Prediction of the enthalpy of vaporization by the group contribution method

Basařová, Pavlína; Svoboda, V.

doi:10.1016/0378-3812(94)02599-v

Cited by 47 publications

(15 citation statements)

References 7 publications

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“…Finally, for vapor pressure data measured at temperatures different from 20 °C (but within the ambient temperature range) one can easily derive the respective equation by combining eq 7 with eq 3 (where T 1 is 25 °C and T 2 is the target temperature) and assuming a constant Δ vap H i . For vapor pressure data at 20 °C this yields It must be noted that a number of group-contribution methods have been described for the estimation of Δ vap H i ( − ). These methods yield a similar or even better accuracy as eq 7 and have the advantage of predicting the temperature dependence of Δ vap H i .…”

Section: Resultsmentioning

confidence: 99%

Empirical Prediction of Heats of Vaporization and Heats of Adsorption of Organic Compounds

Goss

Schwarzenbach

1999

Environ. Sci. Technol.

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Partitioning between the gas phase and ambient condensed phases is an important process in determining the transport and fate of organic chemicals in the atmosphere as well as in other environmental compartments exhibiting a vadose zone (e.g., soils). In general, partition processes including the gas phase are strongly temperature dependent and the respective enthalpies of transfer need to be known. Unfortunately, such data are often not available. In this paper, we evaluate the possibilities of estimating both the enthalpies of vaporization from the pure liquid and the enthalpies of gas/surface adsorption of organic compounds from either their (subcooled) liquid vapor pressure or their equilibrium adsorption constant at a particular temperature. Such an approach becomes possible when linear relationships between the enthalpy and entropy, and hence between the enthalpy and the logarithm of the partition constant, exist. Using literature data reported for almost 200 compounds covering a wide range of compound classes we have derived an empirical relationship that can be used to estimate the enthalpy of vaporization, Δvap H i, of a given compound i from its saturated liquid vapor pressure, p iL*, at 25 °C: Δvap H i (kJ/mol) = −3.82(±0.03) ln p iL* (Pa, 25 °C) + 70.0(±0.2); n = 195; r 2 = 0.99. An analogous equation is given for the estimation of the enthalpy of adsorption of organic vapors to mineral surfaces. The application of this equation to other surfaces including liquid and solid organic phases as well as the liquid water surface is discussed. The equations presented are useful practical tools for approximating the temperature dependence of liquid vapor pressure and of vapor/surface adsorption constants of organic chemicals in the ambient temperature range.

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Section: Resultsmentioning

confidence: 99%

Empirical Prediction of Heats of Vaporization and Heats of Adsorption of Organic Compounds

Goss

Schwarzenbach

1999

Environ. Sci. Technol.

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“…56 Table 21 shows that the heat of vaporization predictions of the five samples differ from those based on the typical composition by less than 2.5%. (Table 16) Ceriani et al 55 Pitzer et al 57 Basařová …”

Section: 3d Effect Of Oil Composition On Heat Of Vaporization Predmentioning

confidence: 97%

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

Liu

Tovar

et al. 2011

Ind. Eng. Chem. Res.

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To optimize biodiesel manufacturing, many reported studies have built simulation models to quantify the relationship between operating conditions and process performance. For mass and energy balance simulations, it is essential to know the four fundamental thermophysical properties of the feed oil: liquid density (ρ L ), vapor pressure (P vap ), liquid heat capacity (C p L ), and heat of vaporization (ΔH vap ). Additionally, to characterize the fuel qualities, it is critical to develop quantitative correlations to predict three biodiesel properties, namely, viscosity, cetane number, and flash point. Also, to ensure the operability of biodiesel in cold weather, one needs to quantitatively predict three low-temperature flow properties: cloud point (CP), pour point (PP), and cold filter plugging point (CFPP). This article presents the results from a comprehensive evaluation of the methods for predicting these four essential feed oil properties and six key biodiesel fuel properties. We compare the predictions to reported experimental data and recommend the appropriate prediction methods for each property based on accuracy, consistency, and generality. Of particular significance are (1) our presentation of simple and accurate methods for predicting the six key fuel properties based on the number of carbon atoms and the number of double bonds or the composition of total unsaturated fatty acid methyl esters (FAMEs) and (2) our posting of the Excel spreadsheets for implementing all of the evaluated accurate prediction methods on our group website (www.design.che.vt.edu) for the reader to download without charge.ii Acknowledgement

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“…This dimensionality reduction is an inherent part of the regression scheme and is sometimes overlooked when comparing with other modelling approaches. The PLSR model reported here uses 12 latent variables and the dimensionality is therefore also 12, which is considerably less than for any of the group contribution methods [7][8][9][10][11][12][13].…”

Section: Model Complexitymentioning

confidence: 99%

“…[6]. The enthalpy of vaporisation has been modelled from the molecular structure using various approaches; these include both group contribution methods [7][8][9][10][11][12][13] as well as combinations of physical properties and descriptors of the molecular structure [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A general structure-property relationship to predict the enthalpy of vaporisation at ambient temperatures

Öberg¹

2007

SAR and QSAR in Environmental Research

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The vapour pressure is the most important property of an anthropogenic organic compound in determining its partitioning between the atmosphere and the other environmental media. The enthalpy of vaporisation quantifies the temperature dependence of the vapour pressure and its value around 298 K is needed for environmental modelling. The enthalpy of vaporisation can be determined by different experimental methods, but estimation methods are needed to extend the current database and several approaches are available from the literature. However, these methods have limitations, such as a need for other experimental results as input data, a limited applicability domain, a lack of domain definition, and a lack of predictive validation. Here we have attempted to develop a quantitative structure-property relationship (QSPR) that has general applicability and is thoroughly validated. Enthalpies of vaporisation at 298 K were collected from the literature for 1835 pure compounds. The three-dimensional (3D) structures were optimised and each compound was described by a set of computationally derived descriptors. The compounds were randomly assigned into a calibration set and a prediction set. Partial least squares regression (PLSR) was used to estimate a low-dimensional QSPR model with 12 latent variables. The predictive performance of this model, within the domain of application, was estimated at n=560, q2Ext=0.968 and s=0.028 (log transformed values). The QSPR model was subsequently applied to a database of 100,000+ structures, after a similar 3D optimisation and descriptor generation. Reliable predictions can be reported for compounds within the previously defined applicability domain.

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Prediction of the enthalpy of vaporization by the group contribution method

Cited by 47 publications

References 7 publications

Empirical Prediction of Heats of Vaporization and Heats of Adsorption of Organic Compounds

Empirical Prediction of Heats of Vaporization and Heats of Adsorption of Organic Compounds

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

A general structure-property relationship to predict the enthalpy of vaporisation at ambient temperatures

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