On the formation and properties of asphaltene nanoaggregates and clusters by DC-conductivity and centrifugation

The hierarchical nanocolloidal structure of asphaltenes in solvent and even in crude oil has recently been delineated by a variety of techniques. It is highly desirable to compare results for the same samples from various techniques dependent on different physics. Here, the critical nanoaggregate concentration (CNAC) of specific asphaltenes is determined using both DC-conductivity and centrifugation; excellent agreement is found. In addition, the role of the lightest asphaltenes (or heaviest resins) in nanoaggregation is now amenable to direct measurement; inclusion of this weaker binding fraction does not materially impact the CNAC except by a trivial effect of dilution of the aggregating asphaltenes. DC-conductivity shows there is no observable change in CNAC over a moderate temperature range indicating that the enthalpy of formation of the nanoaggregate is zero. A simple analysis reveals that the entropy of nanoaggregate formation is positive, in agreement with previous work. Finally, the critical clustering concentration is observed at higher concentrations, and as always the clusters of nanoaggreates are found to have a small aggregation numbers. As with the CNAC, the heaviest resins do not affect the clustering concentration except by a trivial dilution effect.     

The effects of friction-stir process parameters on the fabrication of Ti/SiC nano-composite surface layer

Sound friction-stir processed layers were fabricated on a commercially pure titanium substrate with or without introduction of nano-sized SiC powder to the stir zone under an argon shrouding system using tool rotation and substrate advancing speeds in the range 800-1250 rpm and 35-55 mm/s, respectively. Surface layers exhibited finer grain sizes and greater hardness values compared to those of the as-received substrate. Superior surface enhancements were resulted by uniform dispersion of nano-sized SiC powder in the fabricated surface composite layer after four friction stir process passes. The fabricated Ti/SiC nano-composite surface layer showed a matrix of dynamically restorated ultra fine grains/subgrains with a mean size of ~ 400 nm and a hardness value of ~ 534 HV; this is about 3.3 times greater than that of the as-received substrate.     

Free‐radical homo‐ and copolymerization of vinyl acetate and n‐butyl acrylate: Kinetic studies by online 1H NMR kinetic experiments

Free‐radical homo‐ and copolymerization of vinyl acetate (VAc) and n‐butyl acrylate (BA) in benzene‐d₆ were performed by using benzoyl peroxide as an initiator at 70°C. Polymerization kinetic was followed by online ¹H NMR kinetic experiments. Significant drift in the comonomer mixture composition with reaction progress was observed. Reactivity ratios of VAc and BA were calculated by terminal unit model (TUM) as well as by simplified penultimate unit model (PUM) with r_VAc = 0. It was found that copolymer composition can be described well by the TUM. “Lumped” kinetic parameter ( $ k_p .k_t^{ - 0.5} $ ) was estimated from experimental data. A good fitting between the theoretical and experimental drifts in the comonomer mixture and copolymer compositions with reaction progress was observed. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

A novel modular fretting wear test rig

A novel modular experimental apparatus was designed and developed to measure and visualize fretting wear and friction for Hertzian circular and elliptical contacts and flat on flat contacts. The experimental apparatus utilizes a magnetostrictive actuator to reciprocate a flat, ball, or cylinder between two fixed specimens. Two stationary flat or cylindrical specimens mounted on a rotary table clamp the reciprocating specimen from the top and bottom to generate the fretting contact. The two stationary test specimens installed on the rotary table perpendicular to the moving specimen form a crossed cylinder geometry which creates a well-defined circular contact. An elliptical contact with different aspect ratios can be obtained by varying the angle between the fixed and the moving specimens. Dead weights placed on top of the upper stationary specimen provide the normal load. A force sensor located in line between the actuator output shaft and the specimen is used to measure friction. The test rig's modular design allows it to be configured for Hertzian circular (ball-on-flat, crossed cylinder), elliptical (crossed cylinder), and conformal (flat-on-flat) contacts. In the ball on flat configuration a steel flat or sapphire window is used in contact with the reciprocating ball. When the sapphire window is used a microscope and high speed camera is employed for in situ visualization and recording of the contact.     

Grading of gliomas using transfer learning on MRI images

Magnetic Resonance Materials in Physics, Biology and Medicine - Despite the critical role of Magnetic Resonance Imaging (MRI) in the diagnosis of brain tumours, there are still many pitfalls in the...     

Radiomics-based machine-learning method to diagnose prostate cancer using mp-MRI: a comparison between conventional and fused models

Magnetic Resonance Materials in Physics, Biology and Medicine - Multiparametric MRI (mp-MRI) has been significantly used for detection, localization and staging of Prostate cancer (PCa). However,...     

A new analytical model to predict heavy oil production rate in the SAGD process

An analytical model for predicting the oil production rate in the steam-assisted gravity drainage (SAGD) process is presented in this article. The suggested correlation is found based on Butler's original work. It considers the most effective parameters of the process that emphasize the influence of gravity drainage and that are grouped together in the form of the Rayleigh's number. The present model introduces three coefficients (i, j, and k) into the equation, which are determined by minimizing an objective function based on the difference between the six experimental SAGD datasets and the calculated results. The tool chosen for the minimization is the genetic algorithm (GA). After the initial evaluation, the same approach is used for other reservoir characteristics to ensure the robustness of the new equation. Having considered various simulation outcomes with an average error of 8.9% makes this model a credible one for predicting the SAGD production rates. The novelty of the new predictive model lies within its unique approach, making it quite fast and applicable to a wide range of reservoirs with low associated estimation inaccuracies.