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Henry's Law Constants

www.henrys-law.org

Rolf Sander

Atmospheric Chemistry Division

Max-Planck Institute for Chemistry
Mainz, Germany

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Henry's Law Constants

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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 Please do not cite the old paper anymore.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 → Hydrocarbons (C, H) → Alkanes → 4-ethyl-3,3-dimethylhexane

FORMULA:C10H22
CAS RN:52897-05-9
STRUCTURE
(FROM NIST):
InChIKey:ZRTXVJYJVBTXHE-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
8.5×10−7 Yaws (2003) X 238)
2.1×10−6 Gharagheizi et al. (2012) Q
1.1×10−6 Gharagheizi et al. (2010) Q 247)
1.9×10−6 Hilal et al. (2008) Q
1.3×10−6 Modarresi et al. (2005) Q 248)
7.3×10−7 Yao et al. (2002) Q 230)
8.6×10−7 Yaws (1999) ? 21)
1.3×10−6 Yaws and Yang (1992) ? 21)

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

  • Gharagheizi, F., Abbasi, R., & Tirandazi, B.: Prediction of Henry’s law constant of organic compounds in water from a new group-contribution-based model, Ind. Eng. Chem. Res., 49, 10 149–10 152, doi:10.1021/IE101532E (2010).
  • Gharagheizi, F., Eslamimanesh, A., Mohammadi, A. H., & Richon, D.: Empirical method for estimation of Henry’s law constant of non-electrolyte organic compounds in water, J. Chem. Thermodyn., 47, 295–299, doi:10.1016/J.JCT.2011.11.015 (2012).
  • 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).
  • Modarresi, H., Modarress, H., & Dearden, J. C.: Henry’s law constant of hydrocarbons in air–water system: The cavity ovality effect on the non-electrostatic contribution term of solvation free energy, SAR QSAR Environ. Res., 16, 461–482, doi:10.1080/10659360500319869 (2005).
  • Yao, X., aand X. Zhang, M. L., Hu, Z., & Fan, B.: Radial basis function network-based quantitative structure-property relationship for the prediction of Henry’s law constant, Anal. Chim. Acta, 462, 101–117, doi:10.1016/S0003-2670(02)00273-8 (2002).
  • Yaws, C. L.: Chemical Properties Handbook, McGraw-Hill, Inc., ISBN 0070734011 (1999).
  • Yaws, C. L.: Yaws’ Handbook of Thermodynamic and Physical Properties of Chemical Compounds, Knovel: Norwich, NY, USA, ISBN 1591244447 (2003).
  • Yaws, C. L. & Yang, H.-C.: Henry’s law constant for compound in water, in: Thermodynamic and Physical Property Data, edited by Yaws, C. L., pp. 181–206, Gulf Publishing Company, Houston, TX, ISBN 0884150313 (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.
230) Yao et al. (2002) compared two QSPR methods and found that radial basis function networks (RBFNs) are better than multiple linear regression. In their paper, they provide neither a definition nor the unit of their Henry's law constants. Comparing the values with those that they cite from Yaws (1999), it is assumed that they use the variant Hvpx and the unit atm.
238) Value given here as quoted by Gharagheizi et al. (2010).
247) Calculated using a combination of a group contribution method and neural networks.
248) Modarresi et al. (2005) use different descriptors for the QSPR models. They conclude that their "COSA" method and the artificial neural network (ANN) are best. However, as COSA is not ideal for hydrocarbons with low solubility, only results obtained with ANN are shown here.

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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