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Prana, V.; Rotureau, P.; André, D.; Fayet, G.; Adamo, C. Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides. Mol. Inform. 2017, 36, 1700024.

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Prana, V.; Rotureau, P.; André, D.; Fayet, G.; Adamo, C. Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides. Mol. Inform. 2017, 36, 1700024.

QDB archive DOI: 10.15152/QDB.230   DOWNLOAD

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Property dH_C: Heat of decomposition [J/g]

Eq4: Model for organic peroxides

Regression model (regression)   QMRF

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Name Type n

R2

σ

Training set training 25 0.892 151.784
Test set external validation 12 0.793 239.577

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dc.date.accessioned 2020-04-28T11:09:57Z
dc.date.available 2020-04-28T11:09:57Z
dc.date.issued 2020-04-28
dc.identifier.uri http://hdl.handle.net/10967/230
dc.identifier.uri http://dx.doi.org/10.15152/QDB.230
dc.description.abstract Quantitative structure‐property relationships represent alternative method to experiments to access the estimation of physico‐chemical properties of chemicals for screening purpose at R&D level but also to gather missing data in regulatory context. In particular, such predictions were encouraged by the REACH regulation for the collection of data, provided that they are developed respecting the rigorous principles of validation proposed by OECD. In this context, a series of organic peroxides, unstable chemicals which can easily decompose and may lead to explosion, were investigated to develop simple QSPR models that can be used in a regulatory framework. Only constitutional and topological descriptors were employed to achieve QSPR models predicting the heat of decomposition, which could be used without any time consuming preliminary structure calculations at quantum chemical level. To validate the models, the original experimental dataset was divided into a training and a validation set according to two methods of partitioning, one based on the property value and the other based on the structure of the molecules by the mean of PCA. Four QSPR models were developed upon the type of descriptors and the methods of partitioning. The 2 models issuing from the PCA based method were highlighted as they presented good predictive power and they are easier to apply than our previous quantum chemical based model, since they do not need any preliminary calculations.
dc.publisher Geven Piir
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.title Prana, V.; Rotureau, P.; André, D.; Fayet, G.; Adamo, C. Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides. Mol. Inform. 2017, 36, 1700024.
qdb.property.endpoint 6. Other (Heat of decomposition) en_US
qdb.descriptor.application Codessa 2.7.16 en_US
qdb.prediction.application Codessa 2.7.16 en_US
bibtex.entry article en_US
bibtex.entry.author Prana, V.
bibtex.entry.author Rotureau, P.
bibtex.entry.author André, D.
bibtex.entry.author Fayet, G.
bibtex.entry.author Adamo, C.
bibtex.entry.doi 10.1002/minf.201700024 en_US
bibtex.entry.journal Mol. Inform. en_US
bibtex.entry.month Apr
bibtex.entry.number 10 en_US
bibtex.entry.pages 1700024 en_US
bibtex.entry.title Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides en_US
bibtex.entry.volume 36 en_US
bibtex.entry.year 2017
qdb.model.type Regression model (regression) en_US
qdb.model.qmrf Eq4=QMRF en_US


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