Pure Hydrogen and Propylene Coproduction in Catalytic Membrane Reactor-Assisted Propane Dehydrogenation

Propane dehydrogenation on a commercial Pt-Sn/Al₂O₃ catalyst in a Pd-Ag membrane reactor is considered. A mathematical model is developed to evaluate the performance of the catalytic membrane reactor for the process of propane dehydrogenation. Design and operating conditions are systematically evaluated for key performance metrics such as propane conversion, propylene selectivity, hydrogen selectivity, and hydrogen recovery under different operating conditions. The results confirm that the high performance of the membrane reactor is related to the continuous removal of hydrogen from the reaction zone to shift the reaction equilibrium towards the formation of more propylene and hydrogen.     

A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture

The Journal of Supercomputing - A multimedia-based medical decision-making system is an ultimate requirement in the medical imaging domain. In the healthcare sector, achieving quick and efficient...     

Eddy Current Detection of Retained Austenite in Ni-Hard4 Cast Iron

In this article, the nondestructive eddy current (EC) method was used for microstructural evaluation of Ni-hard4 cast iron (NiHCI). Different destabilizing heat treatments were used to produce different microstructures and hardness. The microstructural analysis and hardness measurement were done for conventional characterization of the reference blocks. Then, the EC techniques were applied to evaluate the hardness and microstructural changes by the detection of EC parameters at different frequencies. Metallurgical investigations showed that increasing the destabilizing soaking time and temperature decreases the amount of retained austenite in NiHCIs. The nondestructive evaluation method (NDT) revealed that it can be good correlated between retained austenite amount and hardness with EC parameters. This shows that the EC technique can detect NiHCIs products according to the metallurgical characterization with good accuracy.     

Photometric stereo for strong specular highlights

Computational Visual Media - Photometric stereo is a fundamental technique in computer vision known to produce 3D shape with high accuracy. It uses several input images of a static scene taken from...     

Extraction of caffeine and catechins using microwave-assisted and ultrasonic extraction from green tea leaves: an optimization study by the IV-optimal design

In this research, optimal conditions for extraction of caffeine and polyphenols were established from Iranian green tea leaves. In the first step, caffeine was extracted with efficacy about 86% versed to 4.5% of EGC + EGCG. The EGCG + EGC was extracted from partially decaffeinated green tea leaves through microwave-assisted extraction (MAE) and ultrasound-assisted extraction (USE) with efficiency levels of 95 and 85%, respectively. The best results for the MAE process were obtained with 7.8 min and three number of extraction cycles and for the USE process were as followed: time 57 min, temperature 65 °C, and the number of extraction cycles 3. The total phenol content values at the best conditions of MAE and the USE processes were 125 ± 5 and 96 ± 6 mg gallic acid/g DW. The 50% inhibition (IC₅₀) on 1,1-diphenyl-2-picrylhydrazyl (DPPH) were 56 and 66 mg/g of phenol for the MAE and USE processes.     

Application of LS-SVM strategy to estimate H2S loading capacity in different ionic liquids and alkanolamines

Favorable properties of aqueous solutions are improved with the addition of different materials for separation of hydrogen sulfide (H₂S). Also, equilibrium data and available equations for solubility estimation of this gas are only valid for specific solutions and limited ranges of temperature and pressure. In this regard, a machine learning model based on Support vector machine (SVM) algorithm is proposed and developed with mixtures containing different amines and ionic liquids to predict H₂S solubility over wide ranges of temperature (298–434.5 K), pressure (13–9319 kPa), overall mass concentration (3.82–100%) and mixture's apparent molecular weight (18.39–556.17 g/mol). The accuracy of the performance of this network was evaluated by regression analysis on calculated and experimental data, which had not been used in network training.     

Simple size-controlled fabrication of Zn2SnO4 nanostructures and study of their behavior in dye sensitized solar cells

Zn₂SnO₄ nanostructures were obtained via facile and rapid co-precipitation approach in presence of amines with different long chain as a novel basic and capping agents. The effect of different amines such as NH₃, ethylenediamine, triethylenetetramine, tetraethylenepentamine on the size of Zn₂SnO₄ nanostructures were investigated. The results demonstrated that applying the appropriate amount of organic amine could be effective in particle size control. The obtained nanostructure products were specified by powder X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectra, scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX) and ultraviolet–visible (UV–vis) spectroscopy. Dye sensitized solar cells (DSSC) were created by the constructed electrodes as working electrode and then were studied by current density–voltage (J–V) curve. It was found that incorporating of TiO₂ nanoparticles to optimized Zn₂SnO₄ nanostructures has significant role on the constructed DSSCs photovoltaic properties.