Nitration of 1,3,3-trimethyl-1-phenylindane on mesoporous aluminosilicates

Nitration of 1,3,3-trimethyl-1-phenylindane (phenylindane) by nitric acid of different concentration over mesoporous aluminosilicates with the molar ratios SiO2 : Al2O3 = 20, 40, and 80 was studied. The effects of the SiO2 : Al2O3 and phenylindane : nitric acid ratios, the concentration of nitric acid, and temperature on the conversion of phenylindane and the yield of dinitrophenylindane were revealed. The aluminosilicate samples with a SiO2 : Al2O3 ratio of 20 are shown to have the highest activity. In the presence of these samples, the conversion of phenylindane reaches 100% with a selectivity of formation of 5and 6-nitro-1-(4´-nitrophenyl)1,3,3-trimethylindanes close to 80% (70% nitric acid, 100 °C)

Nitration of 1,3,3-trimethyl-1-phenylindane on mesoporous aluminosilicates

Nitration of 1,3,3-trimethyl-1-phenylindane (phenylindane) by nitric acid of different concentration over mesoporous aluminosilicates with the molar ratios SiO2 : Al2O3 = 20, 40, and 80 was studied. The effects of the SiO2 : Al2O3 and phenylindane : nitric acid ratios, the concentration of nitric acid, and temperature on the conversion of phenylindane and the yield of dinitrophenylindane were revealed. The aluminosilicate samples with a SiO2 : Al2O3 ratio of 20 are shown to have the highest activity. In the presence of these samples, the conversion of phenylindane reaches 100% with a selectivity of formation of 5and 6-nitro-1-(4´-nitrophenyl)1,3,3-trimethylindanes close to 80% (70% nitric acid, 100 °C)

Crystallization of SAPO-11 Molecular Sieves Prepared from Silicoaluminophosphate Gels Using Boehmites with Different Properties

In this article, we report the results of research the formation of silicoaluminophosphate gels under changing gel aging conditions and the influence of an aluminum source (boehmite), characterized by different properties. The samples of initial gels were characterized by XRF, X-ray diffraction, MAS NMR 27Al and 31P, and scanning electron microscopy (SEM). Products of crystallization were characterized by XRF, X-ray diffraction, MAS NMR 27Al and 31P, scanning electron microscopy (SEM), N2-physical adsorption, and IR spectroscopy with pyridine adsorption. It has been established that the chemical and phase composition of aging gels and the products of further crystallization is conditioned by the size of the crystals and the porous structure of boehmite. Methods of management the morphology and secondary porous structure of SAPO-11, including the hierarchical porous structure, are proposed based on the use of boehmits characterized by different properties and changing the aging conditions of the initial gels. SAPO—based catalyst with a hierarchical porous structure showed excellent catalytic performance in dimerization of α-methylstyrene with a high degree of conversion and selectivity for linear isomers

Crystallization of SAPO-11 Molecular Sieves Prepared from Silicoaluminophosphate Gels Using Boehmites with Different Properties

In this article, we report the results of research the formation of silicoaluminophosphate gels under changing gel aging conditions and the influence of an aluminum source (boehmite), characterized by different properties. The samples of initial gels were characterized by XRF, X-ray diffraction, MAS NMR 27Al and 31P, and scanning electron microscopy (SEM). Products of crystallization were characterized by XRF, X-ray diffraction, MAS NMR 27Al and 31P, scanning electron microscopy (SEM), N2-physical adsorption, and IR spectroscopy with pyridine adsorption. It has been established that the chemical and phase composition of aging gels and the products of further crystallization is conditioned by the size of the crystals and the porous structure of boehmite. Methods of management the morphology and secondary porous structure of SAPO-11, including the hierarchical porous structure, are proposed based on the use of boehmits characterized by different properties and changing the aging conditions of the initial gels. SAPO—based catalyst with a hierarchical porous structure showed excellent catalytic performance in dimerization of α-methylstyrene with a high degree of conversion and selectivity for linear isomers

Enhancing Microwave Photonic Interrogation Accuracy for Fiber-Optic Temperature Sensors via Artificial Neural Network Integration

In this paper, an application of an artificial neural network algorithm is proposed to enhance the accuracy of temperature measurement using a fiber-optic sensor based on a Fabry–Perot interferometer (FPI). It is assumed that the interrogation of the FPI is carried out using an optical comb generator realizing a microwave photonic approach. Firstly, modelling of the reflection spectrum of a Fabry–Perot interferometer is implemented. Secondly, probing of the obtained spectrum using a comb-generator model is performed. The resulting electrical signal of the photodetector is processed and is used to create a sample for artificial neural network training aimed at temperature detection. It is demonstrated that the artificial neural network implementation can predict temperature variations with an accuracy equal to 0.018 °C in the range from −10 to +10 °C and 0.147 in the range from −15 to +15 °C