Skip to main content
Log in

Experimental and numerical study on plasma nitriding of AISI P20 mold steel

  • Published:
International Journal of Minerals, Metallurgy, and Materials Aims and scope Submit manuscript

Abstract

In this study, plasma nitriding was used to fabricate a hard protective layer on AISI P20 steel, at three process temperatures (450°C, 500°C, and 550°C) and over a range of time periods (2.5, 5, 7.5, and 10 h), and at a fixed gas N2:H2 ratio of 75vol%:25vol%. The morphology of samples was studied using optical microscopy and scanning electron microscopy, and the formed phase of each sample was determined by X-ray diffraction. The elemental depth profile was measured by energy dispersive X-ray spectroscopy, wavelength dispersive spectroscopy, and glow dispersive spectroscopy. The hardness profile of the samples was identified, and the microhardness profile from the surface to the sample center was recorded. The results show that ε-nitride is the dominant species after carrying out plasma nitriding in all strategies and that the plasma nitriding process improves the hardness up to more than three times. It is found that as the time and temperature of the process increase, the hardness and hardness depth of the diffusion zone considerably increase. Furthermore, artificial neural networks were used to predict the effects of operational parameters on the mechanical properties of plastic mold steel. The plasma temperature, running time of imposition, and target distance to the sample surface were all used as network inputs; Vickers hardness measurements were given as the output of the model. The model accurately reproduced the experimental outcomes under different operational conditions; therefore, it can be used in the effective simulation of the plasma nitriding process in AISI P20 steel.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. D.C. Wen, Microstructure and corrosion resistance of the layers formed on the surface of precipitation hardenable plastic mold steel by plasma-nitriding, App. Surf. Sci., 256(2009), No. 3, p. 797.

    Article  Google Scholar 

  2. H. Liu, J.C. Li, F. Sun, and J. Hu, Characterization and effect of pre-oxidation on D.C. plasma nitriding for AISI4140 steel, Vacuum, 109(2014), p. 170.

    Article  Google Scholar 

  3. G.X. Pang, Z.L. Li, and Z.Y. Chen, Research on plasma nitriding temperature effect on wear resistance of Cr12MoV steel, Phys. Procedia, 50(2013), p. 120.

    Article  Google Scholar 

  4. A.P.A. Manfridini, C. Godoy, J.C. Avelar-Batista Wilson, and M.V. Auad, Surface hardening of IF steel by plasma nitriding: effect of a shot peening pre-treatment, Surf. Coat. Technol., 260(2014), p. 168.

    Article  Google Scholar 

  5. R. Mohammadzadeh, A. Akbari, and M. Drouet, Microstructure and wear properties of AISI M2 tool steel on RF plasma nitriding at different N2-H2 gas compositions, Surf. Coat. Technol., 258(2014), p. 566.

    Article  Google Scholar 

  6. K. Shetty, S. Kumar, and P.R. Rao, Effect of plasma nitriding on the microstructure and properties of Maraging steel (250 Grade), Surf. Coat. Technol., 203(2009), No. 10-11, p. 1530.

    Article  Google Scholar 

  7. M.H. Sohi, M. Ebrahimi, A.H. Raouf, and F. Mahboubi, Comparative study of the corrosion behaviour of plasma nitrocarburised AISI 4140 steel before and after post-oxidation, Mater. Des., 31(2010), No. 9, p. 4432.

    Article  Google Scholar 

  8. S.M.Y. Soleimani, A.R. Mashreghi, S.S. Ghasemi, and M. Moshrefifar, The effect of plasma nitriding on the fatigue behavior of DIN 1.2210 cold work tool steel, Mater. Des., 35(2012), p. 87.

    Article  Google Scholar 

  9. S.Y. Sirin and E. Kaluc, Structural surface characterization of ion nitrided AISI 4340 steel, Mater. Des., 36(2012), p. 741.

    Article  Google Scholar 

  10. Sh. Ahangarani, F. Mahboubi, and A.R. Sabour, Effects of various nitriding parameters on active screen plasma nitriding behavior of a low-alloy steel, Vacuum, 80(2006), p. 1032.

    Article  Google Scholar 

  11. W.M. Ke, F.C. Zhang, Z.N. Yang, and M. Zhang, Micro-characterization of macro-sliding wear for steel, Mater. Charact., 82(2013), p.120.

    Article  Google Scholar 

  12. G. Kranthi and A. Satapathy, Evaluation and prediction of wear response of pine wood dust filled epoxy composites using neural computation, Comput. Mater. Sci., 49(2010), No. 3, p. 609.

