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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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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 Please do not cite the old paper anymore.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 nitrogen (N) → Heterocycles with oxygen and nitrogen (C, H, O, N) → 1-oxa-4-azacyclohexane

FORMULA:C4H9NO
TRIVIAL NAME: morpholine
CAS RN:110-91-8
STRUCTURE
(FROM NIST):
InChIKey:YNAVUWVOSKDBBP-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.9×102 7800 Nguyen (2013) M 11)
8.5 Duchowicz et al. (2020) V 187)
8.2 HSDB (2015) V
7.3×101 8400 Cabani et al. (1975a) T
2.2×101 Duchowicz et al. (2020) Q
1.6×102 Hilal et al. (2008) Q
8.1×101 Modarresi et al. (2007) Q 68)
9.5×101 English and Carroll (2001) Q 231) 275)
1.0×101 Nirmalakhandan et al. (1997) Q
4.2×101 Yaws (1999) ? 12) 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

  • Cabani, S., Conti, G., Giannessi, D., & Lepori, L.: Thermodynamic study of aqueous dilute solutions of organic compounds. Part 3. – Morpholines and piperazines, J. Chem. Soc. Faraday Trans. 1, 71, 1154–1160, doi:10.1039/F19757101154 (1975a).
  • 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).
  • HSDB: Hazardous Substances Data Bank, TOXicology data NETwork (TOXNET), National Library of Medicine (US), URL https://www.nlm.nih.gov/toxnet/Accessing_HSDB_Content_from_PubChem.html (2015).
  • 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).
  • Nguyen, T.: Amine Volatility in CO2 Capture, Ph.D. thesis, The University of Texas at Austin, USA, URL https://rochelle.che.utexas.edu/files/2015/02/Nguyen-2013-Amine-Volatility-in-CO2-Capture.pdf (2013).
  • Nirmalakhandan, N., Brennan, R. A., & Speece, R. E.: Predicting Henry’s law constant and the effect of temperature on Henry’s law constant, Wat. Res., 31, 1471–1481, doi:10.1016/S0043-1354(96)00395-8 (1997).
  • Yaws, C. L.: Chemical Properties Handbook, McGraw-Hill, Inc., ISBN 0070734011 (1999).

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

11) Measured at high temperature and extrapolated to T⊖ = 298.15 K.
12) Value at T = 293 K.
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.
187) Estimation based on the quotient between vapor pressure and water solubility, 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.
275) Value from the test dataset.

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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