The objectives of this paper was the development of a novel ligand, L, which was achieved in two stages: ligand is synthesised by reducing the result of the reaction between cyclohexane-1,2-diamine and 4-hydroxy-3,5-dimethoxycy clohexane-1-carbaldehyde, followed by the production of the 4,4’-((1E,1’E)-(1,2 phenylenebis(azanylylidene))bis(methanylylidene))bis(2,6-dimethoxyphenol) precursor (P). While studying corrosion inhibition (copper alloy) in acid solution by weight loss, compounds were characterised using 1H, 13CNMR (for ligand (L) and (P)), FT-IR and UV spectra, melting point, molar conductivity, %C, %H and %N, %M, and magnetic susceptibility. The complex’s octahedral structure is inferred from the bidentate coordination of the metal ion. The molar ratio of type [Pt(L)Cl2 (H2 O)2 ] seemed to be 1:1(M:L). Using the weight loss method, the corrosion inhibitory ef fects of the platinum complex on copper alloy in a nitric acid solution (0.5 M HNO3 ) were studied. Adsorption of inhibitor molecules onto the surface of the copper alloy was the primary mechanism by which corrosion activity was reduced and active sites were blocked. The results demonstrated that the efficacy of inhibition was improved with increasing inhibitor concentrations. The inhibitor had its maximum inhibitory effectiveness of 97.5% at a concentration of 700 ppm. Calculated values of the Gibbs free energy corroborated with the results of adsorption investigations, which showed that the process mostly included physical adsorption and Langmuir adsorption iso therm. The development of protective coatings was validated by scanning electron microscopy analyses of surface morphology.
ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
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Management of Foreign Exchange Rate Exposure by Using Financial Hedging An Analytical Empirical Study The main purpose of this Research is to investigate the ability to reduce the effect of exchange rate fluctuation on firm value , by usage appropriate hedging strategies to provide the firms force to adopted with complex and highly uncertainty conditions , characteristic of the most of the financial markets . The field of this study is the giant five Multinational on the world. Nokia, Toyota Motor, Intel , Coca Cola, Microsoft. practical analysis is provide the truth of all study's hypothesis , and it is reach to many of conclusion, the most important of them is Stem from unexpected fluctuation on nominal ex
... Show MoreAn analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.
Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95
... Show MoreThis research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered
... Show MoreThis study included the extraction properties of spatial and morphological basins studied using the Soil and Water Assessment Tool (SWAT) model linked to (GIS) to find the amount of sediment and rates of flow that flows into the Haditha reservoir . The aim of this study is determine the amount of sediment coming from the valleys and flowing into the Haditha Dam reservoir for 25 years ago for the period (1985-2010) and its impact on design lifetime of the Haditha Dam reservoir and to determine the best ways to reduce the sediment transport. The result indicated that total amount of sediment coming from all valleys about (2.56 * 106 ton). The maximum annual total sediment load was about (488.22 * 103 ton) in year 1988
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Development and population expansion have the lion's share of driving up the fuel cost. Biodiesel has considerable attention as a renewable, ecologically friendly and alternative fuel source. In this study, CaO nanocatalyst is produced from mango leaves as a catalysis for the transesterification of waste cooking oil (WCO) to biodiesel. The mango tree is a perennial plant, and its fruit holds significant economic worth due to its abundance of vitamins and minerals. This plant has a wide geographical range and its leaves can be utilized without any negative impact on its growth and yield. An analysis was conducted to determine the calcium content in the fallen leaves, revealing a significant quantity of calcium that holds potential fo
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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