Blends of polypropylene and ethylene octene comonomer with conducting fillers: Influence of state of dispersion of conducting fillers on electrical conductivity

Blends of polypropylene/ethylene octene comonomer (PP/EOC) with conducting fillers viz., carbon black (CB) and multiwall carbon nanotubes (MWNT) were prepared using melt mixing technique with varying filler concentration and blend compositions. Thermo gravimetric analysis studies indicated that presence of filler enhanced the thermal stability of PP/EOC blends. Morphological analysis revealed the formation of matrix‐dispersed droplet and co‐continuous type of morphology depending on the blend compositions. Significant reduction in droplet size and finer ligament thickness in co‐continuous structure were observed in the blends with filler due to compatibilization action. Fillers were found to be aggregated in the EOC phase irrespective of blends compositions and could be related to the affinity of the fillers toward EOC phase. The electrical conductivity of PP/EOC blends with CB and MWNT was found to be highest for 80/20 composition and decreased as EOC content increased. The percolation threshold of CB was between 10 and 15 wt% for the 80/20 and 70/30 blends whereas it was 15–20 wt% for blends with EOC content higher than 30 wt%. The percolation threshold was 2–3 wt% MWNT for PP/EOC blends. This was attributed to the aggregated filler network preferentially in the EOC phase. The melt‐rheological behavior of PP/EOC blends was significantly influenced in presence of both the fillers. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers     

Influence of Cobalt Doping on the Physical Properties of Zn<Subscript>0.9</Subscript>Cd<Subscript>0.1</Subscript>S Nanoparticles

Zn_0.9Cd_0.1S nanoparticles doped with 0.005–0.24 M cobalt have been prepared by co-precipitation technique in ice bath at 280 K. For the cobalt concentration >0.18 M, XRD pattern shows unidentified phases along with Zn_0.9Cd_0.1S sphalerite phase. For low cobalt concentration (≤0.05 M) particle size, d _XRD is ~3.5 nm, while for high cobalt concentration (>0.05 M) particle size decreases abruptly (~2 nm) as detected by XRD. However, TEM analysis shows the similar particle size (~3.5 nm) irrespective of the cobalt concentration. Local strain in the alloyed nanoparticles with cobalt concentration of 0.18 M increases ~46% in comparison to that of 0.05 M. Direct to indirect energy band-gap transition is obtained when cobalt concentration goes beyond 0.05 M. A red shift in energy band gap is also observed for both the cases. Nanoparticles with low cobalt concentrations were found to have paramagnetic nature with no antiferromagnetic coupling. A negative Curie–Weiss temperature of −75 K with antiferromagnetic coupling was obtained for the high cobalt concentration.     

Continuous operation of membrane bioreactor treating toluene vapors by Burkholderia vietnamiensis G4

A laboratory-scale biofilm membrane bioreactor inoculated with Burkholderia vietnamiensis G4 was examined to treat toluene vapors in a waste gas stream. The gas feed side and nutrient solution were separated by a composite membrane consisting of a porous polyacrylonitrile (PAN) support layer coated with a very thin (0.3 μm) dense polydimethylsiloxane (PDMS) top layer. After inoculation, a biofilm developed on the dense layer. The biofilm membrane bioreactor was operated continuously at different residence times (28–2 s) and loading rates (1.2–26.7 kg m⁻³ d⁻¹), with inlet toluene concentrations ranging from 0.21 to 4.1 g m⁻³. The overall performance of the membrane bioreactor was evaluated over a period of 165 days. Removal efficiencies ranging from 78% to 99% and elimination capacities from 4.2 to 14.4 kg m⁻³ d⁻¹ were observed after start-up period depending on the mode of operation. A maximum elimination capacity of 14.4 kg m⁻³ d⁻¹ was observed at a loading rate of 17.4 kg m⁻³ d⁻¹. Overall, the results illustrate that biofilm membrane reactors can potentially be more effective than conventional biofilters and biotrickling filters for the treatment of air pollutants such as toluene.     

Calibration of a hexapod machine tool using a redundant leg

Parallel configurations are recently being applied to the machine tool with the hopes of greater rigidity, stability, and accuracy than conventional multi-axis structures allow. However, the many calibration methods presently available for serial machine tools are not applicable to hexapod type structures. A calibration method is presented that uses a ball–bar or other simple length measuring device to act as an ‘extra leg,’ allowing calibration of the hexapod's true kinematic parameters. This method utilizes a total least squares minimization, does not require any special hexapod configuration or difficult six degree of freedom pose measurements, and is effective with as few as one additional length sensor. Selection of calibration pose sets is briefly discussed, as well as the influence of measurement noise on calibration accuracy. Simulations show the potential for this algorithm to significantly reduce errors to the point where machining errors are within 5–10 times the measurement errors.     

