Aromatic nitrations by mixed acid. Slow liquid-liquid reaction regime

Aromatic nitrations by mixed acid have been selected as a specific case of a heterogeneous liquid-liquid reaction. An extensive experimental programme has been followed using adiabatic and heat-flow calorimetry and pilot reactor experiments, supported by chemical analysis. A series of nitration experiments has been carried out to study the influences of different initial and operating conditions such as temperature, stirring speed and sulphuric acid concentration. In parallel, a mathematical model to predict the overall conversion rate has been developed. In this paper the mathematical modelling and the implementation and experimental validation for benzene, toluene and chlorobenzene mononitration in the kinetic control regime (slow liquid-liquid reaction) are presented and discussed

Kinetics of the hydrogenation of 2,4-dinitrotoluene over a palladium on alumina catalyst

The chemistry and kinetics of the catalytic hydrogenation of 2,4-dinitrotoluene (2,4-DNT) over a palladium on alumina catalyst have been investigated. The catalyst consists of porous cylindrical pellets of 4.2 × 4.2 mm in which a shell of Pd has penetrated to a depth of the order of 100 ¿m. The experiments have been performed in a three-phase batch reactor under isothermal and isobaric conditions. Two reactor temperatures of 308 and 345 K and a hydrogen pressure range 0.5¿4 MPa have been chosen. Employing a chromatographic method, analyses of the reaction mixtures have been carried out and the reaction pathway has been studied¿three stable intermediates have been identified. We have concluded that for both types of catalyst, independent of the palladium carrier, the chemistry of the conversion of DNT into DAT is the same. Mass transfer experiments have shown that external mass transfer resistances can be neglected. However, internal diffusion limitations had to be taken into account. To study the intrinsic reaction kinetics, a series of measurements with a finely crushed catalyst of particle diameter lower than 40 ¿m have been carried out. To describe the kinetics, a Langmuir¿Hinshelwood model based on adsorption of hydrogen and organic species on different active sites has been applied. The kinetics parameters have been determined and compared with data for a Pd on carbon catalyst. The influence of the internal mass transfer resistances on the reaction rates has been quantitatively described with an effectiveness factor. At higher temperatures an additional series of experiments with pellets has been performed at 371 K in order to obtain an impression of the possibilities to extrapolate our correlations outside the experimental region. A good agreement between experimental and calculated hydrogen consumption rates is observed

Experimental study of a cocurrent upflow packed bed bubble column reactor: pressure drop, holdup and interfacial area

Gas¿liquid interfacial areas have been determined by means of chemically enhanced absorption of CO2 into DEA in a packed bed bubble column reactor with an inner diameter of 156 mm. The influence of the gas velocity and particle diameter on the interfacial areas, pressure drops and liquid holdups has been investigated. For both packings the limiting values of the gas velocities have been determined above which the interfacial areas and liquid holdups stabilize. In particular gas channelling has been found, which is less pronounced in the bed of larger particles

Neural networks for modelling of chemical reaction systems with complex kinetics: oxidation of 2-octanol with nitric acid

Application of neural networks to model the conversion rates of a heterogeneous oxidation reaction has been investigated — oxidation of 2-octanol with nitric acid has been considered as a case study. Due to a more complex and unknown kinetics of the investigated reaction the proposed approach based on application of neural networks is an efficient and accurate tool to solve modelling problems. The elaborated hybrid model as well as the modelling procedure have been described in detail. Learning data used to train the networks have been extracted from the experimental results obtained in an extensive investigation programme performed with a RC1 Mettler-Toledo reaction calorimeter. The influence of different operating conditions on the accuracy and flexibility of the obtained results has been investigated and discussed. It has been found that with the proposed approach the behaviour of a semi-batch reactor, i.e. its concentration and heat flow time profiles, can be predicted successfully within a singular series of experiments; however, the generalisation of the neural network approach to all series of experiments was impossible

Aromatic nitrations by mixed acid: Fast liquid-liquid regime

Aromatic nitration by mixed acid was selected as a specific case of heterogeneous liquid-liquid reaction. An extensive experimental programme was followed using adiabatic and heat flow calorimetry and pilot reactor experiments, supported by chemical analysis. A series of nitration experiments was carried out to study the influence of different initial and operating conditions, such as temperature, stirring speed, feed rate and sulphuric acid concentration. In parallel, a mathematical model to predict the overall conversion rate was developed. In this paper, the mathematical modelling, implementation and experimental validation for mononitrations of benzene, toluene and chlorobenzene in the mass transfer controlled regime of fast liquid-liquid reactions are presented and discussed