Evaluation of adsorption of nonionic surfactants blend at water/oil interfaces

The inherent biocompatibility of Span and Tween surfactants makes them an important class of nonionic emulsifiers that are employed extensively in emulsion and foam stabilization. The adsorption of Span-Tween blend at water/oil surface of emulsion has been investigated using a population balance model for the first time. Destability of emulsion was modeled by considering sedimentation, coalescence and interfacial coalescence terms in population balance equation (PBE). The terms of coalescence efficiency and interfacial coalescence time were considered as a function of surface coverage of droplets by surfactant molecules. The surface coverage at different surfactant concentrations was determined by minimization of difference between the model predictions and experimental average droplet sizes. After optimization, the surface coverage outputs were fitted with different adsorption isotherms to evaluate the adsorption behavior of Span-Tween surfactants blend at water/oil surface. The results show that Freundlich isotherm can predict the adsorption behavior of closer to the experimental observation. Moreover, fitted parameters imply the favorable adsorption of Span-Tween blend at water/oil interface.     

Detecting high-potential conditions of asphaltene precipitation in oil reservoir

Crude oil contains a wide range of components with different chemical natures. Complex molecules consisting of associated groups of polyaromatic sheets and alkyl side chains are known as asphaltene. Asphaltenes are insoluble in solvents such as n-heptane and n-pentane and soluble in benzene and toluene. Asphaltene causes serious damages around the wellbore and the reservoir by reducing permeability and plugging the pores. This paper includes a natural depletion test, performed on the bottom-hole sample and on a carbonate-core sample. The main emphasis is to identify high potentially damaged conditions in the reservoir from the asphaltene precipitation point of view. Stability of asphaltene was investigated by Saturates-Asphaltenes-Resins-Aromatics (SARA) analysis; moreover, asphaltene composition, permeability reduction, and porosity reduction were measured using the natural depletion in 4500, 3000, 2500, and 1450 psig via both static and dynamic approaches. At the pressures above the bubble point, asphaltene precipitation decreases as pressure increases, and the solubility model becomes dominant; on the other hand, below the saturation pressure, decrease in the pressure would decreases asphaltene precipitation and let the colloidal model dominate. It can be concluded that the maximum amount of asphaltene precipitation occurs near the saturation pressure. Asphaltene precipitation was then investigated through the core sample, using a novel scaling equation.     

A novel silk/PES hybrid nanofibrous scaffold promotes the in vitro proliferation and differentiation of adipose‐derived mesenchymal stem cells into insulin producing cells

Using stem cells to replace the lost beta cells is a hopeful strategy in the treatment of diabetic patients. Furthermore, during stem cell culture and therapy, it is a need to use a substrate to act as a supportive matrix to mimic 3D in vivo microenvironment. Therefore, in this study, human adipose‐derived stem cells were used to differentiate into insulin‐producing cells (IPCs) on a silk/polyethersulfone (PES) scaffold. After exposing to the differentiation media, 2D and 3D (silk/PES) cultured cells were gradually aggregated and formed spherical shaped clusters. The viability of cells was comparable in both 3D and 2D culture. As the results of gene expression assay in both RNA and protein level showed, the differentiation efficiency was higher in 3D culture. Furthermore, ELISA revealed that the release of C‐peptide and insulin was higher in 3D than 2D culture. It seems that silk/PES nanofibrous hybrid scaffold could provide an appropriate matrix to mimic in vivo microenvironment and therefore increases the IPC differentiation potency of stem cells.     

Optical artefacts in transflection mode FTIR microspectroscopic images of single cells on a biological support: the effect of back-scattering into collection optics

Infrared microspectroscopic imaging data of single human prostate cancer cells, on an artificial extracellular matrix (Matrigel) thin-film surface, are presented. The spectral intensity maps, obtained in reflection mode, appear to show that the protein intensity distribution observed at the location of a cell changes dramatically depending on the concentration and/or thickness of the underlying Matrigel layer. Specifically, cells adhered to a low protein concentration or thin surface exhibit a higher protein intensity signal than the surrounding layer whereas those on a high protein concentration or thick surface exhibit a lower protein intensity signal. These results are qualitatively explained by a simple model that takes into account the fact that radiation scattered from cells can enter the collection optics of the microscope without passing through the Matrigel layer. This leads to an apparent reduction in absorption at the cell.     

Multivariate versus univariate Kriging metamodels for multi-response simulation models

To analyze the input/output behavior of simulation models with multiple responses, we may apply either univariate or multivariate Kriging (Gaussian process) metamodels. In multivariate Kriging we face a major problem: the covariance matrix of all responses should remain positive-definite; we therefore use the recently proposed “nonseparable dependence” model. To evaluate the performance of univariate and multivariate Kriging, we perform several Monte Carlo experiments that simulate Gaussian processes. These Monte Carlo results suggest that the simpler univariate Kriging gives smaller mean square error.     

