3,7-dinitroso-1,3,5,7-tetraazabicyclo[3.3.1]nonane

Boiling point

Administrative data

Endpoint:

boiling point

Type of information:

(Q)SAR

Adequacy of study:

weight of evidence

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 adequate and reliable documentation / justification

Justification for type of information:

1. SOFTWARE
ACD/Percepta

2. MODEL (incl. version number)
ACD/Labs Release 2018.2.2

3. SMILES OR OTHER IDENTIFIERS USED AS INPUT FOR THE MODEL
O=NN1CN2CN(C1)CN(C2)N=O

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

Data source

Reference

Title:

ACD/Labs Release 2018.2.2

Year:

2018

Bibliographic source:

ACD/Percepta Boiling Point/Vapor Pressure Module Report

Materials and methods

Test guideline

Guideline:

other: REACH Guidance on QSARs R.6

Test material

Test material information

Constituent 1

Reference substance name:

3,7-dinitroso-1,3,5,7-tetraazabicyclo[3.3.1]nonane

EC Number:

202-928-3

EC Name:

3,7-dinitroso-1,3,5,7-tetraazabicyclo[3.3.1]nonane

Cas Number:

101-25-7

Molecular formula:

C5H10N6O2

IUPAC Name:

3,7-dinitroso-1,3,5,7-tetraazabicyclo[3.3.1]nonane

Test material form:

solid

Specific details on test material used for the study:

Smiles: O=NN1CN2CN(C1)CN(C2)N=O

Results and discussion

Boiling point

Key result

Boiling pt.:

458.4 °C

Atm. press.:

760 Torr

Remarks on result:

other:

Remarks:

QSAR predicted value

Applicant's summary and conclusion

Conclusions:

ACD/Percepta predicted that 3,7-Dinitroso-1,3,5,7-tetraazabicyclo[3.3.1]nonane has boiling point of 458.4°C.