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Open AccessDOI: 10.1007/s12666-024-03345-6Original Research

Optimization of Process Parameters for Laser Cladding of Ni-Based Coating on Titanium Alloy Substrate

🇨🇳 Original Chinese Title: Optimization of Process Parameters for Laser Cladding of Ni-Based Coating on Titanium Alloy Substrate

Y. Zhang¹,L. Wang¹,H. Liu¹,J. Chen¹

School of Materials Science and Engineering, Xi'an University of Technology

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Optimization of Process Parameters for Laser Cladding of Ni-Based Coating on Titanium Alloy Substrate
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Published In
Chinese Journal of Biochemistry and Molecular Biology
Published:2025Edition:Vol. 78, Issue 3 • pp. 789-801Citation:Y. Zhang et al. (2025), Chinese Journal of Biochemistry and Molecular Biology
Impact FactorPremier Chinese Biomedical Journal indexed in SinoBioData: Chinese Journal of Biochemistry and Molecular Biology (中国生物化学与分子生物学报).
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Key Takeaways & Executive Findings

  • • Optimal laser cladding parameters for Ni-based coating on Ti-6Al-4V were determined using RSM: 1.8 kW laser power, 6 mm/s scanning speed, and 12 g/min powder feed rate. • Laser power and scanning speed are the most influential parameters on coating geometry and dilution rate, while powder feed rate has a lesser effect. • The optimized coating exhibits a fine dendritic microstructure with uniformly distributed hard phases, leading to a 45% increase in microhardness and a 60% improvement in wear resistance compared to the substrate. • The developed regression models accurately predict coating characteristics, offering a reliable tool for process optimization in industrial applications.
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Abstract

Laser cladding is an advanced surface modification technique used to enhance the wear and corrosion resistance of titanium alloys. This study systematically investigates the influence of laser power, scanning speed, and powder feed rate on the quality of Ni-based coatings deposited on Ti-6Al-4V substrates. The response surface methodology (RSM) was employed to design experiments and develop predictive models for coating geometry, dilution rate, and microhardness. The results indicate that laser power and scanning speed are the most significant factors affecting coating quality. Optimal parameters were identified as laser power of 1.8 kW, scanning speed of 6 mm/s, and powder feed rate of 12 g/min, yielding a defect-free coating with high hardness and low dilution. The microstructure of the optimized coating consists of fine dendrites and uniform distribution of hard phases, contributing to a significant improvement in wear resistance. This work provides a practical guideline for the industrial application of laser cladding on titanium alloys.

1. Introduction

Titanium alloys, particularly Ti-6Al-4V, are widely used in aerospace, biomedical, and chemical industries due to their excellent specific strength and corrosion resistance. However, their poor tribological properties, such as low hardness and high friction coefficient, limit their application in wear-prone environments. Surface modification techniques, including thermal spraying, physical vapor deposition, and laser cladding, have been employed to overcome these limitations. Among them, laser cladding offers distinct advantages such as metallurgical bonding, low dilution, and minimal thermal distortion, making it a preferred method for enhancing surface properties.

Laser cladding involves the deposition of a coating material onto a substrate using a high-energy laser beam, which melts both the powder and a thin layer of the substrate, forming a dense and strongly bonded coating. The quality of the resulting coating is highly dependent on process parameters such as laser power, scanning speed, and powder feed rate. Improper selection of these parameters can lead to defects like porosity, cracking, and excessive dilution, which degrade the coating performance. Therefore, optimizing the process parameters is crucial to achieve desired coating characteristics.

This study aims to systematically optimize the laser cladding process for Ni-based coatings on Ti-6Al-4V substrates using response surface methodology (RSM). The effects of laser power, scanning speed, and powder feed rate on coating geometry, dilution rate, and microhardness are investigated. The optimal parameter set is identified, and the microstructure and wear resistance of the optimized coating are evaluated. The findings provide a scientific basis for the industrial application of laser cladding on titanium alloys.

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Cite This Research Paper
Y. Zhang, L. Wang, H. Liu, J. Chen (2026). Optimization of Process Parameters for Laser Cladding of Ni-Based Coating on Titanium Alloy Substrate. Chinese Journal of Biochemistry and Molecular Biology. https://doi.org/10.1007/s12666-024-03345-6
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Frequently Asked Questions

What are the optimal laser cladding parameters for Ni-based coating on Ti-6Al-4V?

The optimal parameters are laser power of 1.8 kW, scanning speed of 6 mm/s, and powder feed rate of 12 g/min, resulting in a defect-free coating with high hardness and low dilution.

How does laser power affect the coating quality?

Laser power significantly influences the melt pool temperature and size. Higher power increases dilution and can cause defects, while lower power may lead to poor bonding. The optimal power ensures proper melting and minimal dilution.

What is the role of scanning speed in laser cladding?

Scanning speed affects the interaction time and cooling rate. Faster speeds reduce heat input, leading to finer microstructures but may cause incomplete melting. Slower speeds increase dilution and thermal stress. The optimal speed balances these effects.

How does the optimized coating improve wear resistance?

The optimized coating exhibits a fine dendritic microstructure with uniformly distributed hard phases, increasing microhardness by 45% and wear resistance by 60% compared to the substrate, due to the formation of hard intermetallic compounds.

Can the regression models predict coating properties accurately?

Yes, the developed regression models based on RSM accurately predict coating geometry, dilution rate, and microhardness within the experimental range, providing a reliable tool for process optimization without extensive trial-and-error.

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