Using poly(N,N-dimethylaminoethyl methacrylate)/polyacrylonitrile composite membranes for gas dehydration and humidification

The transport of water vapor through a composite membrane consisting of hydrophilic poly(N,N-dimethylaminoethyl methacrylate) (PDMAEMA) as the active layer and polyacrylonitrile (PAN) as the substrate was investigated, and the performance of the membrane for gas dehydration and humidification applications was evaluated. For gas dehydration, methane/water vapor mixtures were used as feed and vacuum was applied on the downstream side. The feed composition and operating temperature were found to have a significant effect on the membrane performance. The PAN substrate had little effect on the permeation of methane, but the resistance of the substrate to water vapor permeation was significant because of the substantially higher permeability of water vapor in the membrane. For gas humidification, liquid water was brought to be in contact with the active layer of the membrane and nitrogen gas flowed on the other side. With an increase in the gas flow rate, the mass transfer rate of water through the membrane to reach the gas stream increased, and the humidity level of the gas stream decreased. The humidification can be enhanced significantly by operating at a higher temperature. A phenomenological mass transfer equation was derived for membrane humidifiers to correlate the overall mass transfer coefficient and membrane area, and this equation could be used in process design and scale up.     

All Ag Nanoparticles Are Not the Same: Covalent Interactions between Ag Nanoparticles and Nitrile Groups Help Combat Drug- and Ag-Resistant Bacteria

Antimicrobial resistance has long been viewed as a lethal threat to global health. Despite the availability of a wide range of antibacterial medicines all around the world, organisms have evolved a resistance mechanism to these therapies. As a result, a scenario has emerged requiring the development of effective antibacterial drugs/agents. In this article, we exclusively highlight a significant finding reported by Zbořil and associates (Adv. Sci. 2021, 2003090). The authors construct a covalently bounded silver-cyanographene (GCN/Ag) with the antibacterial activity of 30 fold higher than that of free Ag ions or typical Ag nanoparticles (AgNPs). Ascribed to the strong covalent bond between nitrile and Ag, an immense cytocompatibility is shown by the GCN/Ag towards healthy human cells with a minute leaching of Ag ions. Firm interactions between the microbial membrane and the GCN/Ag are confirmed by molecular dynamics simulations, which rule out the dependence of antibacterial activity upon the Ag ions alone. Thus, this study furnishes ample scope to unfold next-generation hybrid antimicrobial drugs to confront infections arising from drug and Ag-resistant bacterial strains.     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Transport of testosterone and estrogen from dairy-farm waste lagoons to groundwater

Although concentrated animal feeding operations constantly generate physiologically active steroidal hormones, little is known of their environmental fate. Estrogen and testosterone concentrations in groundwater and their distribution in sediments below a dairy-farm wastewater lagoon were therefore determined and compared to a reference site located upgradient of the farm. Forward simulations of flow as well as estrogen and testosterone transport were conducted based on data from the sediment profile obtained during drilling of a monitoring well belowthe dairy-farm waste lagoon. Testosterone and estrogen were detected in sediments to depths of 45 and 32 m, respectively. Groundwater samples were directly impacted by the dairy farm, as evidenced by elevated concentrations of nitrate, chloride, testosterone, and estrogen as compared to the reference site. Modeling potential transport of hormones in the vadose zone via advection, dispersion, and sorption could not explain the depths at which estrogen and testosterone were found, suggesting that other transport mechanisms influence hormone transport under field conditions. These mechanisms may involve interactions between hormones and manure as well as preferential flow paths, leading to enhanced transport rates. These types of interactions should be further investigated to understand the processes regulating hormone transport in the subsurface environment and parametrized to forecast long-term fate and transport of steroidal hormones.     

An empirical correlation for estimating the viscosity of non-Newtonian waxy crude oils

Non-Newtonian fluids are the most complex ones when it comes to predicting their flow behavior. In the pre-existing models, rheological behavior in waxy crude oils is mainly affected by shear rate and thermal history of crude oils. In the present work, rheological characteristics of four different crude oils were studied by coaxial cylindrical rheometer at three different temperatures (40°C, 50°C, and 60°C) and a model was proposed keeping into consideration wax content for the first time. This model is prepared to predict the viscosity of four different crude oils with different wax content and at different temperature. The proposed model can efficiently estimate the viscosity as compared to other established models.     

SUPERCRITICAL EXTRACTION OF STUART OIL SHALE

ABSTRACT

This paper describes the recovery of oil from Stuart oil shale using a supercritical extraction technique employing carbon dioxide as solvent. This supercritical technique provides yields superior to comparable retorting techniques. The importance of extraction temperature, pressure, and time has been investigated. In addition, the chemical composition of the oil extracted from the shale is presented. Simulated distillation has been employed to assess the effect of extraction conditions on the quality of the shale oil extracted.