Galvanic corrosion properties of aluminum coatings on 1045 steel surface with various bias voltages
Abstract When coupling with high tensile steel in an electrolyte, aluminum alloys show elevated corrosion rates due to galvanic corrosion, resulting in severe damage to the aluminum alloy. Herein, a series of pure aluminum (Al) coatings were prepared using Direct current (DC) magnetron sputtering to investigate the influence of bias voltages on the corrosion resistance and enhancement of galvanic corrosion protection provided by these coatings. The deposited Al coatings significantly reduced the galvanic corrosion sensitivity of both steel and aluminum alloy from class E to class B levels, thereby effectively mitigating the galvanic corrosion rate. Furthermore, tafel tests, neutral salt spray tests, and immersion experiments were conducted to examine the effect of bias voltages on the anti-corrosion properties of the Al coatings. The results demonstrated that optimal anti-corrosion performance was achieved at a bias voltage of −75 V due to its dense structure and fine grains. At this bias voltage, the Al coating exhibited a corrosion current density of 9.12 × 10 −8 A cm −2 , an average galvanic current density of 0.41 μA cm −2 , and a hardness value of 0.662 GPa. This study further reveals the mechanism of improved galvanic corrosion protection offered by Al coatings under different bias voltages.
Authors
- Weiming Niu (ORCID: https://orcid.org/0009-0001-2373-9591)
- Yifan Yao (ORCID: https://orcid.org/0009-0002-9490-2111)
- Yongzhe Fan (ORCID: https://orcid.org/0000-0001-7480-1431)
- Hongwei Zhou (ORCID: https://orcid.org/0000-0002-7518-9464)
- Hao Li (ORCID: https://orcid.org/0000-0003-0513-6321)
- Minhao Zhu
Institutions
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- Surface Topography Metrology and Properties
- Published
- 2025-03-13
- DOI
- https://doi.org/10.1088/2051-672x/adc024
- Citations
- 1
- Primary Topic
- Material Properties and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.93
Funders
- National Natural Science Foundation of China
- Sichuan Province Science and Technology Support Program