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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 Please do not cite the old paper anymore.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 oxygen (O) → Alcohols (ROH) → 2-methyl-2-butanol

FORMULA:C5H12O
TRIVIAL NAME: tert-pentanol
CAS RN:75-85-4
STRUCTURE
(FROM NIST):
InChIKey:MSXVEPNJUHWQHW-UHFFFAOYSA-N

Hscp d ln Hs cp / d (1/T) References Type Notes
[mol/(m3Pa)] [K]
6.5×10−1 7900 Brockbank (2013) L 1)
7.1×10−1 8200 Plyasunov and Shock (2000) L
7.2×10−1 8200 Fenclová et al. (2010) M 1)
7.0×10−1 Merk and Riederer (1997) M
7.1×10−1 Butler et al. (1935) M
1.6 Keshavarz et al. (2022) Q
2.3×10−1 Duchowicz et al. (2020) Q
1.2×10−1 Wang et al. (2017) Q 81) 239)
6.6×10−1 Wang et al. (2017) Q 81) 240)
4.8×10−1 Wang et al. (2017) Q 81) 241)
7.2×10−1 HSDB (2015) Q 100)
6.2×10−1 Raventos-Duran et al. (2010) Q 244) 272)
3.9×10−1 Raventos-Duran et al. (2010) Q 245)
7.8×10−1 Raventos-Duran et al. (2010) Q 246)
2.7×10−1 Hilal et al. (2008) Q
1.1 Modarresi et al. (2007) Q 68)
7600 Kühne et al. (2005) Q
7.9×10−1 Yaffe et al. (2003) Q 249) 273)
2.8×10−1 Yao et al. (2002) Q 230)
7.5×10−1 English and Carroll (2001) Q 231) 232)
6.9×10−1 Katritzky et al. (1998) Q
6.1×10−1 Yaws et al. (1997) Q
5.0×10−1 Suzuki et al. (1992) Q 233)
6.0×10−1 Nirmalakhandan and Speece (1988) Q
7.2×10−1 Duchowicz et al. (2020) ? 21) 186)
7200 Kühne et al. (2005) ?
5.6×10−2 Yaws (1999) ? 21)
7.2×10−1 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., & Thomson, D. W.: The solubility of non-electrolytes. Part I. The free energy of hydration of some aliphatic alcohols, J. Chem. Soc., pp. 280–285, doi:10.1039/JR9350000280 (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).
  • 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).
  • Fenclová, D., Dohnal, V., Vrbka, P., & ehk, K.: Temperature dependence of limiting activity coefficients, Henry’s law constants, and related infinite dilution properties of branched pentanols in water. Measurement, critical compilation, correlation, and recommended data, J. Chem. Eng. Data, 55, 3032–3043, doi:10.1021/JE901063S (2010).
  • 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).
  • 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).
  • 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).
  • Merk, S. & Riederer, M.: Sorption of volatile C1 to C6 alkanols in plant cuticles, J. Exp. Bot., 48, 1095–1104, doi:10.1093/JXB/48.5.1095 (1997).
  • 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. & Shock, E. L.: Thermodynamic functions of hydration of hydrocarbons at 298.15K and 0.1MPa, Geochim. Cosmochim. Acta, 64, 439–468, doi:10.1016/S0016-7037(99)00330-0 (2000).
  • 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).
  • Wang, C., Yuan, T., Wood, S. A., Goss, K.-U., Li, J., Ying, Q., & Wania, F.: Uncertain Henry’s law constants compromise equilibrium partitioning calculations of atmospheric oxidation products, Atmos. Chem. Phys., 17, 7529–7540, doi:10.5194/ACP-17-7529-2017 (2017).
  • 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).
  • 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., Hopper, J. R., Sheth, S. D., Han, M., & Pike, R. W.: Solubility and Henry’s law constant for alcohols in water, Waste Manage., 17, 541–547, doi:10.1016/S0956-053X(97)10057-5 (1997).

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.
81) Value at T = 288 K.
100) Calculated based on the method by Meylan and Howard (1991).
186) Experimental value, extracted from HENRYWIN.
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.
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.
239) Calculated using linear free energy relationships (LFERs).
240) Calculated using SPARC Performs Automated Reasoning in Chemistry (SPARC).
241) Calculated using COSMOtherm.
244) Calculated using the GROMHE model.
245) Calculated using the SPARC approach.
246) Calculated using the HENRYWIN method.
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.
272) Value from the validation dataset.
273) Value from the test 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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