990 resultados para Particle physics


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Synthesis of MgC2O4⋅2H2O nano particles was carried out by thermal double decomposition of solutions of oxalic acid dihydrate (C2H2O4⋅2H2O) and Mg(OAc)2⋅4H2O employing CATA-2R microwave reactor. Structural elucidation was carried out by employing X-ray diffraction (XRD), particle size and shape were studied by transmission electron microscopy (TEM) and nature of bonding was investigated by optical absorption and near-infrared (NIR) spectral studies. The powder resulting from this method is pure and possesses distorted rhombic octahedral structure. The synthesized nano rod is 80 nm in diameter and 549 nm in length.

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Red Blood Cells (RBCs) exhibit different types of motions and different deformed shapes, when they move through capillaries. RBCs can travel through capillaries having smaller diameters than RBCs’ diameter, due to the capacity of high deformability of the viscoelastic RBC membrane. The motion and the steady state shape of the RBCs depend on many factors, such as the geometrical parameters of the microvessel through which blood flows, the RBC membrane bending stiffness and the flow velocity. In this study, the effect of the RBC’s membrane stiffness on the deformation of a single RBC in a stenosed capillary is comprehensively examined. Smoothed Particle Hydrodynamics (SPH) in combination with the two-dimensional spring network membrane model is used to investigate the motion and the deformation property of the RBC. The simulation results demonstrate that the membrane bending stiffness of the RBC has a significant impact on the RBCs’ deformability.

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In particle-strengthened metallic alloys, fatigue damage incubates at inclusion particles near the surface or at the change of geometries. Micromechanical simulation of inclusions such that the fatigue damage incubation mechanisms can be categorized. As micro-plasticity gradient field around different inclusions is different, a novel concept for nonlocal evaluation of micro-plasticity intensity is introduced. The effects of void aspects ration and spatial distributions are quantified for fatigue incubation life in the high-cycle fatigue regime. At last, these effects are integrated based on the statistical facts of inclusions to predict the fatigue life of structural components.

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Background The size of the carrier influences the aerosolization of drug from a dry powder inhaler (DPI) formulation. Currently, lactose monohydrate particles in a variety of sizes are preferably used in carrier based DPI formulations of various drugs; however, contradictory reports exist regarding the effect of the size of the carrier on the dispersion of drug. In this study we examined the influence of the intrinsic particle size of the polymeric carrier on the aerosolization of a model drug salbutamol sulphate (SS). Methods Four different sizes (20–150 lm) of polymer carriers were fabricated using solvent evaporation technique and the dispersion of SS particles from these carriers was measured by a Twin Stage Impinger (TSI). The size and morphological properties of polymer carriers were by laser diffraction and SEM, respectively. Results The FPF from these carriers was found to be increasing from 5.6% to 21.3% with increasing the carrier size. The FPF was found to be greater (21%) with the highest particle size of the carrier (150 lm). Conclusions The aerosolization of drug was dependent on the size of polymer carriers. The smaller size of the carrier resulted in lower FPF which was increased with increasing the carrier size. For a fixed mass of drug particles in a formulation, the mass of drug particles per unit area of carriers is higher in formulations containing the larger carriers, which leads to an increase in the dispersion of drug due to the increased mechanical forces occurred between the carriers and the device walls.

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This study demonstrates a novel technique of preparing drug colloid probes to determine the adhesion force between the drug salbutamol sulphate (SS) and the surfaces of polymer microparticles to be used as carriers for the dispersion of drug particles from a dry powder inhaler (DPI) formulation. Initially model silica probes of approximately 4 μm size, similar to a drug particle used in DPI formulations, were coated with a saturated SS solution with the aid of capillary forces acting between the silica probe and the drug solution. The developed method of ensuring a smooth and uniform layer of SS on the silica probe was validated using X-Ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscopy (SEM). Using the same technique, silica microspheres preattached on the AFM cantilever were coated with SS. The adhesion forces between the silica probe and drug coated silica (drug probe) and polymer surfaces (hydrophilic and hydrophobic) were determined. Our experimental results showed that the technique for preparing the drug probe was robust and can be used to determine the adhesion force between hydrophilic/hydrophobic drug probe and carrier surfaces to gain a better understanding on drug carrier adhesion forces in DPI formulations.

