Transport Properties of Self-Consolidating Concrete

The permeability of concrete is influenced by the porosity and the interconnectivity of the pores in the cement paste and the microcracks in concrete, especially in the interface of paste-aggregate. The movements of gases, liquids, and ions through concrete is important because of their interactions with concrete constituents, including pore water, which can alter the integrity of concrete directly and indirectly, leading to the deterioration of structures. This study reports the findings from an investigation carried out to study the effect of the mixture variations on the durability of medium- and high-strength self-consolidating concrete (SCC). The mixture variations studied include the type of mineral admixtures, such as limestone powder (LSP) and pulverized fuel ash (PFA), and viscositymodifying admixtures (VMA) for both medium- and high-strength SCC. Air permeability, water permeability, capillary absorption, and chloride diffusivity were used to assess the durability of SCC mixtures in comparison with normal, vibrated concretes. The results showed that SCC mixtures, for medium- and high-strength grades using PFA followed by LSP, have lower permeability properties compared with normal concretes. SCC made with VMA had a higher sorptivity, air permeability, and water permeability compared with other SCC mixtures, which can be attributed to higher watercement ratio (w/c) and lack of pore filling effect. An in-place migration coefficient was obtained using the in-place ion migration test. This was used to compare the potential diffusivity of different concretes. The results indicated that SCC, for both grades of strength, made with PFA showed much lower diffusivity values in comparison with other mixtures, whereas the SCC mixtures with VMA showed higher diffusivity.

Kinetic model for the hydrolysis of lignocellulosic biomass in the ionic liquid, 1-ethyl-3-methyl-imidazolium chloride†

The kinetics of the acid-catalysed hydrolysis of cellobiose in the ionic liquid 1-ethyl-3-methylimidazolium chloride, [C(2)mim]Cl, was studied as a model for general lignocellulosic biomass hydrolysis in ionic liquid systems. The results show that the rate of the two competing reactions, polysaccharide hydrolysis and sugar decomposition, vary with acid strength, and that for acids with an aqueous pK(a) below approximately zero, the hydrolysis reaction is significantly faster than the degradation of glucose, thus allowing hydrolysis to be performed with a high selectivity in glucose. In tests with soluble cellulose, hemicellulose (xylan), and lignocellulosic biomass (Miscanthus grass), comparable hydrolysis rates were observed with bond scission occurring randomly along the biopolymer chains, in contrast to end-group hydrolysis observed with aqueous acids.

Using Caenorhabditis elegans to probe toxicity of 1-alkyl-3-methylimidazolium chloride based ionic liquids

Ionic liquids are gaining attention as new solvents within the green chemistry community; however this attention has quickly outstripped current environmental and toxicological data available. In the present communication, we establish the use of Caenorhabditis elegans as a model organism for inexpensively and quickly exploring toxicological effects of 1-alkyl-3-methylimidazolium chloride ionic liquids.

Reactivity of ammonium chloride/mercuric chloride mixtures with monel containers. The new compounds (NH4)(2)(NH3)(x)[Ni(NH3)(2)Cl-4] and (NH4)(5)Cl-2[CuCl2][CuCl4]

Ammonium chloride/mercuric chloride mixtures (molar ratio 2: 1) react at 350degreesC with Monel (Cu68Ni32) to yield (NH4)NiCl3 and mercury and copper amalgam, respectively. With larger amounts of (NH4)Cl in the reaction mixture, dark green (NH4)(2)(NH3)(x)[Ni(NH3)(2)Cl-4] (x approximate to 0.77) (1) is also formed as a main product. Light blue crystals of the mixed-valent copper(I,II) chloride (NH4)(5)Cl-5[CuCl2][CuCl4] (2) were obtained as a minor byproduct from a 4:1 reaction mixture. The crystal structures were determined from single crystal X-ray data; (1): tetragonal, I4/mmm, a = 770.9(1), e = 794.2(2) pm, 190 reflections, R-1 = 0.0263; (2): tetragonal, I4/mcm, a = 874.8(1), c = 2329.2(3) pm, 451 reflections, R-1 = 0.0736. In (1) Ni2+ resides in trans-[Ni(NH3)(2)Cl-4](2-) octahedra, and in (2) copper(l) is linearly two-coordinated in ECUC121- and copper(II) resides in a flattened tetrahedron [CuCl4](2-) with a tetrahedricity of 89%. (C) 2001 Elsevier Science.

Antibiofilm activities of 1-alkyl-3-methylimidazolium chloride ionic liquids

Microbial biofilms are ubiquitous in nature and represent the predominant mode of growth of microorganisms. A general characteristic of biofilm communities is that they tend to exhibit significant tolerance to antimicrobial challenge compared with planktonic bacteria of the same species The antibiofilm activity of a series of 1-alkyl-3-methylimidazolium chloride ionic liquids has been evaluated against a panel of clinically significant microbial pathogens, including MRSA. A comparison of antimicrobial activity against planktonic bacteria and established biofilms is presented. In general, these ionic liquids possess potent, broad spectrum antibiofilm activity.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.