Study on plating parameters for preparing Ni-TiN nanocoatings by using Artificial Neural Networks

DOI

10.2991/msmee-17.2017.237How to use a DOI?

Keywords

Plating parameter; Ni-TiN nanocoating; Forecast; Artificial Neural Networks

Abstract

Ni-TiN nanocoatings were successfully synthesized on the surface of 45 steel substrates by using ultrasonic-electrodeposition method. The plating parameters for preparing Ni-TiN nanocoatings were optimized by using an artificial neural network (ANN) basing on the orthogonal test. And the morphologies of the coatings were investigated via scanning electron microscope (SEM). The results indicated that the optimal synthetic conditions were determined as follows: the concentration of TiN nanoparticles 7.5 g/L, the current density 5 A/dm2, the duty cycle 3:2, the concentration of surfactants 80 mg/L and the ultrasonic power 250 W. The Ni-TiN nanocoating prepared under the optimal synthetic conditions had a compact and fine microstructure which the average grain size of nano TiN was 80 nm, and the surface roughness was 14.6 nm.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fafeng Xia
AU  - Wanchun Jia
AU  - Chunyang Ma
PY  - 2017/05
DA  - 2017/05
TI  - Study on plating parameters for preparing Ni-TiN nanocoatings by using Artificial Neural Networks
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 1261
EP  - 1264
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.237
DO  - 10.2991/msmee-17.2017.237
ID  - Xia2017/05
ER  -