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首页> 外文期刊>CERAMICS INTERNATIONAL >Characterization and performance prediction of jet pulse electrodeposited Ni-SiC nanocomposites by means of artificial neural networks
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Characterization and performance prediction of jet pulse electrodeposited Ni-SiC nanocomposites by means of artificial neural networks

机译:通过人工神经网络的射流电沉积Ni-SiC纳米复合材料的表征与性能预测

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摘要

In this study, Ni-SiC nanocomposites were successfully deposited on Q325 steel substrates using jet pulse electrodeposition. Morphologies, microstructures, microhardness values and corrosion properties of Ni-SiC nanocomposites were examined by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Rockwell hardness testing, and electrochemical apparatus. Microhardness and corrosion properties of Ni-SiC nanocomposites were then predicted by BP artificial neural network and compared to experimental values. Results demonstrated that as-prepared Ni-SiC nanocomposites at pulse current density of 4 A/dm(2), SiC particle concentration of 5 g/l and jet rate of 5.5 m/s exhibited maximum microhardness reaching up to similar to 884.2 HV. By contrast, Ni-SiC nanocomposite obtained at current density of 4 A/dm(2), SiC particle concentration of 5 g/l and jet rate of 5.5 m/s showed smaller racemule-like surface morphology with smooth, fine, and uniform microstructures. Average grain sizes of Ni grains and SiC nano particles were estimated to 53.4 nm and 28.7 nm, respectively. Concentrations of Ni and Si in Ni-SiC nano composite fabricated at current density of 3 A/dm(2), SiC particle concentration of 3 g/l and jet rate of 4 m/s were recorded as 71.4 at% and 11.7 at%, respectively. Corrosion current density of Ni-SiC nanocomposite deposited at current density of 4 A/dm(2), SiC particle concentration of 5 g/l and jet rate of 5.5 m/s revealed minimum corrosion current density of 5.1 x 10(-5) A/cm(2) and maximum impedance value, demonstrating the optimal anticorrosion ability. Maximum MEs of microhardness and corrosion mass loss of Ni-SiC nanocomposite predicted by proposed BP model were estimated to 3.1% and 3.4%, respectively. These findings suggested that BP model could effectively predict microhardness and corrosion mass loss of Ni-SiC nanocomposites.
机译:在该研究中,使用喷射脉冲电沉积成功地沉积在Q325钢基板上的Ni-SiC纳米复合材料。通过扫描电子显微镜(SEM),透射电子显微镜(TEM),X射线光电子能谱(XPS),罗克韦尔硬度试验和电化学装置,检查Ni-SiC纳米复合材料的形态学,微观结构,显微硬度值和腐蚀性能。然后通过BP人工神经网络预测Ni-SiC纳米复合材料的显微硬度和腐蚀性能,与实验值相比。结果证明,在脉冲电流密度为4A / dm(2)的时,SiC颗粒浓度为5g / L和射流速率为5.5m / s的喷射率达到884.2HV的最大微硬度。相比之下,在4A / DM(2)的电流密度下获得的Ni-SiC纳米复合材料,5g / L的SiC颗粒浓度和5.5m / s的喷射率呈现出较小的外壳状表面形态,具有光滑,细细和均匀微观结构。将Ni晶粒和SiC纳米颗粒的平均晶粒尺寸分别估计为53.4nm和28.7nm。 Ni-SiC纳米复合材料中的Ni和Si的浓度为3A / dm(2),SiC颗粒浓度为3g / L和4m / s的喷射率为71.4,%和11.7% , 分别。腐蚀电流密度沉积在电流密度为4a / dm(2),SiC颗粒浓度为5g / L和5.5m / s的喷射率,显示最小腐蚀电流密度为5.1×10(-5) A / cm(2)和最大阻抗值,证明了最佳的防腐能力。通过提出的BP模型预测的Ni-SiC纳米复合材料的最大微硬度和腐蚀质量损失分别估计为3.1%和3.4%。这些发现表明BP模型可以有效地预测镍氢纳米复合材料的微硬度和腐蚀质量损失。

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