EXTRACTION KINETICS OF COPPER BY TRILAURYLAMMONIUM CHLORIDE IN TOLUENE FROM AQUEOUS CHLORIDE MEDIA

Abstract

The rate of extraction of copper(II) from aqueous chloride solutions by tri-n-laurylammonium chloride (TLAHC1) dissolved in toluene has been investigated. The extraction rate was evaluated as function of the chemical composition of the system. The experiments were performed by using a stirred cell with constant inter-facial area. The experiments were performed at a stirring rate of the two phases where the influence of film diffusion is minimized. The data have been interpreted by a mechanism which assumes interfacial chemical reactions between the bulk species containing copper(II) and the molecules of TLAHC1 absorbed at the interface as rate determining.     

Effect of different denture adhesives on retention of complete dentures: an in vivo study

The increase in prevalence of tooth loss with the effect of population aging produces the growing need for complete dentures. The success and acceptance of complete dentures by the patient depends on sufficient retention and stability. Therefore, denture adhesives are regularly used by denture wearers to improve the function of complete denture. We evaluated the effect of three different denture adhesives (Corega, Protefix, Fittydent) on the retention of maxillary complete denture (MCD) using with digital dynamometer (DD). For this purpose, denture adhesives were applied on MCDs of 30 participants. After chewing procedure, the force was applied at 45° to the palatal surface of denture by DD. Dislodgement force was recorded by means of Newton. There were four measurements on each patient including; group of control: Group C; Group CR: Corega; Group F: Fittydent; Group P: Protefix. The result of the study was statistically evaluated by using analysis of variance (ANOVA) and Tukey HSD test. Statistics of ANOVA showed a significant difference among all the four groups (p = 0.00, <0.05). Tukey HSD test indicated that there was a statistical difference between Group F and the other groups, but there was not a significant difference between the other groups. The highest adhesive strength value was observed in group F, the lowest in group C. Use of denture adhesives improved the retentive strength of complete denture.     

EXTRACTION OF NITRIC AND PHOSPHORIC ACIDS WITH TRIBUTYL PHOSPHATE

The extraction of nitric acid and phosphoric acid by tributyl phosphate (TBP), from solutions containing acid mixture and in the presence of nitrate salts, has been studied. The effect of the temperature on acid extraction has been also investigated. It is found that TBP extracts nitric acid preferentially to phosphoric acid, especially in the presence of nitrate salts. The coextraction of nitric acid suppresses the extraction of phosphoric acid. These results were interpreted in terms of common ion effect and variation of the activity coefficients variation in both phases. The simultaneous effects of the salts and acids on the extraction of both acids is also studied

Some tests were carried out, using process solution, to evaluate the extraction of acids. Both batch experiments and continuous tests (using mixer settler) were performed. Some flowsheets were tested in order to improve the extractivity and the selectivity of phosphoric acid. The results show the limitation of TBP for the extraction of phosphoric acid. TBP can be used to selectively extract nitric acid.     

Microwave synthesis of mesoporous Cu-Ce0.8Sm0.2O2−δ composite anode for low-temperature ceramic fuel cells

In recent year, new nanocomposite electrolytes materials have been developed for low-temperature ceramic fuel cells (CFCs). To further improve the performance of CFCs based on the nanocomposite electrolyte, compatible active anode with sufficient low polarizations is needed. To improve the performance of anode, i.e. to enlarge tripe phase boundaries (TPB), anode materials with both porous structure and phase homogeneity of metal and ceramic are preferred. In the present study, we developed a novel microwave-assisted template-, surfactant-free synthesis route for mesoporous CuO–Ce_0.8Sm_0.2O_2−δ composite anode by homogeneous precipitation of microspherical precursor in aqueous solutions followed by calcination. The composite anode sample was characterized by thermogravimetry analysis, X-ray diffraction, SEM, EDX, etc. The characterization results indicated that CuO–SDC composite anode with mesoporous structure was prepared and both SDC and CuO phases were homogenously distributed. Fuel cells have been constructed using as-prepared composite as anodes and lithiated NiO as cathode based on the SDC–carbonate nanocomposite electrolyte. Fuel cell performance tests indicated that the cell with mesoporous Cu–SDC anode had better performance than conventional Cu–SDC anode prepared by solid-state method.     

All‐pass sections with rich cascadability and IC realization suitability

In this paper, two new circuit configurations for realizing voltage‐mode (VM) all‐pass sections (APSs) are presented. The proposed circuits employ only two differential voltage current conveyors (DVCCs) and are cascadable with other VM circuits due to their high‐input and low‐output impedances. The first configuration uses a grounded resistor and a grounded capacitor without requiring matching constraints, whereas the second employs two grounded resistors and a grounded capacitor with a single matching condition. While the first configuration can realize only one all‐pass response, the second can provide inverting and non‐inverting all‐pass responses with selection of appropriate input port. Adding two grounded resistors to the proposed filters, variable gain APSs can also be obtained. As applications, two quadrature oscillators, each of which using one of the proposed all‐pass circuits, one grounded resistor and one grounded capacitor are presented. SPICE simulation results are included to verify the theory. Copyright © 2010 John Wiley & Sons, Ltd.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.