Relativistic and Non-Relativistic Quantum Brownian Motion in an Anisotropic Dissipative Medium

Using a minimal-coupling-scheme we investigate the quantum Brownian motion of a particle in an anisotropic-dissipative-medium under the influence of an arbitrary potential in both relativistic and non-relativistic regimes. A general quantum Langevin equation is derived and explicit expressions for quantum-noise and dynamical variables of the system are obtained. The equations of motion for the canonical variables are solved explicitly and an expression for the radiation-reaction of a charged particle in the presence of a dissipative-medium is obtained. Some examples are given to elucidate the applicability of this approach.     

Gaussian-DPSM (G-DPSM) and Element Source Method (ESM) modifications to DPSM for ultrasonic field modeling

In the last few years, Distributed Point Source Method (DPSM) a mesh-free semi-analytical technique has been developed. In spite of its many advantages, one shortcoming of the conventional DPSM method is that the field obtained by conventional DPSM method needs to be scaled to match the theoretical solutions. Two modification techniques called Gaussian-DPSM (G-DPSM) and Element Source Method (ESM) are developed here to avoid the scaling need. G-DPSM technique introduces additional fictitious point sources around every parent point source. Gaussian weight functions determine the strength of these additional fictitious point sources that are denoted as child point sources. ESM replaces discrete point sources used in the conventional DPSM by continuous sources. In the ESM formulation individual point sources are denoted as nodes. Special elements are formed on the boundary by connecting these nodes. The source strength inside the element can vary linearly or non-linearly depending on the order of the interpolation function used inside the element. Results generated by both these methods are compared with the conventional DPSM solution and analytical solution. It is shown that the ultrasonic field in front of the transducer computed by G-DPSM and ESM matches very well with the theory without using any scaling factor.     

The influence of NH3 -attaching on the NMR parameters in the zigzag BN nanotube

Two models of (10, 0) boron nitride nanotubes (BNNTs), perfect and Ammonia-attached, were studied in order to evaluate the influence of NH₃-attaching on the B-11 and N-15 nuclear magnetic resonance in the (10, 0) boron-nitride nanotube (BNNT) for the first time. At first, based on density functional theory (DFT) each of the structures was optimized using B3LYP/6-31G (d) model chemistry. At the next step, the chemical-shielding (CS) tensors were calculated using the B3LYP/6-31G (d, p) level of theory in both of the relaxed forms and were converted to experimentally measurable nuclear magnetic resonance (NMR) parameters, i.e. chemical-shielding isotropic (CSI) and chemical-shielding anisotropic (CSA). Our calculation revealed that in the NH₃-attached BNNT (the most stable model) the B atom chemically bonded to the NH₃ molecule has the largest chemical-shielding isotropic (CSI) and the smallest chemical-shielding anisotropic (CSA) values among the other boron nuclei. Additionally, the NMR parameters of those nuclei directly bonded to the boron dramatically change while those of the other B nuclei remain almost unchanged.     

Classic Kriging <Emphasis Type="Italic">versus</Emphasis> Kriging with bootstrapping or conditional simulation: classic Kriging’s robust confidence intervals and optimization

Kriging is a popular method for estimating the global optimum of a simulated system. Kriging approximates the input/output function of the simulation model. Kriging also estimates the variances of the predictions of outputs for input combinations not yet simulated. These predictions and their variances are used by ‘efficient global optimization’ (EGO), to balance local and global search. This article focuses on two related questions: (1) How to select the next combination to be simulated when searching for the global optimum? (2) How to derive confidence intervals for outputs of input combinations not yet simulated? Classic Kriging simply plugs the estimated Kriging parameters into the formula for the predictor variance, so theoretically this variance is biased. This article concludes that practitioners may ignore this bias, because classic Kriging gives acceptable confidence intervals and estimates of the optimal input combination. This conclusion is based on bootstrapping and conditional simulation.     

Simulation of Viscoelastic Fluid Flows in Expansion Geometry Using Finite Volume Approach简

The simulation results on viscoelastic fluid flows in sudden expansion geometry with different expansion ratios are presented. Oldroyd-B, linear Phan-Thien-Tanner （L-PTT） and Finitely Extensible Nonlinear Elastic （FENE-P） based constitutive equations were applied in two-dimensional Cartesian coordinates. The governing equations in transient and fully developed regions were solved using open source software called OpenFOAM. The flow patterns, including velocity profiles, shear stresses and first normal stress differences in some horizontal and vertical sections are illustrated. In addition, effects of the fluid type, flow dynamics and expansion ratio on the flow and vortex patterns in transient and fully developed regions are presented and discussed. The presented results show that existences of vortices cause the inverse velocity and negative stresses in expansion regions of the channel which increase with increment of expansion ratio and Weissenberg number （We）. Furthermore, some dead spaces can be observed at channel expansion regions close to the wall which are also increased. The results also show that at low We numbers all fluids show close behavior while at high We numbers the FENE-P fluid behavior shows high divergence from that of the two other fluids.