Effect of Bionic Surface Architecture and Ultrasonic Power Density on Wear Resistance of Ni–AlN Nanoparticle-Reinforced Composite Coatings

First, three bionic surface architectures (pit, hexagonal, and coupled) were compared to identify the optimal geometry; subsequently, the effect of ultrasonic power density (UPD, 0–35 W/cm2) on coating microstructure and dry-sliding wear performance was evaluated on the selected coupled structure. In this study, using dung beetle pit structures and many-banded krait hexagonal dorsal scales as bio-inspiration, pit-type (S1), hexagonal-type (S2), and coupled-type (S3) Ni–AlN nanocomposite coatings were deposited on AISI 1045 carbon structural steel by ultrasonic-assisted jet electrodeposition. The effect of ultrasonic power density (UPD, 0–35 W/cm2) on coating microstructure and dry-sliding wear performance was investigated by combining ANSYS finite element simulation with tribological experiments (ASTM G133). The coupled structure (S3) reduced peak contact stress by 45.8% and cumulative wear volume by 11.4%. At UPD = 25 W/cm2, AlN nanoparticles (43.6 nm) were uniformly dispersed, Ni grains were refined to 32.5 nm, and the coating achieved a microhardness of 794 ± 22 HV, a COF of 0.32 ± 0.01, and the lowest wear loss rate among the tested UPD conditions (approximately 0.025% mass loss). Hall–Petch analysis (R2 = 0.96) supports an important contribution of grain refinement to coating strengthening, with a smaller contribution from Orowan strengthening. This work provides a bio-inspired morphology–nanoparticle reinforcement approach for surface wear protection of carbon structural steel.

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Journal
Materials
Published
2026-10-28
DOI
https://doi.org/10.3390/ma19214552
Primary Topic
Electrodeposition and Electroless Coatings
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article
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article

Effect of Bionic Surface Architecture and Ultrasonic Power Density on Wear Resistance of Ni–AlN Nanoparticle-Reinforced Composite Coatings

Chenglin Miao, Honbin Zhang, Rui Liu, C. Zhao et al.
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Materials
Electrodeposition and Electroless Coatings
article

Effect of Bionic Surface Architecture and Ultrasonic Power Density on Wear Resistance of Ni–AlN Nanoparticle-Reinforced Composite Coatings

Chenglin Miao, Honbin Zhang, Rui Liu, C. Zhao, Shuting Li, Shutong Yao
article en

Abstract

First, three bionic surface architectures (pit, hexagonal, and coupled) were compared to identify the optimal geometry; subsequently, the effect of ultrasonic power density (UPD, 0–35 W/cm2) on coating microstructure and dry-sliding wear performance was evaluated on the selected coupled structure. In this study, using dung beetle pit structures and many-banded krait hexagonal dorsal scales as bio-inspiration, pit-type (S1), hexagonal-type (S2), and coupled-type (S3) Ni–AlN nanocomposite coatings were deposited on AISI 1045 carbon structural steel by ultrasonic-assisted jet electrodeposition. The effect of ultrasonic power density (UPD, 0–35 W/cm2) on coating microstructure and dry-sliding wear performance was investigated by combining ANSYS finite element simulation with tribological experiments (ASTM G133). The coupled structure (S3) reduced peak contact stress by 45.8% and cumulative wear volume by 11.4%. At UPD = 25 W/cm2, AlN nanoparticles (43.6 nm) were uniformly dispersed, Ni grains were refined to 32.5 nm, and the coating achieved a microhardness of 794 ± 22 HV, a COF of 0.32 ± 0.01, and the lowest wear loss rate among the tested UPD conditions (approximately 0.025% mass loss). Hall–Petch analysis (R2 = 0.96) supports an important contribution of grain refinement to coating strengthening, with a smaller contribution from Orowan strengthening. This work provides a bio-inspired morphology–nanoparticle reinforcement approach for surface wear protection of carbon structural steel.

MaterialsVol. 19(21)
Qiqihar University (CN)
Openalex Percentile: Top 24%
Electrodeposition and Electroless Coatings
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Effect of Bionic Surface Architecture and Ultrasonic Power Density on Wear Resistance of Ni–AlN Nanoparticle-Reinforced Composite Coatings — Chenglin Miao, Honbin Zhang, et al. · Materials (2026) | TGRS Research Map | TGRS