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

Combined DFT and Machine Learning Study of the Dissociation and Migration of H in Pyrrole Derivatives

Systematic DFT calculations of model coal-pyrrole derivatives substituted by different functional groups are carried out. The N-H bond dissociation energies (N-H BDEs) and H-transfer activation energies (H-TAEs) of pyrrole derivatives are fully evaluated to elucidate the effect of the type of substituents and their position on the molecular reactivity. The results indicate that compounds substituted with electron-donating groups (EDGs) are more prone to pyrolysis while those substituted with electron-withdrawing groups (EWGs) are difficult to pyrolyze. Furthermore, quantitative structure-property relationship (QSPR) models for N-H BDEs and H-TAEs about pyrrole derivatives are built with multiple linear regression (MLR) and support vector machine (SVM). The final results show that the SVM-QSPR model has better fitness, prediction, and robustness, while the MLR-QSPR model can express the physical meaning better. The effects of functional groups on pyrolysis are clarified by the models presented in this paper, which will support the optimization of ultra-low NOx combustion.

A multi-technique approach to unveil the redox behaviour and potentiality of homoleptic CuI complexes based on substituted bipyridine ligands in oxygenation reactions

The effect of differently substituted 2,2'-bipyridine ligands (i.e. 6,6'-dimethyl-2,2'-bipyridine, 5,5'-dimethyl-2,2'-bipyridine, 6,6'-dimethoxy-2,2'-bipyridine and 2,2'-bipyridine) on the reversible oxidation of the resulting Cu^I homoleptic complexes is investigated by means of a multi-technique approach (electronic and vibrational spectroscopies, DFT, electrochemistry). Among the four tested complexes, [Cu^I(6,6'-dimethyl-2,2'-bipyridine)₂] (PF₆) shows a peculiar behavior when oxidized with an organic peroxide (i.e. tert-butyl hydroperoxide, tBuOOH). The simultaneous use of UV-Vis-NIR and Raman spectroscopy methods and cyclovoltammetry, supported by DFT based calculations, allowed identifying (i) the change in the oxidation state of the copper ion and (ii) some peculiar modification in the local structure of the metal leading to the formation of a [Cu^IIOH]⁺ species. The latter, being able to oxidize a model molecule (i.e. cyclohexene) and showing the restoration of the original Cu^I complex and the formation of cyclohexanone, confirms the potential of these simple homoleptic Cu^I complexes as model catalysts for partial oxygenation reactions.

Thermal Conductivity Estimation of Diverse Liquid Aliphatic Oxygen-Containing Organic Compounds Using the Quantitative Structure-Property Relationship Method

Thermal conductivity is an essential thermodynamic data in chemical engineering applications. Liquid aliphatic oxygen-containing organic compounds are important organic intermediates and raw materials. As a result, estimating thermal conductivity of liquid aliphatic oxygen-containing organic compounds is of significance in industry production. In this study, the genetic function approximation method was applied to screen descriptors and develop a 6-descriptor linear quantitative structure-property relationship model. The entire data set of these compounds covering 1064 thermal conductivity values was divided into 694-member training set, 298-member test set, and 72-member prediction set. The average absolute relative deviation of the training set, test set, and prediction set were 4.14, 4.41, and 4.16%, respectively. Model validation and Y-randomization test proved that the developed model has goodness-of-fit, predictive power, and robustness. In addition, the applicability domain of the developed model was visualized by the Williams plot. This study can provide a convenient method to estimate the thermal conductivity for researchers in chemical engineering production.

Development of Simple QSPR Models for the Prediction of the Heat of Decomposition of Organic Peroxides

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.

Significance of Theoretical Decomposition Enthalpies for Predicting Thermal Hazards

Much effort is currently put into the development of models for predicting decomposition enthalpies measured using differential scanning calorimetry (DSC). As an alternative to the purely empirical schemes reported so far, this work relies on theoretical values obtained on the basis of simple assumptions. For nitroaromatic compounds (NACs) studied in sealed sample cells, our approach proves clearly superior to previous ones. In contrast, it correlates poorly with data measured in pin-hole sample cells. Progress might be obtained through a combination of the present approach with the usual Quantitative Structure-Property Relationships (QSPR) methodologies. This work emphasizes the significance of the theoretical decomposition enthalpy as a fundamental descriptor for the prediction of DSC values. In fact, the theoretical value provides a valuable criterion to characterize thermal hazards, as a complement to experimental decomposition temperatures.

Prediction of the thermal decomposition of organic peroxides by validated QSPR models

Organic peroxides are unstable chemicals which can easily decompose and may lead to explosion. Such a process can be characterized by physico-chemical parameters such as heat and temperature of decomposition, whose determination is crucial to manage related hazards. These thermal stability properties are also required within many regulatory frameworks related to chemicals in order to assess their hazardous properties. In this work, new quantitative structure-property relationships (QSPR) models were developed to predict accurately the thermal stability of organic peroxides from their molecular structure respecting the OECD guidelines for regulatory acceptability of QSPRs. Based on the acquisition of 38 reference experimental data using DSC (differential scanning calorimetry) apparatus in homogenous experimental conditions, multi-linear models were derived for the prediction of the decomposition heat and the onset temperature using different types of molecular descriptors. Models were tested by internal and external validation tests and their applicability domains were defined and analyzed. Being rigorously validated, they presented the best performances in terms of fitting, robustness and predictive power and the descriptors used in these models were linked to the peroxide bond whose breaking represents the main decomposition mechanism of organic peroxides.

Calorimetric studies and lessons on fires and explosions of a chemical plant producing CHP and DCPO

Cumene hydroperoxide (CHP) has been used in producing phenol, dicumyl peroxide (DCPO) and as an initiator for synthesizing acrylonitrile-butadiene-styrene (ABS) resin by copolymerization in Taiwan. Four incidents of fire and explosion induced by thermal runaway reactions were occurred in a same plant producing CHP, DCPO and bis-(tert-butylperoxy isopropyl) benzene peroxide (BIBP). The fourth fire and explosion occurred in the CHP reactor that resulted in a catastrophic damage in reaction region and even spread throughout storage area. Descriptions on the occurrences of these incidents were assessed by the features of processes, reaction schemes and unexpected side reactions. Calorimetric data on thermokinetics and pressure were used for explaining the practical consequences or which the worst cases encountered in this kind of plant. Acceptable risk associated with emergency relief system design is vital for a plant producing organic peroxide. These basic data for designing an inherently safer plant can be conducted from adiabatic calorimetry. An encouraging deduction has been drawn here, these incidents may be avoided by the implementation of API RP 520, API RP 521, DIERS technology, OSHA 1910.119 and AIChE's CCPS recommended PSM elements.