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Henry's Law Constants

www.henrys-law.org

Rolf Sander

NEW: Version 5.0.0 has been published in October 2023

Atmospheric Chemistry Division

Max-Planck Institute for Chemistry
Mainz, Germany

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Henry's Law Constants

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References

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When referring to the compilation of Henry's Law Constants, please cite this publication:

R. Sander: Compilation of Henry's law constants (version 5.0.0) for water as solvent, Atmos. Chem. Phys., 23, 10901-12440 (2023), doi:10.5194/acp-23-10901-2023

The publication from 2023 replaces that from 2015, which is now obsolete. Please do not cite the old paper anymore.

Henry's Law Constants → Organic species with oxygen (O) → Esters (RCOOR) → methyl pentanoate

FORMULA:C4H9COOCH3
TRIVIAL NAME: methyl valerate
CAS RN:624-24-8
STRUCTURE
(FROM NIST):
InChIKey:HNBDRPTVWVGKBR-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
3.0×10−2 6100 Plyasunov et al. (2004) L
3.1×10−2 Buttery et al. (1969) M
9.7×10−1 5000 Djerki and Laub (1988) V
6200 Della Gatta et al. (1981) T
3.9×10−2 Keshavarz et al. (2022) Q
2.4×10−1 Duchowicz et al. (2020) Q 300)
2.9×10−2 Li et al. (2014) Q 242)
3.1×10−2 Raventos-Duran et al. (2010) Q 244) 272)
2.0×10−2 Raventos-Duran et al. (2010) Q 245)
2.5×10−2 Raventos-Duran et al. (2010) Q 246)
2.2×10−2 Hilal et al. (2008) Q
3.6×10−2 Modarresi et al. (2007) Q 68)
3.1×10−2 English and Carroll (2001) Q 231) 232)
3.8×10−2 Katritzky et al. (1998) Q
2.6×10−2 Suzuki et al. (1992) Q 233)
2.5×10−2 Nirmalakhandan and Speece (1988) Q
3.1×10−2 Duchowicz et al. (2020) ? 21) 186)
3.1×10−2 Abraham et al. (1990) ?

Data

The first column contains Henry's law solubility constant Hscp at the reference temperature of 298.15 K.
The second column contains the temperature dependence d ln Hs cp / d (1/T), also at the reference temperature.

