In this study, corrosion inhibiting properties of amino pentadecylphenols (APPs) derived from Cashew Nut Shell Liquid (CNSL) on mild steel in aerated 0.10 M HCl at 303 K were studied using Electrochemical Impedance Sp...In this study, corrosion inhibiting properties of amino pentadecylphenols (APPs) derived from Cashew Nut Shell Liquid (CNSL) on mild steel in aerated 0.10 M HCl at 303 K were studied using Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization measurements. Both methods indicated the potential of a mixture of amino pentadecyphenols to serve as a corrosion inhibitor in mild steel in 0.10 M HCl. Corrosion inhibition efficiencies were observed to increase with increase in the inhibitor concentration, with maximum corrosion inhibition of about 98% at inhibitor concentration of 600 ppm. The adsorption of the inhibitor on mild steel surface was found to obey Temkin adsorption isotherm, signifying physical adsorption of the inhibitor molecules on mild steel surface.展开更多
This work was aimed at synthesizing Cashew Nut Shell Liquid (CNSL) based polymer particles for adsorption of Cr(III) ions from aqueous solutions. Natural CNSL was used as a starting material in synthesizing amino pent...This work was aimed at synthesizing Cashew Nut Shell Liquid (CNSL) based polymer particles for adsorption of Cr(III) ions from aqueous solutions. Natural CNSL was used as a starting material in synthesizing amino pentadecylphenols (APP). This was achieved through isolating anacardic acid from the CNSL via calcium anacardate procedure, followed by hydrogenation of the alkenyl side chains, and subsequently decarboxylating the product to form 3-pentadecylphenol, which was then nitrated and reduced to a mixture of APP. APP were co-polymerized with ethylene glycol dimethacrylate (EGDMA) to form poly(APP-co-EGDMA) particles. The chemical structures of the synthesized compounds were confirmed by Fourier Transform IR and 1H-NMR. The co-polymer particles were characterized by Scanning Electron Microscopy (SEM) to establish their morphological properties. The prepared co-polymer particles were found to have-NH loading of 46 mmol/g and a maximum adsorption capacity for Cr(III) ions of 16 mg per g of dry polymer particles. The spent polymer particles were recoverable and reusable.展开更多
This paper explores the use of artificial neural networks （ANN） to predict performance, combustion and emissions of a single cylinder, four stroke stationary, diesel engine operated by thermal cracked cashew nut she...This paper explores the use of artificial neural networks （ANN） to predict performance, combustion and emissions of a single cylinder, four stroke stationary, diesel engine operated by thermal cracked cashew nut shell liquid （TC-CNSL） as the biodiesel blended with diesel. The tests were performed at three different injection timings （21°, 23°, 25℃A bTDC） by changing the thickness of the advance shim. The ANN was used to predict eight different engine-output responses, namely brake thermal efficiency （BTE）, brake specific fuel consumption （BSFC）, exhaust gas temperature （EGT）, carbon monoxide （CO）, oxide of nitrogen （NOx）, hydrocarbon （HC）, maximum pressure （Pm~,,） and heat release rate （HRR）. Four pertinent engine operating parameters, i.e., injection timing （IT）, injection pressure （IP）, blend percentage and pecentage load were used as the input parameters for this modeling work. The ANN results show that there is a good correlation between the ANN predicted values and the experimental values for various engine performances, combustion parameters and exhaust emission characteristics. The mean square error value （MSE） is 0.005621 and the regression value ofR2 is 0.99316 for training, 0.98812 for validation, 0.9841 for testing while the overall value is 0.99173. Thus the developed ANN model is fairly powerful for predicting the performance, combustion and exhaust emissions of internal combustion engines.展开更多
文摘In this study, corrosion inhibiting properties of amino pentadecylphenols (APPs) derived from Cashew Nut Shell Liquid (CNSL) on mild steel in aerated 0.10 M HCl at 303 K were studied using Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization measurements. Both methods indicated the potential of a mixture of amino pentadecyphenols to serve as a corrosion inhibitor in mild steel in 0.10 M HCl. Corrosion inhibition efficiencies were observed to increase with increase in the inhibitor concentration, with maximum corrosion inhibition of about 98% at inhibitor concentration of 600 ppm. The adsorption of the inhibitor on mild steel surface was found to obey Temkin adsorption isotherm, signifying physical adsorption of the inhibitor molecules on mild steel surface.
文摘This work was aimed at synthesizing Cashew Nut Shell Liquid (CNSL) based polymer particles for adsorption of Cr(III) ions from aqueous solutions. Natural CNSL was used as a starting material in synthesizing amino pentadecylphenols (APP). This was achieved through isolating anacardic acid from the CNSL via calcium anacardate procedure, followed by hydrogenation of the alkenyl side chains, and subsequently decarboxylating the product to form 3-pentadecylphenol, which was then nitrated and reduced to a mixture of APP. APP were co-polymerized with ethylene glycol dimethacrylate (EGDMA) to form poly(APP-co-EGDMA) particles. The chemical structures of the synthesized compounds were confirmed by Fourier Transform IR and 1H-NMR. The co-polymer particles were characterized by Scanning Electron Microscopy (SEM) to establish their morphological properties. The prepared co-polymer particles were found to have-NH loading of 46 mmol/g and a maximum adsorption capacity for Cr(III) ions of 16 mg per g of dry polymer particles. The spent polymer particles were recoverable and reusable.
文摘This paper explores the use of artificial neural networks （ANN） to predict performance, combustion and emissions of a single cylinder, four stroke stationary, diesel engine operated by thermal cracked cashew nut shell liquid （TC-CNSL） as the biodiesel blended with diesel. The tests were performed at three different injection timings （21°, 23°, 25℃A bTDC） by changing the thickness of the advance shim. The ANN was used to predict eight different engine-output responses, namely brake thermal efficiency （BTE）, brake specific fuel consumption （BSFC）, exhaust gas temperature （EGT）, carbon monoxide （CO）, oxide of nitrogen （NOx）, hydrocarbon （HC）, maximum pressure （Pm~,,） and heat release rate （HRR）. Four pertinent engine operating parameters, i.e., injection timing （IT）, injection pressure （IP）, blend percentage and pecentage load were used as the input parameters for this modeling work. The ANN results show that there is a good correlation between the ANN predicted values and the experimental values for various engine performances, combustion parameters and exhaust emission characteristics. The mean square error value （MSE） is 0.005621 and the regression value ofR2 is 0.99316 for training, 0.98812 for validation, 0.9841 for testing while the overall value is 0.99173. Thus the developed ANN model is fairly powerful for predicting the performance, combustion and exhaust emissions of internal combustion engines.
