Vapor-liquid equilibriums: 2,3-dimethylbutane-methanol and 2,3-dimethylbutane-methanol-chloroform systems

Kirby, C. E.

doi:10.1021/je60044a017

Cited by 13 publications

(2 citation statements)

References 3 publications

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“…Generally experimental measure errors reported in different publications are around 0.06 K for the bubble temperature ( T b ) and 0.1 % for the composition ( X ) 23,24. These are the measure errors made within the same laboratory; they are smaller than the errors of the same measurement made by different labs, which could be as high as 0.5 K and 1 %, respectively 25,26. In some cases due to imprecise control of atmospheric pressure and different approximation methods employed in each laboratory, the average error for T b of pure compounds may reach 12–18 K 27…”

Section: Methodsmentioning

confidence: 93%

QSPR Approach to Predict Nonadditive Properties of Mixtures. Application to Bubble Point Temperatures of Binary Mixtures of Liquids

Oprisiu¹,

Varlamova²,

Muratov³

et al. 2012

Molecular Informatics

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This paper is devoted to the development of methodology for QSPR modeling of mixtures and its application to vapor/liquid equilibrium diagrams for bubble point temperatures of binary liquid mixtures. Two types of special mixture descriptors based on SiRMS and ISIDA approaches were developed. SiRMS-based fragment descriptors involve atoms belonging to both components of the mixture, whereas the ISIDA fragments belong only to one of these components. The models were built on the data set containing the phase diagrams for 167 mixtures represented by different combinations of 67 pure liquids. Consensus models were developed using nonlinear Support Vector Machine (SVM), Associative Neural Networks (ASNN), and Random Forest (RF) approaches. For SVM and ASNN calculations, the ISIDA fragment descriptors were used, whereas Simplex descriptors were employed in RF models. The models have been validated using three different protocols: "Points out", "Mixtures out" and "Compounds out", based on the specific rules to form training/test sets in each fold of cross-validation. A final validation of the models has been performed on an additional set of 94 mixtures represented by combinations of novel 34 compounds and modeling set chemicals with each other. The root mean squared error of predictions for new mixtures of already known liquids does not exceed 5.7 K, which outperforms COSMO-RS models. Developed QSAR methodology can be applied to the modeling of any nonadditive property of binary mixtures (antiviral activities, drug formulation, etc.).

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Section: Methodsmentioning

confidence: 93%

QSPR Approach to Predict Nonadditive Properties of Mixtures. Application to Bubble Point Temperatures of Binary Mixtures of Liquids

Oprisiu¹,

Varlamova²,

Muratov³

et al. 2012

Molecular Informatics

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“…For 2,3-dimethylbutane (1) + methanol (2), the NRTL equation yielded the lowest mean deviations between the experimental and calculated temperatures, 0.08 K and vapor compositions, 0.004. The NRTL parameters for this system are found to be The data for the system 2,3-dimethylbutane (1) + ethanol (2) were best correlated using the Wilson equation with parameters ,2 -,, = 619.630 J mol"1 2 -22 = 1648.854 J mol"1 and an absolute average deviation of 0.006 In mole fraction and of 0.09 K In temperature.…”

Section: Resultsmentioning

confidence: 93%

Vapor-liquid equilibria of 2,3-dimethylbutane + methanol or ethanol at 101.3 kPa

Hiaki¹,

Yamato²,

Kojima³

1992

J. Chem. Eng. Data

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Vapor‐liquid equilibrium: Part II. Correlations from P‐x data for 15 systems

1973

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SCOPEThe apparatus described by Gibbs and Van Ness (1972) has been used systematically to measure solution vapor pressures as a function of liquid composition at 3OoC for 15 binary systems in vapor-liquid equilibrium (VLE). Data reduction by the method described in the preceding paper for P-x data yields correlating equations for the excess Gibbs free energy and the activity coefficients, from which the P-x-y relationship at 3OoC may be calculated. The systems studied are CC&, CHCl3, and CH2C12, each with tetrahydrofuran and with furan; tetrahydrofuran with furan; CH2C12 with methyl acetate, with acetone, and with l,4-dioxane; CHC13 with 1,4-dioxane; pyridine with acetone, with CHC13, and with CH2C12; and n-pentanol with n-hexane. Heat-of-mixing data, which are available in the literature for most of the systems reported, allow extension of these results to other conditions. CONCLUSIONS A N D SIGNIFICANCEThe rapidity with which P-x data may be taken commends the use of such data as the basis for formulation of VLE relationships for binary systems. These are useful in themselves, and they serve also in predictive schemes for multicomponent systems, for which experimental determination is much more tedious.Routine methods of data reduction are available, as reviewed in the preceding paper, and the reliability of the method depends solely on the reliability of the P-x data.Gibbs and Van Ness (1972) demonstrated for the ethanoln-heptane system agreement between results obtained with the present apparatus and data from the literature based on measurements with an equilibrium still. The results presented here are for systems representing a wide range of behavior, from large positive to large negative deviations from ideality.The experimental apparatus used in this work is fully described by Gibbs and Van Ness ( 1972). Liquid solutions of known composition are prepared in a thermostated test cell by volumetric metering of degassed liquids from accurate piston-injectors. Direct measurement of pressure in the cell provides for the solution vapor pressure. The raw data' therefore consist of pairs of values for pressure and liquid mole fraction at constant temperature and cover the full composition range from x1 = 0 to x1 = 1.As indicated by the discussion of P-x data in the preceding paper, the raw data are fit by the least-squares spline-fit procedure of Klaus and Van Ness (1967), and this provides the input for the numerical procedure of Mixon et al. (1965) which yields the g = GE/RT versus x1 relationship in accord with Equation (9b) of the preceding paper. The resulting numerical values of g/xlx2 or of ln(yl/yz) are then fit with respect to x1 by an appro-

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Vapor-liquid equilibriums: 2,3-dimethylbutane-methanol and 2,3-dimethylbutane-methanol-chloroform systems

Cited by 13 publications

References 3 publications

QSPR Approach to Predict Nonadditive Properties of Mixtures. Application to Bubble Point Temperatures of Binary Mixtures of Liquids

QSPR Approach to Predict Nonadditive Properties of Mixtures. Application to Bubble Point Temperatures of Binary Mixtures of Liquids

Vapor-liquid equilibria of 2,3-dimethylbutane + methanol or ethanol at 101.3 kPa

Vapor‐liquid equilibrium: Part II. Correlations from P‐x data for 15 systems

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