Modeling of CO2-brine interfacial tension: Application to enhanced oil recovery

Development of reliable and accurate models to estimate carbon dioxide–brine interfacial tension (IFT) is necessary, since its experimental measurement is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure. In the current study, feed forward artificial neural network is used for estimation of CO₂–brine IFT based on data from published literature which consists of a number of carbon dioxide–brine interfacial tension data covering broad ranges of temperature, total salinity, mole fractions of impure components and pressure. Trial-and-error method is utilized to optimize the artificial neural network topology in order to enhance its capability of generalization. The results showed that there is good agreement between experimental values and modeling results. Comparison of the empirical correlations with the proposed model suggests that the current model can predict the CO₂–brine IFT more accurately and robustly.     

Synthesis of Ferrocene-Based Hyperbranched Polyether and Its Catalytic Performance for Thermal Decomposition of Ammonium Perchlorate

A series of ferrocene-based hyperbranched polyethers (HBPE-Fc) with different ferrocene content were synthesized by esterification of ferrocenecarbonyl chloride and hyperbranched polyether (HBPE). ¹H NMR and FT-IR were used to confirm the structure of HBPE and HBPE-Fc. GPC was used to calculate the molecular weights. The catalytic performance of the synthesized HBPE-Fc for thermal decomposition of ammonium perchlorate (AP) was investigated by TG and DTG techniques. The results showed that HBPE-Fc exhibited good catalytic activity on the thermal decomposition of AP. The influence factors on catalytic performances, such as substitution degree of ferrocene and mass ratio of AP/HBPE-Fc were discussed as well.     

Probabilistic Fatigue Life Prediction and Structural Reliability Evaluation of Turbine Rotors Integrating an Automated Ultrasonic Inspection System

The paper presents a general method and procedure for fatigue reliability assessment integrating automated ultrasonic non-destructive inspections. The basic structure of an automated ultrasonic inspection system is presented. Fatigue reliability assessment methodology is developed using uncertainty quantification models for detection, sizing, and fatigue model parameters. The probability of detection model is based on a classical log-linear model coupling the actual flaw size with the ultrasonic inspection reported size. Using probabilistic modeling, the distribution of the actual flaw size is derived. Reliability assessment procedure using ultrasonic inspection data is suggested. A steam turbine rotor example with realistic ultrasonic inspection data is presented to demonstrate the overall method. Calculations and interpretations of assessment results based on risk recommendations for industrial applications are given.     

Spatial analyses of wildlife contact networks

Datasets from which wildlife contact networks of epidemiological importance can be inferred are becoming increasingly common. A largely unexplored facet of these data is finding evidence of spatial constraints on who has contact with whom, despite theoretical epidemiologists having long realized spatial constraints can play a critical role in infectious disease dynamics. A graph dissimilarity measure is proposed to quantify how close an observed contact network is to being purely spatial whereby its edges are completely determined by the spatial arrangement of its nodes. Statistical techniques are also used to fit a series of mechanistic models for contact rates between individuals to the binary edge data representing presence or absence of observed contact. These are the basis for a second measure that quantifies the extent to which contacts are being mediated by distance. We apply these methods to a set of 128 contact networks of field voles (Microtus agrestis) inferred from mark–recapture data collected over 7 years and from four sites. Large fluctuations in vole abundance allow us to demonstrate that the networks become increasingly similar to spatial proximity graphs as vole density increases. The average number of contacts, , was (i) positively correlated with vole density across the range of observed densities and (ii) for two of the four sites a saturating function of density. The implications for pathogen persistence in wildlife may be that persistence is relatively unaffected by fluctuations in host density because at low density is low but hosts move more freely, and at high density is high but transmission is hampered by local build-up of infected or recovered animals.     

The Electrochemical Behavior of Au/AuNPs/PNA/ZnSe-QD/ACA Electrode Towards CySH Oxidation

Nano-Micro Letters - This work describes the electrochemical behavior of azodicarboxamide (ACA) film immobilized on the surface of penicillamine (PNA)/ZnSe-quantum dot (ZnSe-QD) gold nanoparticle...     

