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 Please do not cite the old paper anymore.
|
FORMULA: | C2F5Cl |
TRIVIAL NAME:
|
R115
|
CAS RN: | 76-15-3 |
STRUCTURE
(FROM
NIST):
|
|
InChIKey: | RFCAUADVODFSLZ-UHFFFAOYSA-N |
|
|
References |
Type |
Notes |
[mol/(m3Pa)] |
[K] |
|
|
|
3.4×10−6 |
2800 |
Wilhelm et al. (1977) |
L |
|
3.1×10−6 |
2100 |
Reichl (1995) |
M |
763)
|
1.8×10−6 |
|
Duchowicz et al. (2020) |
V |
187)
|
1.8×10−6 |
|
HSDB (2015) |
V |
|
3.8×10−6 |
|
Mackay et al. (1993) |
V |
|
3.7×10−6 |
|
Meylan and Howard (1991) |
V |
|
3.2×10−6 |
|
Hine and Mookerjee (1975) |
V |
|
3.8×10−6 |
|
Yaws (2003) |
X |
238)
|
3.2×10−6 |
|
Irmann (1965) |
C |
|
3.1×10−6 |
|
Hayer et al. (2022) |
Q |
20)
|
6.5×10−5 |
|
Duchowicz et al. (2020) |
Q |
|
4.9×10−5 |
|
Gharagheizi et al. (2012) |
Q |
|
2.5×10−6 |
|
Gharagheizi et al. (2010) |
Q |
247)
|
3.4×10−5 |
|
Hilal et al. (2008) |
Q |
|
7.6×10−6 |
|
Modarresi et al. (2007) |
Q |
68)
|
|
2900 |
Kühne et al. (2005) |
Q |
|
2.4×10−5 |
|
Yao et al. (2002) |
Q |
230)
|
1.2×10−6 |
|
Meylan and Howard (1991) |
Q |
|
2.1×10−6 |
|
Irmann (1965) |
Q |
|
|
2000 |
Kühne et al. (2005) |
? |
|
3.8×10−6 |
|
Yaws (1999) |
? |
21)
|
3.8×10−6 |
|
Yaws and Yang (1992) |
? |
21)
|
Data
The first column contains Henry's law solubility constant
at the reference temperature of 298.15 K.
The second column contains the temperature dependence
, also at the
reference temperature.
References
-
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).
-
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).
-
Hayer, N., Jirasek, F., & Hasse, H.: Prediction of Henry’s law constants by matrix completion, AIChE J., 68, e17 753, doi:10.1002/AIC.17753 (2022).
-
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).
-
Hine, J. & Mookerjee, P. K.: The intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions, J. Org. Chem., 40, 292–298, doi:10.1021/JO00891A006 (1975).
-
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).
-
Irmann, F.: Eine einfache Korrelation zwischen Wasserlöslichkeit und Struktur von Kohlenwasserstoffen und Halogenkohlenwasserstoffen, Chem.-Ing.-Tech., 37, 789–798, doi:10.1002/CITE.330370802 (1965).
-
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).
-
Mackay, D., Shiu, W. Y., & Ma, K. C.: Illustrated Handbook of Physical-Chemical Properties and Environmental Fate for Organic Chemicals, vol. III of Volatile Organic Chemicals, Lewis Publishers, Boca Raton, ISBN 0873719735 (1993).
-
Meylan, W. M. & Howard, P. H.: Bond contribution method for estimating Henry’s law constants, Environ. Toxicol. Chem., 10, 1283–1293, doi:10.1002/ETC.5620101007 (1991).
-
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).
-
Reichl, A.: Messung und Korrelierung von Gaslöslichkeiten halogenierter Kohlenwasserstoffe, Ph.D. thesis, Technische Universität Berlin, Germany (1995).
-
Wilhelm, E., Battino, R., & Wilcock, R. J.: Low-pressure solubility of gases in liquid water, Chem. Rev., 77, 219–262, doi:10.1021/CR60306A003 (1977).
-
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
20) |
Calculated using machine learning matrix completion methods (MCMs). |
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. |
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. |
763) |
The data from Reichl (1995) were fitted to the three-parameter equation: Hscp= exp( −149.62353 +7869.46528/T +19.40044 ln(T)) mol m−3 Pa−1, with T in K. |
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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