148 resultados para chemical spots


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We have developed an explanation for ultra trace detection found when using Au/Ag SERS nanoparticles linked to biochemical affinity tags, e.g. antibodies. The nanoparticle structure is not as usually assumed and the aggregated nanoparticles constitute hot spots that are indispensable for these very low levels of analyte detection, even more so when using a direct detection method.

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Following the growing need for adoption of alternative fuels, this project aimed at getting more information on the oxidative potential of biodiesel particulate matter. Within this scope, the physical and chemical characteristics of biodiesel PM were analysed which lead to identification of reactive organic fractions. An in-house developed proflurescent nitroxide probe was used. This project further developed in-depth understanding of the chemical mechanisms following the detection of the oxidative potential of PM. This knowledge made a significant contribution to our understanding of processes behind negative health effects of pollution and enabled us to further develop new techniques to monitor it.

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Liuwei Dihuang Wan (LWD), a classic Chinese medicinal formulae, has been used to improve or restore declined functions related to aging and geriatric diseases, such as impaired mobility, vision, hearing, cognition and memory. It has attracted increasingly much attention as one of the most popular and valuable herbal medicines. However, the systematic analysis of the chemical constituents of LDW is difficult and thus has not been well established. In this paper, a rapid, sensitive and reliable ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight high-definition mass spectrometry (UPLC-ESI-Q-TOF-MS) method with automated MetaboLynx analysis in positive and negative ion mode was established to characterize the chemical constituents of LDW. The analysis was performed on a Waters UPLCTM HSS T3 using a gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. Under the optimized conditions, a total of 50 peaks were tentatively characterized by comparing the retention time and MS data. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS has been successfully developed for globally identifying multiple-constituents of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of the chemical constituents of LDW. This article is protected by copyright. All rights reserved.

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Stress corrosion cracking (SCC) is a well known form of environmental attack in low carat gold jewellery. It is desirable to have a quick, easy and cost effective way to detect SCC in alloys and prevent them from being used and later failing in their application. A facile chemical method to investigate SCC of 9 carat gold alloys is demonstrated. It involves a simple application of tensile stress to a wire sample in a corrosive environment such as 1–10 % FeCl3 which induces failure in less than 5 minutes. In this study three quaternary (Au, Ag, Cu and Zn) 9 carat gold alloy compositions were investigated for their resistance to SCC and the relationship between time to failure and processing conditions is studied. It is envisaged that the use of such a rapid and facile screening procedure at the production stage may readily identify alloy treatments that produce jewellery that will be susceptible to SCC in its lifetime.

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Chemical reaction studies of N-methyl-N-propyl-pyrrolidinium-bis(fluorosulfonyl)imide-based ionic liquid with the lithium metal surface were performed using ab initio molecular dynamics (aMD) simulations and X-ray Photoelectron Spectroscopy (XPS). The molecular dynamics simulations showed rapid and spontaneous decomposition of the ionic liquid anion, with subsequent formation of long-lived species such as lithium fluoride. The simulations also revealed the cation to retain its structure by generally moving away from the lithium surface. The XPS experiments showed evidence of decomposition of the anion, consistent with the aMD simulations and also of cation decomposition and it is envisaged that this is due to the longer time scale for the XPS experiment compared to the time scale of the aMD simulation. Overall experimental results confirm the majority of species suggested by the simulation. The rapid chemical decomposition of the ionic liquid was shown to form a solid electrolyte interphase composed of the breakdown products of the ionic liquid components in the absence of an applied voltage.

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The effect of storage time on the cyclability of lithium electrodes in an ionic liquid electrolyte, namely 0.5 m LiBF4 in N-methyl-N-propyl pyrrolidinium bis(fluorosulfonyl)imide, [C3mpyr+][FSI–], was investigated. A chemical interaction was observed which is time dependent and results in a morphology change of the Li surface due to build up of passivation products over a 12-day period. The formation of this layer significantly impacts on the Li electrode resistance before cycling and the charging/discharging process for symmetrical Li|0.5 m LiBF4 in [C3mpyr+][FSI–]|Li coin cells. Indeed it was found that introducing a rest period between cycling, and thereby allowing the chemical interaction between the Li electrode and electrolyte to take place, also impacted on the charging/discharging process. For all Li surface treatments the electrode resistance decreased after cycling and was due to significant structural rearrangement of the surface layer. These results suggest that careful electrode pretreatment in a real battery system will be required before operation.

