26 resultados para Casting solvent
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Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used to simultaneously follow the diffusion of model drugs and solvent across polydimethylsiloxane (silicone) membrane. Three model drugs, cyanophenol (CNP), methyl nicotinate (MN) and butyl paraben (BP) were selected to cover a range of lipophilicities. Isostearyl isostearate (ISIS) was chosen as the solvent because its large molecular weight should facilitate observation of whether the drug molecules are able to diffuse through the membrane independently of the solvent. The diffusion of the three drugs and the solvent was successfully described by a Fickian model. The effects of parameters such as the absorption wavelength used to follow diffusion on the calculated diffusion coefficient were investigated. Absorption wavelength which affects the depth of penetration of the infrared radiation into the membrane did not significantly affect the calculated diffusion coefficient over the wavelength range tested. Each of the model drugs was observed to diffuse independently of the solvent across the membrane. The diffusion of a CNP-ISIS hydrogen bonded complex across the membrane was also monitored. The relative diffusion rates of the solute and solvent across the membrane can largely be accounted for by the molecular size of the permeant.
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The uptake and diffusion of solvents across polymer membranes is important in controlled drug delivery, effects on drug uptake into, for example, infusion bags and containers, as well as transport across protective clothing. Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy has been used to monitor the effects of different solvents on the diffusion of a model compound, 4-cyanophenol (CNP) across silicone membrane and on the equilibrium concentration of CNP obtained in the membrane following diffusion. ATR-FTIR spectroscopic imaging of membrane diffusion was used to gain an understanding of when the boundary conditions applied to Fick's second law, used to model the diffusion of permeants across the silicone membrane do not hold. The imaging experiments indicated that when the solvent was not taken up appreciably into the membrane, the presence of discrete solvent pools between the ATR crystal and the silicone membrane can affect the diffusion profile of the permeant. This effect is more significant if the permeant has a high solubility in the solvent. In contrast, solvents that are taken up into the membrane to a greater extent, or those where the solubility of the permeant in the vehicle is relatively low, were found to show a good fit to the diffusion model. As such these systems allow the ATR-FTIR spectroscopic approach to give mechanistic insight into how the particular solvents enhance permeation. The solubility of CNP in the solvent and the uptake of the solvent into the membrane were found to be important influences on the equilibrium concentration of the permeant obtained in the membrane following diffusion. In general, solvents which were taken up to a significant extent into the membrane and which caused the membrane to swell increased the diffusion coefficient of the permeant in the membrane though other factors such as solvent viscosity may also be important.
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Counter-current chromatography (CCC) is a technique that shows a lot of potential for large scale purification. Its usefulness in a "research and development" pharmaceutical environment has been investigated, and the conclusions are shown in this article. The use of CCC requires the development of an appropriate solvent system (a parameter of critical importance), a process which can be tedious. This article presents a novel strategy, combining a statistical approach and fast HPLC to generate a three-dimensional partition coefficient map and rapidly predict an optimal solvent system. This screen is performed in half a day and involves 9 experiments per solvent mixture. Test separations were performed using that screen to ensure the validity of the method.
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Drug dissolution and release characteristics from freeze-dried wafers and solvent-cast films prepared from sodium carboxymethylcellulose (CMC) have been investigated to determine the mechanisms of drug release from the two systems. The formulations were prepared by freeze-drying (wafers) or drying in air (films), the hydrated gel of the polymer containing paracetamol as a model soluble drug. Scanning electron microscopy (SEM) was used to examine differences between the physical structure of the wafers and films. Dissolution studies were performed using an exchange cell and drug release was measured by UV spectroscopy at 242 nm. The effects of drug loading, polymer content and amount of glycerol (films) on the release characteristics of paracetamol were investigated. The release profiles of paracetamol from the wafers and films were also compared. A digital camera was used to observe the times to complete hydration and dissolution of the wafers containing different amounts of CMC and how that impacts on drug release rates. Both formulations showed sustained type drug release that was modelled by the Korsmeyer–Peppas equation. Changes in the concentration of drug and glycerol (films) did not significantly alter the rate of drug release while increasing polymer content significantly decreased the rate of drug release from both formulations. The results show that the rate of paracetamol release was faster from the wafers than the corresponding films due to differences in their physical structures. The wafers which formed a porous network, hydrated faster than the more dense and continuous, (non-porous) sheet-like structure of the films.