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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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Chinese modal particles feature prominently in Chinese people’s daily use of the language, but their pragmatic and semantic functions are elusive as commonly recognised by Chinese linguists and teachers of Chinese as a foreign language. This book originates from an extensive and intensive empirical study of the Chinese modal particle a (啊), one of the most frequently used modal particles in Mandarin Chinese. In order to capture all the uses and the underlying meanings of the particle, the author transcribed the first 20 episodes, about 20 hours in length, of the popular Chinese TV drama series Kewang ‘Expectations’, which yielded a corpus data of more than 142’000 Chinese characters with a total of 1829 instances of the particle all used in meaningful communicative situations. Within its context of use, every single occurrence of the particle was analysed in terms of its pragmatic and semantic contributions to the hosting utterance. Upon this basis the core meanings were identified which were seen as constituting the modal nature of the particle.

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This project advances the knowledge of rail wear and crack formation due to rail/wheel contact in Australian heavy-haul railway lines. This comprehensive study utilised numerous techniques including: simulation using a twin-disk test-rig, scanning electron microscope particle analysis and finite element modeling for material failure prediction. Through this work, new material failure models have been developed which may be used to predict the lifetime and reliability of materials undergoing severe contact conditions.

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The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

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The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

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This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

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Bagasse stockpile operations have the potential to lead to adverse environmental and social impacts. Dust releases can cause occupational health and safety concerns for factory workers and dust emissions impact on the surrounding community. Preliminary modelling showed that bagasse depithing would likely reduce the environmental risks, particularly dust emissions, associated with large-scale bagasse stockpiling operations. Dust emission properties were measured and used for dispersion modelling with favourable outcomes. Modelling showed a 70% reduction in peak ground level concentrations of PM10 dust (particles with an aerodynamic diameter less than 10 μm) from operations on depithed bagasse stockpiles compared to similar operations on stockpiles of whole bagasse. However, the costs of a depithing operation at a sugar factory were estimated to be approximately $2.1 million in capital expenditure to process 100 000 t/y of bagasse and operating costs were 200 000 p.a. The total capital cost for a 10 000 t/y operation was approximately $1.6 million. The cost of depithing based on a discounted cash flow analysis was $5.50 per tonne of bagasse for the 100 000 t/y scenario. This may make depithing prohibitively expensive in many situations if installed exclusively as a dust control measure.

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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.

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Na-dodecylbenzenesulfate (SDBS), a natural anionic surfactant, has been successfully intercalated into a Ca based LDH host structure during tricalcium aluminate hydration in the presence of SDBS aqueous solution (CaAl-SDBS-LDH). The resulting product was characterized by powder X-ray diffraction (XRD), mid-infrared (MIR) spectroscopy combined with near-infrared (NIR) spectroscopy technique, thermal analysis (TG–DTA) and scan electron microscopy (SEM). The XRD results revealed that the interlayer distance of resultant product was expanded to 30.46 Å. MIR combined with NIR spectra offered an effective method to illustrate this intercalation. The NIR spectra (6000–5500 cm−1) displayed prominent bands to expound SDBS intercalated into hydration product of C3A. And the bands around 8300 cm−1 were assigned to the second overtone of the first fundamental of CH stretching vibrations of SDBS. In addition, thermal analysis showed that the dehydration and dehydroxylation took place at ca. 220 °C and 348 °C, respectively. The SEM results appeared approximately hexagonal platy crystallites morphology for CaAl-SDBS-LDH, with particle size smaller and thinner.

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The ability to understand and predict how thermal, hydrological,mechanical and chemical (THMC) processes interact is fundamental to many research initiatives and industrial applications. We present (1) a new Thermal– Hydrological–Mechanical–Chemical (THMC) coupling formulation, based on non-equilibrium thermodynamics; (2) show how THMC feedback is incorporated in the thermodynamic approach; (3) suggest a unifying thermodynamic framework for multi-scaling; and (4) formulate a new rationale for assessing upper and lower bounds of dissipation for THMC processes. The technique is based on deducing time and length scales suitable for separating processes using a macroscopic finite time thermodynamic approach. We show that if the time and length scales are suitably chosen, the calculation of entropic bounds can be used to describe three different types of material and process uncertainties: geometric uncertainties,stemming from the microstructure; process uncertainty, stemming from the correct derivation of the constitutive behavior; and uncertainties in time evolution, stemming from the path dependence of the time integration of the irreversible entropy production. Although the approach is specifically formulated here for THMC coupling we suggest that it has a much broader applicability. In a general sense it consists of finding the entropic bounds of the dissipation defined by the product of thermodynamic force times thermodynamic flux which in material sciences corresponds to generalized stress and generalized strain rates, respectively.