Measurement of yield stress for concentrated suspensions using a plate device

Slump has often been correlated with the yield stress of concrete as defined by the Bingham model. The discussion is still open as to what the yield stress value actually is and how to measure the yield stress of a suspension in general and for a cementitious material in particular. A plate device is a recent development in the measurement of yield stress of suspensions that allows for testing at shear rates far below most rotational rheometers. This paper presents the plate device and the modifications made so that it can be used with suspensions such as bentonite or titanium dioxide (TiO₂) in aqueous solution, as well as high concentration suspensions such as portland cement paste. A systematic analysis of the experimental results is presented with a critical discussion on the potential use of this device. The results indicate that the yield stresses of the suspensions determined by the plate device were generally lower than those determined by the parallel-plate rheometer. It appears that the pattern of stress growth curve and method of yield stress calculation in plate device experiments are affected by the suspension type.     

The synthesis of multilayer graphene materials by the fluorination of carbon nanodiscs/nanocones

Multilayer carbonaceous nanomaterial has been synthesized using a two-step process: carbon nanodiscs/nanocones were fluorinated using either the direct reaction with pure F₂ gas or the thermal decomposition of solid fluorinating agent (TbF₄). Then the fluorinated parts were removed by treatment at 600 °C in air. When the fluorine atoms are homogenously dispersed, using fluorination by TbF₄, thinning due to thermal defluorination results in multilayer materials with 7–10 nm of thickness and 400–500 nm of width. Such resulting materials and the fluorinated precursors have been characterized by solid state NMR, TGA, XRD, SEM, TEM, AFM and Raman spectroscopy.     

亲历莫桑比克红宝石之旅

2014年年中,亲历莫桑比克红宝石矿的绝对Gemfeilds公司首次在新加坡进行红宝石拍卖,此事件对全球交易市场而言是一个重要的里程碑。     

Thermal conductivity of polyimide/boron nitride nanocomposite films

The thermal conductivity of polyimide/boron nitride (PI/BN) nanocomposite thin films has been studied for two sizes of BN nanofillers (40 and 120 nm) and for a wide range of content. A strong influence of BN particle size on the thermal conduction of PI has been identified. In the case of the largest nanoparticles (hexagonal‐BN), the thermal conductivity of PI/h‐BN (120 nm) increases from 0.21 W/mK (neat PI) up to 0.56 W/mK for 29.2 vol %. For the smaller nanoparticles (wurtzite‐BN), PI/w‐BN (40 nm), we observed two different behaviors. First, we see a decrease until 0.12 W/mK for 20 vol % before increasing for higher filler content. The initial phenomenon can be explained by the Kapitza theory describing the presence of an interfacial thermal resistance barrier between the nanoparticles and the polymer matrix. This is induced by the reduction in size of the nanoparticles. Modeling of the experimental results allowed us to determine the Kapitza radius a_K for both PI/h‐BN and PI/w‐BN nanocomposites. Values of a_K of 7 nm and >500 nm have been obtained for PI/h‐BN and PI/w‐BN nanocomposite films, respectively. The value obtained matches the Kapitza theory, particularly for PI/w‐BN, for which the thermal conductivity is expected to decrease compared to that of neat PI. The present work shows that it seems difficult to enhance the thermal conductivity of PI films with BN nanoparticles with a diameter <100 nm due to the presence of high interfacial thermal resistance at the BN/PI interfaces. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42461.     

Function block-based human-robot collaborative assembly driven by brainwaves

As an emerging communication modality, brainwaves can be used to control robots for seamless assembly, especially in noisy environments where voice recognition is not reliable or when an operator is occupied with other tasks and unable to make gestures. This paper investigates human-robot collaborative assembly based on function blocks and driven by brainwaves. Using wavelet transform, brainwaves measured by EEG sensors are converted to time-frequency images and subsequently classified by a convolutional neural network (CNN) as commands to trigger a network of function blocks for assembly actions. The effectiveness of the system is experimentally validated through an engine-assembly case study.     

Minimal intervention to simulations of shallow-water equations

A minimal intervention (MI) strategy is employed to manage the unphysical oscillations in the classical finite volume (CFV) numerical solution of the shallow-water equations. Only the missing variables on the face of the finite volume are modified for Total Variation Diminishing (TVD). The MI strategy maintains long-term computational stability without compromising the accuracy of the numerical solution. Flux limiters are implemented by imposing downwind weighting factor constraints on the missing variables on a staggered grid as the shallow-water equations are updated by a fourth-order Runge-Kutta scheme. The shock capturing capability of this MI-CFV method is verified by comparing the simulations with the exact solutions. A series of turbulence simulations for sub-critical and super-critical flows demonstrates the long-term numerical stability of the computation scheme developed using the MI strategy.     

Wave runup simulations using Lagrangian blocks on Eulerian mesh

The runup of breaking and non-breaking solitary waves on a plane beach has been simulated using the shallow-water equations and a Lagrangian blocks on Eulerian mesh (LBEM) method. The results obtained for the entire range of wave steepness are compared with the experimental data, the nonlinear theory, and the finite-difference method. The LBEM simulation agrees with the nonlinear theory when the amplitude of the wave is small. On the whole, it produces a better result in agreement with the experimental data when friction is included in the simulation. The simulation also produced better result than the finite-difference simulation.     

Low-temperature anaerobic biological treatment of toluene-containing wastewater

Two expanded granular sludge bed-anaerobic filter (EGSB-AF) bioreactors, R1 and R2, were operated at 15 degrees C for the treatment of toluene-contaminated volatile fatty acid-based wastewater. The seed inoculum and the R1 reactor were unexposed to toluene, prior to and during the trial, respectively. Both reactors were operated at a hydraulic retention time of 24h at applied organic loading rates of 0.71-1.43kg chemical oxygen demand (COD)m(-3)d(-1). Toluene was supplemented to the R2 influent at concentrations of 5-104 mg toluenel(-1) (solubilised in ethanol). Bioreactor performance was evaluated by COD and toluene removal efficiency, and the methane content of biogas (%). Specific methanogenic activity and toxicity assays were employed to investigate the activity and toluene toxicity thresholds of key trophic groups, respectively, within the seed and reactor biomass samples. COD and toluene removal efficiencies of 70-90% and 55-99%, respectively, were achieved during the 630-d trial. Metabolic assays suggested that a psychrotolerant H(2)/CO(2)-utilizing methanogenic community developed in the toluene-degrading biomass. The results indicate the viability of low-temperature anaerobic digestion for the treatment of wastewater containing toluene.