journal article·2026-05Open access

Optimization of electrochemical polishing process and corrosion resistance performance of milled surfaces in NiTi shape memory alloys

Guijie Wang, Zelin Wang, Qiang Zhang, Xiaoyue Chen, Yibo Wang, Xinyi Wang, Yaoan Song, Chengming Gong, Meng Miao, Xiaoxiao Zheng

Abstract

NiTi shape memory alloys are superior materials for artificial joints due to their exceptional corrosion resistance and biocompatibility. Consequently, the milling-electropolishing process is crucial for manufacturing high-quality medical NiTi components. This study employs orthogonal experiments and response surface methodology to investigate the interactive effects of electrochemical polishing parameters on the surface roughness ( S a) of milled NiTi alloy. Potentiodynamic polarization and electrochemical impedance spectroscopy were conducted to evaluate the corrosion behavior and mechanisms of the NiTi alloy in simulated body fluid after polishing, supported by XRD, XPS, SEM, and EDS characterizations. The results reveal that the interactive effects of the parameters on S a are ranked as follows: electrode gap-polishing time > current density-polishing time > current density-electrode gap. The optimized electrochemical polishing process reduces S a to 75.5 nm, achieving 87.9% reduction. The corrosion potential shifted positively from -0.856 V to -0.335 V, and the polarization resistance increases from 4.83×10 5 to 1.38×10 6 Ω·cm 2 . XPS and SEM results demonstrate a passive film formed after polishing, altering the corrosion mode from crevice corrosion to minor pitting corrosion. The findings provide theoretical guidance for optimizing the milling-electrochemical polishing process of medical NiTi alloy. • Clarifying the corrosion mechanism of NiTi alloy milled surface in SBF after electrochemical polishing. • The significance of interactive effects on surface roughness as follows: electrode gap-polishing time > current density-polishing time > current density-electrode gap. • Optimal process parameters were derived by second-order model optimization, yielding 87.9% reduction in surface roughness.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Shape Memory Alloy Transformations · Electrodeposition and Electroless Coatings · Nanoporous metals and alloys

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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