995 resultados para Gibbs excess models
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In this work, a study on the role of the long-range term of excess Gibbs energy models in the modeling of aqueous systems containing polymers and salts is presented. Four different approaches on how to account for the presence of polymer in the long-range term were considered, and simulations were conducted considering aqueous solutions of three different salts. The analysis of water activity curves showed that, in all cases, a liquid-phase separation may be introduced by the sole presence of the polymer in the long-range term, regardless of how it is taken into account. The results lead to the conclusion that there is no single exact solution for this problem, and that any kind of approach may introduce inconsistencies.
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The water activity of aqueous solutions of EO-PO block copolymers of six different molar masses and EO/PO ratios and of maltodextrins of three different molar masses was determined at 298.15 K. The results showed that these aqueous solutions present a negative deviation from Raoult`s law. The Flory-Huggins and UNIFAC excess Gibbs energy models were employed to model the experimental data. While a good agreement was obtained with the Flory-Huggins equation, discrepancies were observed when predicting the experimental behavior with the UNIFAC model. The water activities of ternary systems formed by a synthetic polymer, maltodextrin and water were also measured and used to test the predictive capability of both models.
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Experimental results for the activity of water in aqueous solutions of 10 single, synthetic polyelectrolytes (polysodium acrylate, polysodium methacrylate, polyammonium acrylate, polysodium ethylene sulfonate, and polysodium styrene sulfonate) and sodium chloride at 298.2 K are presented. The experimental work was performed by applying the isopiestic method with sodium chloride as a reference substance. As expected, the activity of water decreases when the concentration of a polyelectrolyte and/or sodium chloride increases. At constant concentration of a polyelectrolyte and sodium chloride, the activity of water depends on the monomer unit and the molecular mass of the polyelectrolyte. The new data are to be used in future work to develop and test models for the Gibbs excess energy of aqueous solutions of polyelectrolytes.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.
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An exact treatment of adsorption from a one-dimensional lattice gas is used to eliminate and correct a well-known inconsistency in the Brunauer–Emmett–Teller (B.E.T.) equation—namely, Gibbs excess adsorption is not taken into account and the Gibbs integral diverges at the transition point. However, neither model should be considered realistic for experimental adsorption systems.
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Pitzer`s equation for the excess Gibbs energy of aqueous solutions of low-molecular electrolytes is extended to aqueous solutions of polyelectrolytes. The model retains the original form of Pitzer`s model (combining a long-range term, based on the Debye-Huckel equation, with a short-range term similar to the virial equation where the second osmotic virial coefficient depends on the ionic strength). The extension consists of two parts: at first, it is assumed that a constant fraction of the monomer units of the polyelectrolyte is dissociated, i.e., that fraction does not depend on the concentration of the polyelectrolyte, and at second, a modified expression for the ionic strength (wherein each charged monomer group is taken into account individually) is introduced. This modification is to account for the presence of charged polyelectrolyte chains, which cannot be regarded as punctual charges. The resulting equation was used to correlate osmotic coefficient data of aqueous solutions of a single polyelectrolyte as well as of binary mixtures of a single polyelectrolyte and a salt with low-molecular weight. It was additionally applied to correlate liquid-liquid equilibrium data of some aqueous two-phase systems that might form when a polyelectrolyte and another hydrophilic but neutral polymer are simultaneously dissolved in water. A good agreement between the experimental data and the correlation result is observed for all investigated systems. (c) 2008 Elsevier B.V. All rights reserved.
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A recent method for phase equilibria, the AGAPE method, has been used to predict activity coefficients and excess Gibbs energy for binary mixtures with good accuracy. The theory, based on a generalised London potential (GLP), accounts for intermolecular attractive forces. Unlike existing prediction methods, for example UNIFAC, the AGAPE method uses only information derived from accessible experimental data and molecular information for pure components. Presently, the AGAPE method has some limitations, namely that the mixtures must consist of small, non-polar compounds with no hydrogen bonding, at low moderate pressures and at conditions below the critical conditions of the components. Distinction between vapour-liquid equilibria and gas-liquid solubility is rather arbitrary and it seems reasonable to extend these ideas to solubility. The AGAPE model uses a molecular lattice-based mixing rule. By judicious use of computer programs a methodology was created to examine a body of experimental gas-liquid solubility data for gases such as carbon dioxide, propane, n-butane or sulphur hexafluoride which all have critical temperatures a little above 298 K dissolved in benzene, cyclo-hexane and methanol. Within this methodology the value of the GLP as an ab initio combining rule for such solutes in very dilute solutions in a variety of liquids has been tested. Using the GLP as a mixing rule involves the computation of rotationally averaged interactions between the constituent atoms, and new calculations have had to be made to discover the magnitude of the unlike pair interactions. These numbers have been seen as significant in their own right in the context of the behaviour of infinitely-dilute solutions. A method for extending this treatment to "permanent" gases has also been developed. The findings from the GLP method and from the more general AGAPE approach have been examined in the context of other models for gas-liquid solubility, both "classical" and contemporary, in particular those derived from equations-of-state methods and from reference solvent methods.
