Pathways in particle assembly by ultrasound-assisted spray-drying of kaolin/SAPO-34 as a fluidized bed catalyst for methanol to light olefins

Ultrasound-assisted rapid hydrothermal design of efficient nanostructured MFI-Type aluminosilicate catalyst for methanol to propylene reaction

The influence of ultrasound-assisted rapid hydrothermal synthesis of aluminosilicate ZSM-5 catalysts was examined in this work. A series of MFI-type nanostructured materials with sonochemical approach and conventionalheating were synthesized and evaluated for conversion of methanol to propylene reaction. The prepared samples were tested by characterization analyses such as XRD, FESEM, BET-BJH, FTIR, TPD-NH₃ and TG/DTG. The obtained results confirmed that ultrasound treatment enhanced the nucleation process and crystal growth for ZSM-5 sample synthesized at moderate temperature of 250 °C. Therefore, it was found the formation of pure MFI zeolite with high crystallinity and improved textural, structural and acidic properties for ZSM-5(UH-250) sample compared with the other zeolites. This observation was attributed to the relationship between the perfect crystallization mechanism and catalytic properties, which led to producing an efficient MFI zeolite toward the optimal catalytic performance. In this manner, the methanol conversion and products selectivity of prepared materials were carried out in MTP reaction at 460 °C and atmospheric pressure. The ZSM-5(UH-250) zeolite with slower deactivation regime exhibited the constant level of methanol conversion (84%) and high propylene selectivity (78%) after 2100 min time on stream. Moreover, the synthesis pathway for MFI zeolite at moderate temperature and also deactivation mechanism of improved sample were proposed.

Power ultrasound and its applications: A state-of-the-art review

Ultrasonic processing has attracted increasing attention by people because ultrasonic technology may represent a flexible 'green' alternative for energy efficient processes. The major challenges for the power ultrasound application in real situations are the design and development of specific power ultrasonic systems for large-scale operations. Thus, new families of power ultrasonic transducers have been developed in recent years to meet actual needs, and this contributes to the implementation of power ultrasound of application in many fields such as chemical industry, food industry and manufacturing. This paper presents the current state of ultrasonic transducers of magnetostrictiv type and piezoelectric type as well as applications of power ultrasound in various industrial fields including chemical reactions, drying/dehydration, welding, extraction, heat transfer enhancement, de-ice, enhanced oil recovery, droplet atomization, cleaning and fine particle removal. The review paper helps to understand the current development of power ultrasonic technology and its applications in various situations, and induce extended applications of power ultrasound to more and more fields.

Performance analysis of ultrasound-assisted synthesized nano-hierarchical SAPO-34 catalyst in the methanol-to-lights-olefins process via artificial intelligence methods

The present study has focused on performance analysis of ultrasound-assisted synthesized nano-hierarchical silico-alumino-phosphate-34 (SAPO-34) catalyst during methanol-to-light-olefins (MTO) process. A classical method, i.e., multiple linear regression (MLR) and two intelligent methods, i.e., genetic programming (GP) and artificial neural networks (ANN) were used for modeling of the performance of nano-hierarchical SAPO-34 catalyst. We studied the influence of basic parameters for the sonochemical synthesis of nano-hierarchical SAPO-34 catalyst such as crystallization time, ultrasonic irradiation time, ultrasonic intensity, amount of organic template (diethylamine (DEA) and carbon nanotube (CNT)) on its performance (methanol conversion and light olefins selectivity) in MTO process. The results revealed that the models achieved using the GP method had the highest accuracy for training and test data. Therefore, GP models were used in the following to predict the effect of main parameters for the sonochemical synthesis of nano-hierarchical SAPO-34 catalyst. Finally, an optimal catalyst with the highest yield into light olefins was predicted using the genetic optimization algorithm. The genetic models were employed as an evaluation function in the genetic algorithm (GA). A good agreement between the outputs of GP models for the optimal catalyst and experimental results were obtained. The optimal ultrasound-assisted synthesized nano-hierarchical SAPO-34 was accompanied by light olefins selectivity of 77% and methanol conversion of 94% from the onset of the process after 9 h.