Chromium carbonitride coating produced on DIN 1.2210 steel by thermo-reactive deposition technique: Thermodynamics, kinetics and modeling

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@Article{Khalaj:2013:SCT,

• author = "Gholamreza Khalaj and Ali Nazari and Seyyed Mohammad {Mousavi Khoie} and Mohammad Javad Khalaj and Hesam Pouraliakbar",
• title = "Chromium carbonitride coating produced on {DIN 1.2210} steel by thermo-reactive deposition technique: Thermodynamics, kinetics and modeling",
• journal = "Surface and Coatings Technology",
• volume = "225",
• pages = "1--10",
• year = "2013",
• keywords = "genetic algorithms, genetic programming, Gene expression programming, Duplex surface treatment, Diffusion coatings, TRD",
• ISSN = "0257-8972",
• DOI = "doi:10.1016/j.surfcoat.2013.02.030",
• URL = "http://www.sciencedirect.com/science/article/pii/S0257897213001850",
• abstract = "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 9.5micrometres of chromium carbonitride coatings on a hardened diffusion zone. Characterisation 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 Cr2(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.",

}

Genetic Programming entries for Gholamreza Khalaj Ali Nazari Seyyed Mohammad Mousavi Khoie Mohammad Javad Khalaj Hesam Pouraliakbar

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