    Article  Google Scholar 

  13. M. Vasudevan, B.P.C. Rao, B. Venkatraman, T. Jayakumar, and B. Raj, Artificial neural network modelling for evaluating austenitic stainless steel and Zircaloy-2 welds, J. Mater. Process. Technol., 169(2005), No. 3, p. 396.

    Article  Google Scholar 

  14. Z.Y. Jiang, L. Gyurova, Z. Zhang, K. Friedrich, and A.K. Schlarb, Neural network based prediction on mechanical and wear properties of short fibers reinforced polyamide composites, Mater. Des., 29(2008), No. 3, p. 628.

    Article  Google Scholar 

  15. S.S. Behzadi, C. Prakasvudhisarn, J. Klocker, P. Wolschann, and H. Viernstein, Comparison between two types of artificial neural networks used for validation of pharmaceutical processes, Powder Technol., 195(2009), No. 2, p. 150.

    Article  Google Scholar 

  16. M.S. Ozerdem and S. Kolukisa, Artificial neural network approach to predict the mechanical properties of Cu–Sn–Pb–Zn–Ni cast alloys, Mater. Des., 30(2009), No. 3, p. 764.

    Article  Google Scholar 

  17. A. Fotovati and T. Goswami, Prediction of elevated temperature fatigue crack growth rates in Ti–6Al–4V alloy: neural network approach, Mater. Des., 25(2004), No. 7, p. 547.

    Article  Google Scholar 

  18. M. Reihanian, S.R. Asadullahpour, S. Hajarpour, and K. Gheisari, Application of neural network and genetic algorithm to powder metallurgy of pure iron, Mater. Des., 32(2011), No. 6, p. 3183.

    Article  Google Scholar 

  19. C. Sanjay, M.L. Neema, and C.W. Chin, Modeling of tool wear in drilling by statistical analysis and artificial neural network, J. Mater. Process. Technol., 170(2005), No. 3, p. 494.

    Article  Google Scholar 

  20. Y.Y. Yang, D.A. Linkens, and J. Talamantes-Silva, Roll load prediction: data collection, analysis and neural network modelling, J. Mater. Process. Technol., 152(2004), No. 3, p. 304.

    Article  Google Scholar 

  21. K. Dehghani and A. Nekahi, Artificial neural network to predict the effect of thermomechanical treatments on bake hardenability of low carbon steels, Mater. Des., 31(2010), No. 4, p. 2224.

    Article  Google Scholar 

  22. Ó. Martín, M. López, and F. Martín, Artificial neural networks for quality control by ultrasonic testing in resistance spot welding, J. Mater. Process. Technol., 183(2007), No. 2–3, p. 226.

    Article  Google Scholar 

  23. H. Chandler, Heat Treater's Guide: Practices and Procedures for Irons and Steels, 2nd Ed., ASM international, 1995, p. 432.

    Google Scholar 

  24. D.R. Askeland, P.P. Fulay and W.J. Wright, The Science and Engineering of Materials, Cengage Learning, Stamford, 2010, p. 290.

    Google Scholar 

  25. P. Shewmon, Diffusion in Solids, Wiley, 1991, p. 186.

    Google Scholar 

  26. H. Forati Rad, A. Amadeh, and H. Moradi, Wear assessment of plasma nitrided AISI H11 steel, Mater. Des., 32(2011), No. 5, p. 2635.

    Article  Google Scholar 

  27. M. Soltanieh, H. Aghajani, F. Mahboubi, and Kh.A. Nekouee, Surface characterization of multiple coated H11 hot work tool steel by plasma nitriding and hard chromium electroplating processes, Vacuum, 86(2012), No. 10, p. 1470.

    Article  Google Scholar 

  28. P. Corengia, G. Ybarra, C. Moina, A. Cabo, and E. Broitman, Microstructural and topographical studies of DC-pulsed plasma nitrided AISI 4140 low-alloy steel, Surf. Coat. Technol., 200(2005), No. 7, p. 2391.

    Article  Google Scholar 

  29. I. Calliari, M. Dabalà, E. Ramous, M. Zanesco, and E. Gianotti, Microstructure of a nitrided steel previously decarburized, J. Mater. Eng. Perform., 15(2006), No. 6, p. 693.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to N. Nayebpashaee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nayebpashaee, N., Vafaeenezhad, H., Kheirandish, S. et al. Experimental and numerical study on plasma nitriding of AISI P20 mold steel. Int J Miner Metall Mater 23, 1065–1075 (2016). https://doi.org/10.1007/s12613-016-1324-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12613-016-1324-y

Keywords

Navigation