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Solvent-cast films from three polymers, carboxymethylcellulose (CMC), sodium alginate (SA), and xanthan gum, were prepared by drying the polymeric gels in air. Three methods, (a) passive hydration, (b) vortex hydration with heating, and (c) cold hydration, were investigated to determine the most effective means of preparing gels for each of the three polymers. Different drying conditions [relative humidity - RH (6-52%) and temperature (3-45 degrees C)] were investigated to determine the effect of drying rate on the films prepared by drying the polymeric gels. The tensile properties of the CMC films were determined by stretching dumbbell-shaped films to breaking point, using a Texture Analyser. Glycerol was used as a plasticizer, and its effects on the drying rate, physical appearance, and tensile properties of the resulting films were investigated. Vortex hydration with heating was the method of choice for preparing gels of SA and CMC, and cold hydration for xanthan gels. Drying rates increased with low glycerol content, high temperature, and low relative humidity. The residual water content of the films increased with increasing glycerol content and high relative humidity and decreased at higher temperatures. Generally, temperature affected the drying rate to a greater extent than relative humidity. Glycerol significantly affected the toughness (increased) and rigidity (decreased) of CMC films. CMC films prepared at 45 degrees C and 6% RH produced suitable films at the fastest rate while films containing equal quantities of glycerol and CMC possessed an ideal balance between flexibility and rigidity.
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Metal casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena – heat conduction and solidification. However, to predict other phenomena, such as porosity formation, requires modelling the interaction of the fluid flow, heat transfer, solidification and the development of stressdeformation in the solidified part of the casting. This paper will describe a modelling framework called PHYSICA[1] which has the capability to stimulate such multiphysical phenomena.
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This paper presents a three dimensional, thermos-mechanical modelling approach to the cooling and solidification phases associated with the shape casting of metals ei. Die, sand and investment casting. Novel vortex-based Finite Volume (FV) methods are described and employed with regard to the small strain, non-linear Computational Solid Mechanics (CSM) capabilities required to model shape casting. The CSM capabilities include the non-linear material phenomena of creep and thermo-elasto-visco-plasticity at high temperatures and thermo-elasto-visco-plasticity at low temperatures and also multi body deformable contact with which can occur between the metal casting of the mould. The vortex-based FV methods, which can be readily applied to unstructured meshes, are included within a comprehensive FV modelling framework, PHYSICA. The additional heat transfer, by conduction and convection, filling, porosity and solidification algorithms existing within PHYSICA for the complete modelling of all shape casting process employ cell-centred FV methods. The termo-mechanical coupling is performed in a staggered incremental fashion, which addresses the possible gap formation between the component and the mould, and is ultimately validated against a variety of shape casting benchmarks.
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A variety of interacting complex phenomena takes place during the casting of metallic components. Here molten metal is poured into a mould cavity where it flows, cools, solidifies and then deforms in its solid state. As the metal cools, thermal gradients will promote thermal convection which will redistribute the heat around the component (usually from feeders or risers) towards the solidification front and mushy zone. Also, as the evolving solid regions of the cast component deform they will form gap at the cast-mould interface. This gap may change the rate of solidification in certain parts the casting, hence affecting the manner in which the cast component solidifies. Interaction between a cast component and its surrounding mould will also govern stress magnitudes in both the cast and mould -these may lead to defects such as cracks. This paper presents a multiphysics modelling approach to this complex process. Emphasis will be placed on the interacting phenomena taking place during the process and the modelling strategy used. Comparisons with plant data are also be given.