Hot tensile properties and microstructural evolution of as cast NiTi and NiTiCu shape memory alloys

Hot tensile properties of as cast NiTi and NiTiCu shape memory alloys were investigated by hot tensile test at temperature range of 700–1100 °C using the strain rate of 0.1 s⁻¹. The NiTi alloy exhibited a maximum hot ductility at temperature range of 750–1000 °C, while the NiTiCu alloy showed it at temperature range of 800–1000 °C. It was found that at temperatures less than 750 °C, diffusion-assisted deformation mechanism was inactive leading to semi-brittle type of failure and limited ductility in both alloys. Also it was found that at temperature range of 800–1000 °C, dynamic recrystallization is dominant leading to high ductility. Likewise, the fracture surface of the specimens presenting the maximum hot ductility showed an ideal type of ductile rupture in which they gradually pulled out to a fine point. On the other hand, the decline in ductility occurred at the temperatures above 1000 °C was attributed to the liquid phase formation leading to interdendritic and intergranular type of fracture.     

pH-dependant structural and morphology evolution of Ni(OH)2 nanostructures and their morphology retention upon thermal annealing to NiO

Nickel hydroxide nanosheets, nanobelts and nanorods were prepared by hydrothermal treatment of the precipitates obtained at different pH values. The morphology and crystal structure of the products could be controlled simply by adjusting the pH value at precipitation. Interconnected nanosheets of hexagonal β-Ni(OH)₂ with thickness around 10–20 nm were formed at pH ∼ 11, whereas nanobelts with typical widths around 40–80 nm, and nanorods with diameters around 50–60 nm of phase pure α-Ni(OH)₂ containing intercalated sulphate ions were obtained in the pH range ∼9.5–8.5. Thermal annealing of the hydroxides at 500 °C yielded cubic phase NiO with morphologies similar to their hydroxide precursors. X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and energy dispersive X-ray (EDX) analysis were used to characterize the as-prepared products. The role of pH in controlling the phase and morphology of the products was discussed.     

Orchestrated structure evolution: modeling growth-regulated nanomanufacturing

Orchestrated structure evolution (OSE) is a scalable manufacturing method that combines the advantages of top-down (tool-directed) and bottom-up (self-propagating) approaches. The method consists of a seed patterning step that defines where material nucleates, followed by a growth step that merges seeded islands into the final patterned thin film. We develop a model to predict the completed pattern based on a computationally efficient approximate Green's function solution of the diffusion equation plus a Voronoi diagram based approach that defines the final grain boundary structure. Experimental results rely on electron beam lithography to pattern the seeds, followed by the mass transfer limited growth of copper via electrodeposition. The seed growth model is compared with experimental results to quantify nearest neighbor seed-to-seed interactions as well as how seeds interact with the pattern boundary to impact the local growth rate. Seed-to-seed and seed-to-pattern interactions are shown to result in overgrowth of seeds on edges and corners of the shape, where seeds have fewer neighbors. We explore how local changes to the seed location can be used to improve the patterning quality without increasing the manufacturing cost. OSE is shown to enable a unique set of trade-offs between the cost, time, and quality of thin film patterning.     

On the Performance of Phase I Dispersion Control Charts for Process Monitoring

Control charts are usually implemented in two phases: the retrospective phase (phase I) and the monitoring phase (phase II). The performance of any phase II control chart structure depends on the preciseness of the control limits obtained from the phase I analysis. In statistical process control, the performance of phase I dispersion charts has mainly been investigated for normal or contaminated normal distributions of the quality characteristic of interest. Little work has been carried out to investigate the performance of a wide range of possible phase I dispersion charts for processes following non‐normal distributions. The current study deals with the proper choice of a control chart for the evaluation of process dispersion in phase I. We have analyzed the performance of a wide range of dispersion control charts, including two distribution‐free structures. The performance of the control charts is evaluated in terms of probability to signal, under normal and non‐normal process setups. These results will be useful for quality control practitioners in their selection of a phase I control chart. Copyright © 2014 John Wiley & Sons, Ltd.