Revision of MOSCED Parameters and Extension to Solid Solubility Calculations

Lazzaroni, Michael J.; Bush, David; Eckert, Charles A.; Frank, Timothy C.; Gupta, and Sumnesh; Olson, James D.

doi:10.1021/ie049122g

Cited by 80 publications

(192 citation statements)

References 54 publications

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“…In this work, the IDAC database made available in a previous work (Gerber and Soares, 2010) was expanded with data points from Thomas et al (1982), Dallas and Carr (1994), Castells et al (2000) and Lazzaroni et al (2005). As mentioned previously, only substances known to not form hydrogen bonds were considered.…”

Section: Resultsmentioning

confidence: 99%

Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

Gerber

Soares

2013

Braz. J. Chem. Eng.

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-Currently, the most successful predictive models for activity coefficients are those based on functional groups such as UNIFAC. In contrast, these models require a large amount of experimental data for the determination of their parameter matrix. A more recent alternative is the models based on COSMO, for which only a small set of universal parameters must be calibrated. In this work, a recalibrated COSMO-SAC model was compared with the UNIFAC (Do) model employing experimental infinite dilution activity coefficient data for 2236 non-hydrogen-bonding binary mixtures at different temperatures. As expected, UNIFAC (Do) presented better overall performance, with a mean absolute error of 0.12 ln-units against 0.22 for our COSMO-SAC implementation. However, in cases involving molecules with several functional groups or when functional groups appear in an unusual way, the deviation for UNIFAC was 0.44 as opposed to 0.20 for COSMO-SAC. These results show that COSMO-SAC provides more reliable predictions for multifunctional or more complex molecules, reaffirming its future prospects.

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Section: Resultsmentioning

confidence: 99%

Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

Gerber

Soares

2013

Braz. J. Chem. Eng.

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“…where y i and x i are the vapour-phase mole fraction and the liquid-phase mole fraction respectively of the ith species, f i is the fugacity coefficient in the mixture of the ith species, p is the total pressure, g i is the liquidphase activity coefficient of the ith species and p sat,i is the vapour pressure of the ith species at 310.95 K. In the model employed by the present authors, the liquid-phase activity coefficients g i of each species are calculated via the Wilson equation using the activity coefficients at infinite dilution for each binary pair obtained from the revised modified separation of cohesive energy density (MOSCED) model of Lazzaroni et al 33 The vapour-phase fugacity coefficients f i for each species are calculated from the virial equation of state where the second virial coefficient of each species within the mixture is calculated using the correlation described by Smith et al 34 The interaction parameters for each binary pair are estimated from pure component critical data using the correlation given by Chueh and Prausnitz; 35 the exception to this is for alkanealcohol systems for which values of 0.15 are assigned following the work by Tsonopoulos et al 36 The model was well validated against literature data for a range of gasoline and gasoline-oxygenate blends (see Appendix 6 for further details of the numerical model and examples of the validation results).…”

Section: Vapour Pressure and Distillation Characteristics: Simulationmentioning

confidence: 99%

Iso-stoichiometric fuel blends: characterisation of physicochemical properties for mixtures of gasoline, ethanol, methanol and water

Pearson

Turner

Bell

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

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When appropriately sourced, bioethanol and biodiesel fuels provide an opportunity for nations to increase their energy independence or to reduce greenhouse gas emissions by supplying energy-dense fuels which are miscible with fossilderived gasoline and diesel. These fuels can be used in low concentrations in vehicles with no modifications; in the case of ethanol, only minor changes in the fuel system materials together with a low-cost alcohol sensor are necessary for compatibility with a high concentration. Ethanol provides the beneficial property of having a high research octane number which can be exploited at the high-load operating conditions in modern pressure-charged spark ignition engines. However, the availability of sustainable feedstocks constrains the supply of biofuels, and this limits the level at which they are able to displace fossil fuels. The miscibility of methanol with both ethanol and gasoline enables the penetration of alcohols in the fuel pool to be increased. The present work describes the properties of specific mixtures of gasoline, ethanol and methanol which are blended to be iso-stoichiometric and iso-energetic replacements for mixtures of gasoline and ethanol. A simple analytical approach to the formulation of these ternary blends is described on the basis of the volumetric energy density of the pre-blended components, and a number of further physicochemical properties are characterised, including their stoichiometries, vapour pressures, distillation characteristics and propensities to phase separate. Data on the octane numbers of the blends are reported. The properties of quaternary iso-stoichiometric blends of water, gasoline, ethanol and methanol (the so-called hydrous ternary blends) are also examined.

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“…The MOSCED model (Lazzaroni et al, 2005), generates infinite dilution activity coefficients. In order to obtain a noninfinite dilution activity coefficient, another activity coefficient model is required.…”

Section: Mosced and Unifac Modelsmentioning

confidence: 99%

Evaluation of the Effect of the Solubility Model on Antisolvent Crystallization Optimization

Widenski

Abbas

Romagnoli

2009

IFAC Proceedings Volumes

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The use of predictive solubility models can be of great use for crystallization modeling, and can decrease the amount of experimental data needed to create a robust crystallization model. In this paper, predictive solubility models such as MOSCED, UNIFAC, NRTL-SAC, and the Jouyban-Acree model are compared against an empirical model for predicted solubility accuracy. The best models are subsequently compared against the empirical model for the antisolvent crystallization of acetaminophen in acetone using water. Two different optimization objective functions are executed for each solubility model to generate corresponding optimal profiles. The effect of these optimal profiles on the predicted crystal properties is evaluated.

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Revision of MOSCED Parameters and Extension to Solid Solubility Calculations

Cited by 80 publications

References 54 publications

Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

Iso-stoichiometric fuel blends: characterisation of physicochemical properties for mixtures of gasoline, ethanol, methanol and water

Evaluation of the Effect of the Solubility Model on Antisolvent Crystallization Optimization

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