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Globally, obesity and diabetes (particularly type 2 diabetes) represents a major challenge to world health. Despite decades of intense research efforts, the genetic basis involved in diabetes pathogenesis & conditions associated with obesity are still poorly understood. Recent advances have led to exciting new developments implicating epigenetics as an important mechanism underpinning diabetes and obesity related disease. One epigenetic mechanism known as the "histone code" describes the idea that specific patterns of post-translational modifications to histones act like a molecular "code" recognised and used by non-histone proteins to regulate specific chromatin functions. One modification which has received significant attention is that of histone acetylation. The enzymes which regulate this modification are described as lysine acetyltransferases or KATs and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. Some of the known inhibitors of HDACs (HDACi) have also been shown to act as "chemical chaperones" to alleviate diabetic symptoms. In this review, we discuss the available evidence concerning the roles of HDACs in regulating chaperone function and how this may have implications in the management of diabetes. © 2009 Bentham Science Publishers Ltd.

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This thesis reports a comprehensive study on the physical and chemical properties of airborne particles in Brisbane, especially around schools. The sources and potential toxicity of the particles were identified, enabling an assessment of the contributing factors to children's exposure at school. The results from this thesis give a quantitative estimate of the range of airborne particles that children are exposed to at urban schools with different traffic conditions.

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Chemical vapor deposition (CVD) is widely utilized to synthesize graphene with controlled properties for many applications, especially when continuous films over large areas are required. Although hydrocarbons such as methane are quite efficient precursors for CVD at high temperature (∼1000 °C), finding less explosive and safer carbon sources is considered beneficial for the transition to large-scale production. In this work, we investigated the CVD growth of graphene using ethanol, which is a harmless and readily processable carbon feedstock that is expected to provide favorable kinetics. We tested a wide range of synthesis conditions (i.e., temperature, time, gas ratios), and on the basis of systematic analysis by Raman spectroscopy, we identified the optimal parameters for producing highly crystalline graphene with different numbers of layers. Our results demonstrate the importance of high temperature (1070 °C) for ethanol CVD and emphasize the significant effects that hydrogen and water vapor, coming from the thermal decomposition of ethanol, have on the crystal quality of the synthesized graphene.

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Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

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Purpose: This study investigated the effect of chemical conjugation of the amino acid L-leucine to the polysaccharide chitosan on the dispersibility and drug release pattern of a polymeric nanoparticle (NP)-based controlled release dry powder inhaler (DPI) formulation. Methods: A chemical conjugate of L-leucine with chitosan was synthesized and characterized by Infrared (IR) Spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy, Elemental Analysis and X-ray Photoelectron Spectroscopy (XPS). Nanoparticles of both chitosan and its conjugate were prepared by a water-in-oil emulsification – glutaraldehyde cross-linking method using the antihypertensive agent, diltiazem (Dz) hydrochloride as the model drug. The surface morphology and particle size distribution of the nanoparticles were determined by Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS). The dispersibility of the nanoparticle formulation was analysed by a Twin Stage Impinger (TSI) with a Rotahaler as the DPI device. Deposition of the particles in the different stages was determined by gravimetry and the amount of drug released was analysed by UV spectrophotometry. The release profile of the drug was studied in phosphate buffered saline at 37 ⁰C and analyzed by UV spectrophotometry. Results: The TSI study revealed that the fine particle fractions (FPF), as determined gravimetrically, for empty and drug-loaded conjugate nanoparticles were significantly higher than for the corresponding chitosan nanoparticles (24±1.2% and 21±0.7% vs 19±1.2% and 15±1.5% respectively; n=3, p<0.05). The FPF of drug-loaded chitosan and conjugate nanoparticles, in terms of the amount of drug determined spectrophotometrically, had similar values (21±0.7% vs 16±1.6%). After an initial burst, both chitosan and conjugate nanoparticles showed controlled release that lasted about 8 to 10 days, but conjugate nanoparticles showed twice as much total drug release compared to chitosan nanoparticles (~50% vs ~25%). Conjugate nanoparticles also showed significantly higher dug loading and entrapment efficiency than chitosan nanoparticles (conjugate: 20±1% & 46±1%, chitosan: 16±1% & 38±1%, n=3, p<0.05). Conclusion: Although L-leucine conjugation to chitosan increased dispersibility of formulated nanoparticles, the FPF values are still far from optimum. The particles showed a high level of initial burst release (chitosan, 16% and conjugate, 31%) that also will need further optimization.

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In this article, we analyse bifurcations from stationary stable spots to travelling spots in a planar three-component FitzHugh-Nagumo system that was proposed previously as a phenomenological model of gas-discharge systems. By combining formal analyses, center-manifold reductions, and detailed numerical continuation studies, we show that, in the parameter regime under consideration, the stationary spot destabilizes either through its zeroth Fourier mode in a Hopf bifurcation or through its first Fourier mode in a pitchfork or drift bifurcation, whilst the remaining Fourier modes appear to create only secondary bifurcations. Pitchfork bifurcations result in travelling spots, and we derive criteria for the criticality of these bifurcations. Our main finding is that supercritical drift bifurcations, leading to stable travelling spots, arise in this model, which does not seem possible for its two-component version.

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An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

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Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

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This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.