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Boiling point

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Reference
Endpoint:
boiling point
Type of information:
(Q)SAR
Adequacy of study:
key study
Reliability:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
results derived from a valid (Q)SAR model and falling into its applicability domain, with limited documentation / justification
Justification for type of information:
1. SOFTWARE
ACD/Percepta

2. MODEL (incl. version number)
ACD/Labs Release 2017.2

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
O=C(NCCO)CCCCCCCCCCC(O)CCCCCC

4. SCIENTIFIC VALIDITY OF THE (Q)SAR MODEL
Boiling Point Calculation

The boiling point of a pure substance is in principle a non-additive property. It has been observed experimentally that in homologous sets, the dependence of boiling point on the number of –CH2– groups obeys, approximately, the following non-linear function:

nC = a0 + a1 / (bp – a2)

where nC is the number of –CH2– groups in the structure, bp is the observed boiling point, and 'ai are empirically-determined constants. Note, however, that the additive algorithm cannot be applied to prediction of the Boiling Point.

We made a detailed comparison of the behavior of different macroscopic properties, such as the index of refraction (nd20), density (d20), and surface tension (γ), for different homologous sets, with respect to boiling point. We observed that all of these properties can be approximately described by the above equation These three properties are further related by different relationships between two out of four macroscopic properties (molar volume, molecular weight, molar refractivity, and the parachor):

nd20 = f(MR, MV)
d20 = f(MW, MV)
γ = f(Parachor, MV)

via the following well-known functions:

f(d) = 1 / d = MV / MW
f(n) = (n2 + 2) / (n2 – 1)= MV / MRr
f(γ) = 1 / γ1/4 = MV / Pr

The noteworthy discovery, made by senior scientists at ACD/Labs, is that there is a function of boiling point with respect to other additive molecular properties, which is a linear (additive) function too. (Moreover, such an approach can also be used for prediction of the dielectric constant for organic compounds).

We express this function as:

K = f(MV, BP)

For different homologous sets, to a good approximation, the linear relationship is obeyed:

K = f(MV, BP) = c0 + c1·nC

where the ci are empirically determined.

From this, we can obtain two linearly-predicted properties (using additive algorithms): our function K, and the molar volume (MV), which are similar in construction to our algorithm for prediction of logP. Of course, there are some differences: for example, the boiling point algorithm is different and more specialized for homologous sets and for other classes of compounds. Once K and MV are obtained, the boiling point is easily calculated
Guideline:
other: REACH Guidance on QSARs R.6
GLP compliance:
no
Type of method:
other: predicted data
Specific details on test material used for the study:
SMILES : O=C(NCCO)CCCCCCCCCCC(O)CCCCCC
Key result
Boiling pt.:
522.4 °C
Atm. press.:
760 Torr
Remarks on result:
other:
Remarks:
QSAR predicted value
Conclusions:
ACD/Percepta predicted that test chemical has boiling point of 522.4°C.
Executive summary:

ACD/Percepta predicted that test chemical has boiling point of 522.4°C.

Description of key information

Based on prediction done using ACD/Percepta, boiling point of test chemical was predicted as 522.4°C.

Key value for chemical safety assessment

Boiling point at 101 325 Pa:
522.4 °C

Additional information

Based on prediction done using ACD/Percepta, boiling point of test chemical was predicted as 522.4°C.

Also from other estimation database, the Boiling point of test chemical was  estimated to be 506.82 ˚C.