for optimal decision-making. In this approach, ranking orders obtained by various MCDM methods are used as the input of the suggested procedure and the outputs are aggregation rankings, which help designers and engineers to reach a consensus on materials selection for a specific application. An illustrative example is given to demonstrate the application of this procedure and its effectiveness in obtaining optimal materials selection.     

Preparation and characterization of symmetric and asymmetric pure polysulfone membranes for CO2 and CH4 separation

Preparation of pure polysulfone (PSf) membrane for CO₂/CH₄ separation was aimed in this study. Accordingly, the effects of different variables such as: type and concentration of alcohol as external nonsolvent in the coagulation bath, solvent type in the casting solution and also presence of butanol (BuOH) as internal nonsolvent in polymer solution were examined. CO₂ and CH₄ permeabilities of prepared membranes in different coagulation baths follow this order: ethanol‐50% (EtOH‐50%) > isopropyl alcohol‐50% (IPA‐50%) > ethanol‐100% (EtOH‐100%) > IPA‐100%. According to scanning electron microscopy photographs, membrane asymmetry decreased in higher concentration of alcohols and a high symmetric membrane was prepared using IPA‐100% as external nonsolvent. CO₂/CH₄ selectivity improved in the following order: IPA‐100% > EtOH‐100% > IPA‐50% > EtOH‐50%. Then, a high CO₂/CH₄ selectivity (36.40) was obtained employing pure IPA in coagulation bath. When a mixture of NMP/THF was used instead of NMP as solvent, CO₂/CH₄ selectivity increased from 7.10 to 18.50. Thickness of membranes decreased from 124.70 to 72.11 μm by addition of BuOH concentration from 0 to 10 wt% as internal nonsolvent. Consequently, an enhancement in gas permeability was observed in higher BuOH concentrations. POLYM. ENG. SCI., 54:1686–1694, 2014. © 2013 Society of Plastics Engineers     

The Use of FTIR Spectroscopy and Chemometrics for Rapid Authentication of Extra Virgin Olive Oil

The authenticity of high value edible fats and oils including extra virgin olive oil (EVOO) is an emerging issue, currently. The potential employment of Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics of multivariate calibration and discriminant analysis has been exploited for rapid authentication of EVOO from canola oil (Ca‐O). The optimization of two calibration models of partial least square (PLS) and principle component regression was performed in order to quantify the level of Ca‐O in EVOO. The chemometrics of discriminant analysis (DA) was used for making the classification between pure EVOO and EVOO adulterated with Ca‐O. The individual oils and their blends were scanned on good contact with ZnSe crystals in horizontal attenuated total reflectance, as a sampling technique. The wavenumbers of 3,028–2,985 and 1,200–987 cm^?1 were used for quantification and classification of EVOO adulterated with Ca‐O. The results showed that PLS with normal FTIR spectra was well suited for quantitative analysis of Ca‐O with a value of the coefficient of determination (R²) > 0.99. The error, expressed as root mean square error of calibration obtained was relatively low, i.e. 0.108 % (v/v). DA can make the classification between pure EVOO and that adulterated with Ca‐O with one misclassified reported.     

High density polyethylene/ultra high molecular weight polyethylene blend. II. Effect of hydroxyapatite on processing,thermal, and mechanical properties

Hydroxyapatite (HA) is part of bone mineral composition. Several attempts have been made to incorporate HA into high density polyethylene (HDPE) to produce bone replacement biomaterials since neat HDPE is not suitable as bone replacement. The blending of HDPE with ultra high molecular weight polyethylene (UHMWPE) up to 50% by weight was performed with the aim of improving the toughness of composites. Reinforcement of blend with HA of up to 50% by weight was carried out. Methods of characterizing the composites included density, differential scanning calorimetry, thermal gravimetric analysis, ash content, and morphological examination using scanning electron microscope. For the mechanical properties of the composites, tensile, flexural, and impact tests were carried out. Incorporation of HA into HDPE has resulted in the brittleness of the composites. Blending of HDPE with UHMWPE in the presence of HA was found to improve the mechanical properties and promote a ductile failure of the resulting composites. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3931–3942, 2006