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首页> 外文期刊>Surface & Coatings Technology >Chromium carbonitride coating produced on DIN 1.2210 steel by thermo-reactive deposition technique: Thermodynamics, kinetics and modeling
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Chromium carbonitride coating produced on DIN 1.2210 steel by thermo-reactive deposition technique: Thermodynamics, kinetics and modeling

机译:通过热反应沉积技术在DIN 1.2210钢上生产的碳氮化铬涂层:热力学,动力学和模型

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摘要

A duplex surface treatment on DIN 1.2210 steel has been developed involving nitriding and followed by chromium thermo-reactive deposition (TRD) techniques. The TRD process was performed in molten salt bath at 550, 625 and 700°C for 1-14h. The process formed a thickness up to 9.5μm of chromium carbonitride coatings on a hardened diffusion zone. Characterization of the coatings by means of scanning electron microscopy (SEM) and X-ray diffraction analysis (XRD) indicates that the compact and dense coatings mainly consist of Cr(C,N) and Cr_2(C,N) phase. All the growth processes of the chromium carbonitride obtained by TRD technique followed a parabolic kinetics. Activation energy (Q) for the process was estimated to be 185.6kJ/mol of chromium carbonitride coating. A model based on genetic programming for predicting the layer thickness of duplex coating of the specimens has been presented. To construct the model, training and testing was conducted by using experimental results from 82 specimens. The data used as inputs in genetic programming models were five independent parameters consisting of the pre-nitriding time, ferro-chromium particle size, ferro-chromium weight percent, salt bath temperature and coating time. The training and testing results in genetic programming models illustrated a strong capability for predicting the layer thickness of duplex coating.
机译:已经开发出一种在DIN 1.2210钢上进行双相表面处理的方法,该方法包括氮化和铬热反应沉积(TRD)技术。 TRD过程在550、625和700°C的熔融盐浴中进行1-14h。该工艺在硬化扩散区上形成了厚度高达9.5μm的碳氮化铬涂层。利用扫描电子显微镜(SEM)和X射线衍射分析(XRD)对涂层进行表征,表明致密致密的涂层主要由Cr(C,N)和Cr_2(C,N)相组成。通过TRD技术获得的碳氮化铬的所有生长过程均遵循抛物线动力学。该工艺的活化能(Q)估计为185.6kJ / mol碳氮化铬涂层。提出了一种基于遗传程序的模型,用于预测样品的双面涂层的层厚。为了构建模型,使用82个样本的实验结果进行了训练和测试。遗传编程模型中用作输入的数据是五个独立的参数,包括预氮化时间,铬铁粒度,铬铁重量百分比,盐浴温度和涂覆时间。基因编程模型中的训练和测试结果说明了预测双面涂层厚度的强大能力。

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