Key observations of cumene hydroperoxide concentration on runaway reaction parameters

Lu, Yuan; Ng, Dedy; Miao, Ling; Mannan, M. Sam

doi:10.1016/j.tca.2010.01.011

Cited by 17 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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. 31,32 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%

“…In this study, reactivity data in the training set were collected from DSC tests in which the concentration of organic peroxides varied in the range of 34−98 wt %. Through our previous findings and the work of other researchers, concentration was found to be a factor in affecting the detected onset temperature of organic peroxide. , Therefore, the concentration ( C ) of organic peroxides was also chosen as a descriptor.…”

Section: Methodsmentioning

confidence: 99%

“…Through our previous findings and the work of other researchers, concentration was found to be a factor in affecting the detected onset temperature of organic peroxide. 31,32 Therefore, the concentration (C) of organic peroxides was also chosen as a descriptor.…”

Section: Conceptual Density Functional Theory (Dft) Descriptorsmentioning

confidence: 99%

See 2 more Smart Citations

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

Mannan

2010

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%