In this paper, a theoretical analysis of optimum bed thickness operates under mass transfer control for realizing a high efficiency and reaction conversion of an electrochemical reactor has been made based on flowthrough porous electrode (FTPE) configuration. Many models have been used to represent the optimum bed thickness by taking a look into previous works concerned and collecting all related information, data, and models. The parameters that affect the optimum bed thickness have been visualized and reviewed, and almost all of them have been examined by experimental data from different sources and based on the various models. It has been found that the increase in electrolyte flow rate, concentration, limiting current density, and specific surface area reduce the optimum bed thickness, and the increase in electrolyte conductivity, void fraction, and overpotential range increases optimum bed thickness. The most important design parameter that has a great effect on optimum bed thickness is found to be the electrolyte flow rate for any certain operation. It has been concluded that the most appropriate two models to represent the optimum bed thickness of FTPE electrochemical reactor operating under mass transfer control based on the results are those predicted theoretically and stated by Kreysa in (1978) and Doherty et al. in (1996).
ABSTRACT:
The study aims at expounding the correlation and effect between the Human resource development strategy and Quality Municipality Service within a theoretical framework and a practical framework conducted at Directorate Of Municipalities in holy Karbala . The researcher found during a pilot study that there isn’t enough care paid by the Directorate Of Municipalities in developing its human resources using one strategy or a number of strategies and their effect on the Quality Municipality Service. Thus a number of research questions were set concerning the existence of clear perception in the Directorates Of Municipalities concerning the strategies of developing both the human resource an Qualit
... Show MoreThe Manganese doped zinc sulfide nanoparticles of the cubic zinc blende structure with the average crystallite size of about 3.56 nm were synthesized using a coprecipitation method using Thioglycolic Acid as an external capping agent for surface modification. The ZnS:Mn2+ nanoparticles of diameter 3.56 nm were manufactured through using inexpensive precursors in an efficient and eco-friendly way. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy are used to examine the structure, morphology and chemical composition of the nanoparticles. The antimicrobial activity of (ZnS:Mn2+) nanocrystals was investigated by measuring the diameter of inhibition zone using well diffusion mechanism
... Show MorePromoting the production of industrially important aromatic chloroamines over transition-metal nitrides catalysts has emerged as a prominent theme in catalysis. This contribution provides an insight into the reduction mechanism of p-chloronitrobenzene (p-CNB) to p-chloroaniline (p-CAN) over the γ-Mo2N(111) surface by means of density functional theory calculations. The adsorption energies of various molecularly adsorbed modes of p-CNB were computed. Our findings display that, p-CNB prefers to be adsorbed over two distinct adsorption sites, namely, Mo-hollow face-centered cubic (fcc) and N-hollow hexagonal close-packed (hcp) sites with adsorption energies of −32.1 and −38.5 kcal/mol, respectively. We establish that the activation of nit
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed
... Show MoreThe present study aimed to assess the potential impact of serum concentration of undercarboxylated osteocalcin (the active form of osteocalcin) and fibroblast growth factor-23 on the incidence of cardiovascular diseases in type 2 diabetics with carotid artery calcification and the possible association with metabolic changes in relation to glucose and minerals homeostasis.
This study included 52 men with carotid artery calcification type 2 diabetes mellitus. These patients were categorized; as follows: group A includes 30 patients who had cardiovascular disease and group B includes 22 patients who had no cardiovascular disease. These groups were compared with 25 apparently healthy control (Group C).
It has been shown
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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