References

  • Abraham, M. H., Whiting, G. S., Fuchs, R., & Chambers, E. J.: Thermodynamics of solute transfer from water to hexadecane, J. Chem. Soc. Perkin Trans. 2, pp. 291–300, doi:10.1039/P29900000291 (1990).
  • Buttery, R. G., Ling, L. C., & Guadagni, D. G.: Volatilities of aldehydes, ketones, and esters in dilute water solutions, J. Agric. Food Chem., 17, 385–389, doi:10.1021/JF60162A025 (1969).
  • Della Gatta, G., Stradella, L., & Venturello, P.: Enthalpies of solvation in cyclohexane and in water for homologous aliphatic ketones and esters, J. Solution Chem., 10, 209–220, doi:10.1007/BF00653098 (1981).
  • Djerki, R. A. & Laub, R. J.: Solute retention in column liquid chromatography. X. Determination of solute infinite-dilution activity coefficients in methanol, water, and their mixtures, by combined gas-liquid and liquid-liquid chromatography, J. Liq. Chromatogr., 11, 585–612, doi:10.1080/01483918808068333 (1988).
  • Duchowicz, P. R., Aranda, J. F., Bacelo, D. E., & Fioressi, S. E.: QSPR study of the Henry’s law constant for heterogeneous compounds, Chem. Eng. Res. Des., 154, 115–121, doi:10.1016/J.CHERD.2019.12.009 (2020).
  • English, N. J. & Carroll, D. G.: Prediction of Henry’s law constants by a quantitative structure property relationship and neural networks, J. Chem. Inf. Comput. Sci., 41, 1150–1161, doi:10.1021/CI010361D (2001).
  • Hilal, S. H., Ayyampalayam, S. N., & Carreira, L. A.: Air-liquid partition coefficient for a diverse set of organic compounds: Henry’s law constant in water and hexadecane, Environ. Sci. Technol., 42, 9231–9236, doi:10.1021/ES8005783 (2008).
  • Katritzky, A. R., Wang, Y., Sild, S., Tamm, T., & Karelson, M.: QSPR studies on vapor pressure, aqueous solubility, and the prediction of water-air partition coefficients, J. Chem. Inf. Comput. Sci., 38, 720–725, doi:10.1021/CI980022T (1998).
  • Keshavarz, M. H., Rezaei, M., & Hosseini, S. H.: A simple approach for prediction of Henry’s law constant of pesticides, solvents, aromatic hydrocarbons, and persistent pollutants without using complex computer codes and descriptors, Process Saf. Environ. Prot., 162, 867–877, doi:10.1016/J.PSEP.2022.04.045 (2022).
  • Li, H., Wang, X., Yi, T., Xu, Z., & Liu, X.: Prediction of Henry’s law constants for organic compounds using multilayer feedforward neural networks based on linear salvation energy relationship, J. Chem. Pharm. Res., 6, 1557–1564 (2014).
  • Modarresi, H., Modarress, H., & Dearden, J. C.: QSPR model of Henry’s law constant for a diverse set of organic chemicals based on genetic algorithm-radial basis function network approach, Chemosphere, 66, 2067–2076, doi:10.1016/J.CHEMOSPHERE.2006.09.049 (2007).
  • Nirmalakhandan, N. N. & Speece, R. E.: QSAR model for predicting Henry’s constant, Environ. Sci. Technol., 22, 1349–1357, doi:10.1021/ES00176A016 (1988).
  • Plyasunov, A. V., Plyasunova, N. V., & Shock, E. L.: Group contribution values for the thermodynamic functions of hydration of aliphatic esters at 298.15 K, 0.1 MPa, J. Chem. Eng. Data, 49, 1152–1167, doi:10.1021/JE049850A (2004).
  • Raventos-Duran, T., Camredon, M., Valorso, R., Mouchel-Vallon, C., & Aumont, B.: Structure-activity relationships to estimate the effective Henry’s law constants of organics of atmospheric interest, Atmos. Chem. Phys., 10, 7643–7654, doi:10.5194/ACP-10-7643-2010 (2010).
  • Suzuki, T., Ohtaguchi, K., & Koide, K.: Application of principal components analysis to calculate Henry’s constant from molecular structure, Comput. Chem., 16, 41–52, doi:10.1016/0097-8485(92)85007-L (1992).

Type

Table entries are sorted according to reliability of the data, listing the most reliable type first: L) literature review, M) measured, V) VP/AS = vapor pressure/aqueous solubility, R) recalculation, T) thermodynamical calculation, X) original paper not available, C) citation, Q) QSPR, E) estimate, ?) unknown, W) wrong. See Section 3.1 of Sander (2023) for further details.

Notes

21) Several references are given in the list of Henry's law constants but not assigned to specific species.
68) Modarresi et al. (2007) use different descriptors for their calculations. They conclude that a genetic algorithm/radial basis function network (GA/RBFN) is the best QSPR model. Only these results are shown here.
186) Experimental value, extracted from HENRYWIN.
231) English and Carroll (2001) provide several calculations. Here, the preferred value with explicit inclusion of hydrogen bonding parameters from a neural network is shown.
232) Value from the training dataset.
233) Calculated with a principal component analysis (PCA); see Suzuki et al. (1992) for details.
242) Temperature is not specified.
244) Calculated using the GROMHE model.
245) Calculated using the SPARC approach.
246) Calculated using the HENRYWIN method.
272) Value from the validation dataset.
300) Value from the test set for true external validation.

The numbers of the notes are the same as in Sander (2023). References cited in the notes can be found here.

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