Self-association of hydrocarbon hydroperoxides

Belyaev, V. A.; Yablonskii, O. P.; Vinogradov, A. N.; Bystrov, V. F.

doi:10.1007/bf00525908

Cited by 1 publication

(2 citation statements)

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“…The effect of concentration determined in the prediction model may indicate the intramolecular association between peroxide molecules, which can be beneficial for the thermal stability of organic peroxides. 44 In most cases, the use of external data is recommended to ensure the validation of the models. However, in this study, given the training set containing only 16 organic peroxides, it is difficult to divide the data into the training set and test set.…”

Section: Discussionmentioning

confidence: 99%

“…However, this conclusion contradicts with the results of previous research, which state that the increase of concentration leads to the decrease of detected onset temperature. , It is possible that the effect of concentration identified in previous research was neglected in this QSPR study due to its limited influence on detected onset temperature. The effect of concentration determined in the prediction model may indicate the intramolecular association between peroxide molecules, which can be beneficial for the thermal stability of organic peroxides …”

Section: Discussionmentioning

confidence: 99%

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Prediction of the Reactivity Hazards for Organic Peroxides Using the QSPR Approach

Mannan

2010

Ind. Eng. Chem. Res.

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Organic peroxides can thermally decompose and may lead to runaway reactions. These reactivity hazards have been reported as one of the main causes for fire and explosion in process industries. The risk associated with runaway reactions of organic peroxides can be minimized by employing the inherently safer design (ISD) principles: substitution and moderation of hazardous peroxides in chemical processes. However, the application of ISD concepts requires lengthy evaluations and classification of reactivity hazards of organic peroxides, which are impractical to be done through experimental approach due to the large number of peroxide members and great variations in their reactivity hazards. In this work, the quantitative structure-property relationship (QSPR) was used to predict the detected onset temperature (T 0 ) and heat of decomposition (Q d ) of organic peroxides for the estimation of thermal stability and severity of runaway reactions. In addition to the conventional descriptors used in QSPR, we used other properties of the peroxides such as concentration and the number of peroxide functional group as additional descriptors to construct accurate and economic models to predict reactivity hazards. Partial least-squares method (PLS) and multiple linear regression method (MLR) were used to model T 0 and Q d . It was found that the regression model derived from the PLS method give better prediction for reactivity hazards of organic peroxides. Sensitivity analyses were also performed to identify important descriptors contributing to the reactivity hazards of organic peroxides. The proposed study describes a new approach to identify the reactivity hazards of organic peroxides that may lead to safe practices in the process industries.

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Section: Discussionmentioning

confidence: 99%