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In this work, we experimentally showed that the spontaneous segregation of MgO as surface excess in MgO doped SnO(2) nanoparticles plays an important role in the system`s energetics and stability. Using Xray fluorescence in specially treated samples, we quantitatively determined the fraction of MgO forming surface excess when doping SnO(2) with several different concentrations and established a relationship between this amount and the surface energy of the nanoparticles using the Gibbs approach. We concluded that the amount of Mg ions on the surface was directly related to the nanoparticles total free energy, in a sense that the dopant will always spontaneously distribute itself to minimize it if enough diffusion is provided. Because we were dealing with nanosized particles, the effect of MgO on the surface was particularly important and has a direct effect on the equilibrium particle size (nanoparticle stability), such that the lower the surface energy is, the smaller the particle sizes are, evidencing and quantifying the thermodynamic basis of using additives to control SnO(2) nanoparticles stability. (C) 2010 Elsevier B.V. All rights reserved.
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Purpose: The aim of this study was to investigate the impact of acute PaCO(2) temporal variation on the standard base excess (SBE) value in critically ill patients. Methods: A total of 265 patients were prospectively observed; 158 were allocated to the modeling group, and 107 were allocated to the validation group. Two models were developed in the modeling group (one including and one excluding PaCO(2) as a variable determinant of SBE), and both were tested in the validation group. Results: In the modeling group, the mathematical model including SIDai, SIG, L-lactate, albumin, phosphate, and PaCO(2) had a predictive superiority in comparison with the model without PaCO(2) (R(2) = 0.978 and 0.916, respectively). In the validation group, the results were confirmed with significant F change statistics (R(2) change = 0.059, P < .001) between the model with and without PaCO(2). A high correlation (R = 0.99, P < .001) and agreement (bias = -0.25 mEq/L, limits of agreement 95% = -0.72 to 0.22 mEq/L) were found between the model-predicted SBE value and the SBE calculated using the Van Slyke equation. Conclusions: Acute PaCO(2), temporal variation is related to SBE changes in critically ill patients. (C) 2009 Elsevier Inc. All rights reserved.
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We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.
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Entry regulations affecting professional services such as pharmacies are common practice in many European countries. We assess the impact of entry regulations on profits estimating a structural model of entry using the information provided by a policy experiment. We use the case of different regional policies governing the opening of new pharmacies in Spain to show that structural models of entry ought to be estimated with data from policy experiments to pin down how entry regulations change payoffs functions of the incumbents. Contrary to the public interest rationales, regulations are not boosting only small town pharmacies payoffs nor increasing all pharmacies payoffs alike. The gains from regulations are very unevenly distributed,suggesting that private interests are shaping the current mix of entry and markup regulations.
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One of the cornerstone of financial anomalies is that there exists money making opportunities. Shiller’s excess volatility theory is re-investigated from the perspective of a trading strategy where the present value is computed using a series of simple econometric models to forecast the present value. The results show that the excess volatility may not be exploited given the data available until time t. However, when learning is introduced empirically, the simple trading strategy may offer profits, but which are likely to disappear once transaction costs are considered.
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This paper investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in bond yields of seven advanced economies is due to global co-movement, which is mainly attributed to shocks to non-fundamentals. Global fundamentals, especially global inflation, affect yields through a ‘policy channel’ and a ‘risk compensation channel’, but the effects through two channels are offset. This evidence explains the unsatisfactory performance of fundamentals-driven term structure models. Our approach delineates asymmetric spillovers in global bond markets connected to diverging monetary policies. The proposed model is robust as identified factors has significant explanatory power of excess returns. The finding that global inflation uncertainty is useful in explaining realized excess returns does not rule out regime changing as a source of non-fundamental fluctuations.