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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 Please do not cite the old paper anymore.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 → Organic species with nitrogen (N) → Nitriles (C, H, N) → butanenitrile

FORMULA:C3H7CN
TRIVIAL NAME: butyronitrile
CAS RN:109-74-0
STRUCTURE
(FROM NIST):
InChIKey:KVNRLNFWIYMESJ-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
1.8×10−1 5100 Brockbank (2013) L 1)
1.8×10−1 5100 Plyasunov et al. (2006) L
2.7×10−1 5100 Ji and Evans (2007) M
1.3×10−1 Ramachandran et al. (1996) M
1.9×10−1 Li and Carr (1993) M
1.4×10−1 Hawthorne et al. (1985) M
1.9×10−1 Butler and Ramchandani (1935) M
1.8×10−1 Yaws (2003) X 259)
1.8×10−1 Yaws (2003) X 238)
3.7×10−1 Dupeux et al. (2022) Q 260)
1.2×10−1 Keshavarz et al. (2022) Q
1.0×10−1 Duchowicz et al. (2020) Q 185)
1.8×10−1 Gharagheizi et al. (2010) Q 247)
3.5×10−1 Hilal et al. (2008) Q
1.5×10−1 Modarresi et al. (2007) Q 68)
4900 Kühne et al. (2005) Q
1.5×10−1 Yaffe et al. (2003) Q 249) 250)
5.7×10−2 English and Carroll (2001) Q 231) 275)
1.9×10−2 Nirmalakhandan et al. (1997) Q
5.4×10−1 Russell et al. (1992) Q 280)
1.9×10−1 Suzuki et al. (1992) Q 233)
1.9×10−1 Duchowicz et al. (2020) ? 21) 186)
1.9×10−1 Mackay et al. (2006d) ?
4700 Kühne et al. (2005) ?
1.8×10−1 Yaws (1999) ? 21)
1.9×10−1 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).
  • Brockbank, S. A.: Aqueous Henry’s law constants, infinite dilution activity coefficients, and water solubility: critically evaluated database, experimental analysis, and prediction methods, Ph.D. thesis, Brigham Young University, USA, URL https://scholarsarchive.byu.edu/etd/3691/ (2013).
  • Butler, J. A. V. & Ramchandani, C. N.: The solubility of non-electrolytes. Part II. The influence of the polar group on the free energy of hydration of aliphatic compounds, J. Chem. Soc., pp. 952–955, doi:10.1039/JR9350000952 (1935).
  • 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).
  • Dupeux, T., Gaudin, T., Marteau-Roussy, C., Aubry, J.-M., & Nardello-Rataj, V.: COSMO-RS as an effective tool for predicting the physicochemical properties of fragrance raw materials, Flavour Fragrance J., 37, 106–120, doi:10.1002/FFJ.3690 (2022).
  • 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).
  • 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).
  • Hawthorne, S. B., Sievers, R. E., & Barkley, R. M.: Organic emissions from shale oil wastewaters and their implications for air quality, Environ. Sci. Technol., 19, 992–997, doi:10.1021/ES00140A018 (1985).
  • 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).
  • Ji, C. & Evans, E. M.: Using an internal standard method to determine Henry’s law constants, Environ. Toxicol. Chem., 26, 231–236, doi:10.1897/06-339R.1 (2007).
  • 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).
  • Kühne, R., Ebert, R.-U., & Schüürmann, G.: Prediction of the temperature dependency of Henry’s law constant from chemical structure, Environ. Sci. Technol., 39, 6705–6711, doi:10.1021/ES050527H (2005).
  • Li, J. & Carr, P. W.: Measurement of water-hexadecane partition coefficients by headspace gas chromatography and calculation of limiting activity coefficients in water, Anal. Chem., 65, 1443–1450, doi:10.1021/AC00058A023 (1993).
  • Mackay, D., Shiu, W. Y., Ma, K. C., & Lee, S. C.: Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. IV of Nitrogen and Sulfur Containing Compounds and Pesticides, CRC/Taylor & Francis Group, doi:10.1201/9781420044393 (2006d).
  • 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., 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).
  • Plyasunov, A. V., Plyasunova, N. V., & Shock, E. L.: Group contribution values for the thermodynamic functions of hydration at 298.15 K, 0.1 MPa. 4. aliphatic nitriles and dinitriles, J. Chem. Eng. Data, 51, 1481–1490, doi:10.1021/JE060129+ (2006).
  • Ramachandran, B. R., Allen, J. M., & Halpern, A. M.: Air–water partitioning of environmentally important organic compounds, J. Chem. Educ., 73, 1058–1061, doi:10.1021/ED073P1058 (1996).
  • Russell, C. J., Dixon, S. L., & Jurs, P. C.: Computer-assisted study of the relationship between molecular structure and Henry’s law constant, Anal. Chem., 64, 1350–1355, doi:10.1021/AC00037A009 (1992).
  • 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).
  • Yaffe, D., Cohen, Y., Espinosa, G., Arenas, A., & Giralt, F.: A fuzzy ARTMAP-based quantitative structure-property relationship (QSPR) for the Henry’s law constant of organic compounds, J. Chem. Inf. Comput. Sci., 43, 85–112, doi:10.1021/CI025561J (2003).
  • 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).

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

1) A detailed temperature dependence with more than one parameter is available in the original publication. Here, only the temperature dependence at 298.15 K according to the van 't Hoff equation is presented.
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.
185) Value from the validation set for checking whether the model is satisfactory for compounds that are absent from the training set.
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.
233) Calculated with a principal component analysis (PCA); see Suzuki et al. (1992) for details.
238) Value given here as quoted by Gharagheizi et al. (2010).
247) Calculated using a combination of a group contribution method and neural networks.
249) Yaffe et al. (2003) present QSPR results calculated with the fuzzy ARTMAP (FAM) and with the back-propagation (BK-Pr) method. They conclude that FAM is better. Only the FAM results are shown here.
250) Value from the training set.
259) Value given here as quoted by Dupeux et al. (2022).
260) Calculated using the COSMO-RS method.
275) Value from the test dataset.
280) Value from the training set.

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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