No abstract

A large number of organic compounds, such as ethers, spontaneously form unstable peroxides through a self-propagating process of autoxidation (peroxidation). Although the hazards of organic peroxides are well known, the oxidation mechanisms of peroxidizable compounds like ethers reported in the literature are vague and often based on old experiments, carried out in very different conditions (e.g. atmospheric, combustion). With the aim to (partially) fill the lack of information, in this paper we present an extensive Density Functional Theory (DFT) study of autoxidation reaction of diethyl ether (DEE), a chemical that is largely used as solvent in laboratories, and which is considered to be responsible for various accidents. The aim of the work is to investigate the most probable reaction paths involved in the autoxidation process and to identify all potential hazardous intermediates, such as peroxides. Beyond the determination of a complex oxidation mechanism for such a simple molecule, our results suggest that the two main reaction channels open in solution are the direct decomposition (β-scission) of DEE radical issued of the initiation step and the isomerization of the peroxy radical formed upon oxygen attack (DEEOO˙). A simple kinetic evaluation of these two competing reaction channels hints that radical isomerization may play an unexpectedly important role in the global DEE oxidation process. Finally industrial hazards could be related to the hydroperoxide formation and accumulation during the chain propagation step. The resulting information may contribute to the understanding of the accidental risks associated with the use of diethyl ether.

The formation of molecular hydrogen in the radiolysis of water confined in nanoscale pores of well-characterised porous silica glasses and mesoporous molecular sieves (MCM-41) is examined. The comparison of dihydrogen formation by irradiation of both materials, dry and hydrated, shows that a large part of the H2 comes from the surface of the material. The radiolytic yields, G(H2)=(3+/-0.5)x10(-7) mol J(-1), calculated using the total energy deposited in the material and the water, are only slightly affected by the degree of hydration of the material and by the pore size. These yields are also not modified by the presence of hydroxyl radical scavengers. This observation proves that the back reaction between H2 and HO(.) is inoperative in such confined environments. Furthermore, the large amount of H2 produced in the presence of different concentrated scavengers of the hydrated electron and its precursor suggests that these two species are far from being the only species responsible for the H2 formation. Our results show that the radiolytic phenomena that occur in water confined in nanoporous silica are dramatically different to those in bulk water, suggesting the need to investigate further the chemical reactivity in this type of environment.

No abstract

For registration of a chemical, European Union REACH legislation requires information on the relevant physico-chemical properties of the chemical. Predicted property values can be used when the predictions can be shown to be valid and adequate. The relevant physico-chemical properties that are amenable to prediction are: melting/freezing point, boiling point, relative density, vapour pressure, surface tension, water solubility, n-octanol-water partition coefficient, flash point, flammability, explosive properties, self-ignition temperature, adsorption/desorption, dissociation constant, viscosity, and air-water partition coefficient (Henry's law constant). Published quantitative structure-property relationship (QSPR) methods for all of these properties are discussed, together with relevant property prediction software, as an aid for those wishing to use predicted property values in submissions to the European Chemicals Agency (ECHA).

The decomposition mechanism of ammonium nitrate in the gas phase was investigated and fully characterized by means of CBS-QB3 calculations. Five reaction channels were identified, leading to the formation of products (N2, H2O, O2, OH, HNO, NO3) found in the experimental works. The identified mechanism well underlines the origin of the chemical hazard of ammonium nitrate which is related to the exothermicity of the lowest decomposition channels. Furthermore, the high barrier to overcome in the rate determining step well explained the fact that the reaction is not usually spontaneous and requires a significant external stimulus for its onset. An accurate DFT benchmark study was then conducted to determine the most suitable exchange-correlation functional to accurately describe the reaction profile both in terms of structures and thermochemistry. This evaluation supports the use of the M06-2X functional as the best option for the study of ammonium nitrate decomposition and related reactions. Indeed, this level of theory provided the lowest deviations with respect to CBS-QB3 reference values, outperforming functionals especially developed for reaction kinetics.

No abstract

Quantitative structure−property relationships (QSPRs) are increasingly used for the prediction of physicochemical properties of pure compounds, but only a few have been developed to predict the properties of mixtures. In this work, a series of existing and new formulas were proposed to derive mixture descriptors for the development of QSPR models for mixtures. These mixture descriptors were used to model the flash points of a series of 435 organic mixture compositions. Multilinear models were obtained using 12 different mathematical formulas, taking into account the linear or nonlinear dependence of the flash point on the concentration of each compound. The best model, issued from the newly proposed (x 1 d 1 + x 2 d 2 ) 2 formula, was a four-parameter model presenting good prediction capabilities (with a mean absolute error in prediction of 10.3°C) compared with existing predictive methods for both mixtures and pure compounds. ■ INTRODUCTIONQuantitative structure−property relationships (QSPRs) are predictive models that allow the prediction of macroscopic properties by correlation with descriptors of the molecular structures of chemicals. 1 These molecular descriptors belong to various categories: 1,2 constitutional, topological, geometrical, or quantum-chemical. Such methods have been largely used for biological activities in the fields of toxicology, 3 ecotoxicology, 4 and pharmaceutics 5,6 and are increasingly used for physicochemical properties. 7−9Various models have been developed for hazardous physicochemical properties 10−19 such as flammability, 10,11 thermal stability, 12−14 and explosibility. 15−19 To date, the QSPR approach has mostly been dedicated to pure compounds, and only a few recent works have been dedicated to mixtures. 20 Ajmani and co-workers proposed various models to predict the densities 21,22 and infinite-dilution activity coefficients 23 of binary mixtures. In these studies, the molecular descriptors for each pure compound were combined, e.g., by mole-weighted averaging, 24 to derive mixture descriptors. These mixture descriptors were then correlated to the property of the studied mixtures. Several studies have also been dedicated to azeotropic mixtures. 25−29 In particular, Oprisiu et al. 29 developed several QSPR models to predict the boiling points 25,28 of azeotropic binary mixtures on the basis of fragment descriptors.The flash point (FP) is the temperature at which the vapor above a flammable liquid ignites under the effect of a spark. 30 This property characterizes flammability hazards of liquids and is a key safety issue in the risk assessment of industrial processes and in various regulatory frameworks dedicated to chemicals (for use, storage, and transport). 31,32 The flash points of pure compounds have been studied in several works with the aim of developing predictive methods taking advantage of the large availability of data. 33,34 Among them, many are based on knowledge of other properties such as the boiling point. 24,35,36 The highest performance was obtained by Carroll ...