Monitoring and risk assessment of tetracycline residues in foods of animal origin

Food Science and Biotechnology - A total of 450 samples consisting of red meat, poultry meat, aquatic product and raw milk were collected during winter 2016 and summer 2017. 22.2% (100/450) of...     

On‐Chip Self‐Assembly of a Smart Hybrid Nanocomposite for Antitumoral Applications

A hybrid nanocomposite comprised by porous silicon nanoparticles and a stimuli responsive polymeric material, polyethylene glycol‐block‐poly(L‐histidine), is spontaneously formed by nanoprecipitation in a flow‐focusing microfluidic chip. The nanocomposite presents a novel hybrid compound micelle structure with a great robustness for therapeutic applications. Therefore, the nanocomposite is developed and tested as a “smart” multistage drug delivery system (MDDS) in response to some of the current problems that cancer treatment presents. Based on the stimuli‐responsive behavior of the nanocomposite, a chemotherapeutic agent is successfully loaded into the nanosystem and released upon changes in the pH‐values. The nanocomposite demonstrates enhanced stability in plasma, narrow size distribution, improved surface smoothness, and high cytocompatibility. Furthermore, the nanocomposite presents reduced nanoparticle internalization by phagocytic macrophage cells and pH‐dependent cell growth inhibition capacity. Overall, the developed hybrid nanocomposite shows very promising features for its further development as a “smart” pH‐responsive MDDS.     

Simultaneous saccharification and fermentation of sweet sorghum after acid pretreatment

The sweet sorghum bagasse pretreated with 5% (w/w) acetic acid at an accumulated solid concentration of 20% (w/v) during the 96-h fed-batch simultaneous saccharification and fermentation achieved a maximum ethanol concentration of 53.1 g/L and ethanol yield of 88.7%, compared to 25.7 g/L and 86.7% for the 96-h batch simultaneous saccharification and fermentation at a solid concentration of 10% (w/v), respectively. For comparison, the bagasse pretreated with 0.5% (w/w) sulfuric acid and water under the same fed-batch simultaneous saccharification and fermentation conditions produced maximum ethanol concentrations of 44.3 and 36.5 g/L, and ethanol yields of 77.6 and 69.7%, respectively.     

Evaluation of the ability of the hydrophobic nanoparticles of SiO2 in the EOR process through carbonate rock samples

More than 50% of oil remains in reservoirs after primary and secondary recovery processes. Consequently, methods of enhanced oil recovery (EOR) should be applied for more recovery from these reservoirs. In this study the ability of hydrophobic nanoparticles of sio₂ in EOR process through carbonate rock samples is studied. By employing hydrophobic nanosilica, we can lower interfacial tension between oil and nanofluid and then reduce the mobility ratio between oil and nanofluid in carbonate reservoirs; however, nanosilica can increase the viscosity of water exponentially. To evaluate this goal, core displacement experiment for carbonate core is conducted. These experiments are performed on the carbonate samples saturated with oil and brine that had got injected with nanosilica with six different concentrations. Investigating the outcomes shows that by rising nanoparticle concentration, the IFT between water and oil phases decreases and yields in decrease the mobility ratio between oil and nanofluid. For this, we measure the recovery level in different states of using 0.05, 0.1, 0.1, 0.15, 0.3, 0.6, 1.0, and 0 concentration of the nanoparticle. The outcomes achieved from our experiments reveals that employing hydrophobic nanosilica could increases the oil recovery factor.     

Enhancement of the Ti-6Al-4V alloy corrosion resistance by applying CrN/CrAlN multilayer coating via Arc-PVD method

In this study, the Ti-6Al-4V substrate was coated by CrN-CrN/TiN-TiN and CrN/CrAlN multilayer coatings using the cathodic arc physical vapor deposition (Arc-PVD) method. The results of potentiodynamic polarization (PDP) have shown the lowest and highest corrosion current density belong to the double-layer (0.16 µA/Cm²) and TiN (0.51 µA/Cm²) samples, indicating the higher corrosion resistance of the double-layer coating. The field emission electron microscope (FESEM), X-ray diffraction pattern (XRD), open circuit potential (OCP), PDP, and electrochemical impedance spectroscopy (EIS) analysis were employed in order to characterize the coatings and evaluate their corrosion behavior. Finally, applying the double-layer coating resulted in the significant improvement of the protective behavior of the Ti-6Al-4V alloy, as compared to the sample coated with TiN in corrosive environments.     

3-dimensional numerical analysis of friction stir welding of copper and aluminum

Journal of Mechanical Science and Technology - A time dependent Eulerian thermal/material flow model of friction stir welding was developed and applied to the dissimilar joining of pure copper and...     

Prediction of Uniaxial Compressive Strength of Underground Formations From Sonic Log Parameters

Selecting the most appropriate bit for any hole section is the key feature in achieving superior drilling performance. This feature has an enormous influence on the optimized performance of drilling and also economically affects the process greatly. The most important factor to correctly select a bit is formation physical characteristics, mainly rock compressive strength. Different sources can be used to obtain rock strength along the wellbore, such as logs, cutting and rock mechanical test, or even drilling data. The use of empirical correlations based on logs is often the only way to estimate strength in many situations due to the absence of cores for laboratory tests. In this study, one of the Iranian oil fields was selected to be analyzed. The goal was calculating the compressive strength from sonic log parameters. In order to develop an exponential correlation, log, drilling data, and backward simulation were used. Log data included sonic, neutron, density, and gamma ray logs. The correlation developed is applicable to determine the quantity of compressive strength of underground formations in absence of cores.     

The Development of a New Sonic Correlation for UCS Estimation from Drilling Data

Abstract

One of the most important characteristics of rocks in drilling operations is unconfined rock strength (UCS), which is critical in different aspects of drilling operations. Several laboratory-based correlations have been generated for specific rocks to estimate UCS from physical properties (such as transient time, porosity, and Young's modulus) of the rocks. In drilling analysis, when UCS information is required and direct methods for estimation of UCS are not available, it is common to use correlations that have been developed for other formations with the same or similar lithology. Obviously, the results of estimations based on UCS correlations for other formations will not be accurate and can affect subsequent analyses. Therefore, it is highly recommended to generate a correlation for the formation of interest, though it is not always possible to reach this goal from experimental works on core samples retrieved from the formation.

In this study, a sonic correlation that shows that it can provide relatively better global estimation of UCS for limestone rocks is modified for one of the Iranian carbonate formations by determining new coefficients for the correlation based on drilling data. For this purpose, the drilling information recorded in mud logging data is analyzed to backward simulate the drilling process based on a modified penetration rate model and calculate the rock strengths of the formation. The apparent rock strength log generated from this calculation proceeds quality-controlled steps according to statistical and pattern recognition methods to eliminate the noises and fluctuations that normally exist while working with field data. Then, a new correlation is developed from the formation response to sonic logs and apparent rock strength log. Because this new correlation is originally generated for the formation of interest, UCS is estimated more accurately and analyses dependent on UCS show fewer errors.