Corrosion resistance and microstructure evolution correlation in Zn-6%Mg-x%Al coatings

In this research, Zn-6%Mg-x%Al (x = 15∼22) coatings were prepared using a laboratory-scale simulator. Their properties were characterized by NSS tests, electrochemical measurements, microstructural analysis, and SKPFM. The NSS test data revealed that the corrosion resistance of the Zn-6%Mg-x%Al coatings did not improve continuously with increase aluminum content. The Zn-6%Mg-19%Al coating exhibited the best corrosion resistance, showing no red rust after 2400 h of testing. To further identify the coating with the optimal corrosion resistance, electrochemical measurements were performed on four selected coatings. The results showed that Zn-6%Mg-19%Al coating exhibited the lowest corrosion current density (915 μA/cm 2 ). While previous studies have primarily focused on corrosion products, the key distinction of this work is that it elucidates the corrosion mechanism from the perspective of microstructural constituency. Microstructural analysis revealed that the dendrites consist of an α-Al core and a shell of Zn-Al eutectoid microstructure. The volume fraction of this core-shell dendritic structure was found to determine the corrosion resistance of the Zn-6%Mg-x%Al coatings. SKPFM measurements demonstrated that the Volta potential of α-Al phase in the dendritic core was −567 mV, which is higher than that of Zn (−653 mV). In contrast, the Zn-Al eutectoid structure in the dendritic shell exhibited the lowest Volta potential of −711 mV. The Zn-6%Mg-19%Al coating achieves its optimal corrosion resistance by balancing the area ratios of the α-Al dendritic core and the Zn-Al eutectoid shell.

Authors

Institutions

Publication Details

Journal
Surface Engineering
Published
2026-04-17
DOI
https://doi.org/10.1177/02670844261441482
Primary Topic
Magnesium Alloys: Properties and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Corrosion resistance and microstructure evolution correlation in Zn-6%Mg-x%Al coatings

J Zhang, Y Q Li, Zhao Li, She-ming Jiang
Surface Engineering
Magnesium Alloys: Properties and Applications
article

Corrosion resistance and microstructure evolution correlation in Zn-6%Mg-x%Al coatings

J Zhang, Y Q Li, Zhao Li, She-ming Jiang
article en

Abstract

In this research, Zn-6%Mg-x%Al (x = 15∼22) coatings were prepared using a laboratory-scale simulator. Their properties were characterized by NSS tests, electrochemical measurements, microstructural analysis, and SKPFM. The NSS test data revealed that the corrosion resistance of the Zn-6%Mg-x%Al coatings did not improve continuously with increase aluminum content. The Zn-6%Mg-19%Al coating exhibited the best corrosion resistance, showing no red rust after 2400 h of testing. To further identify the coating with the optimal corrosion resistance, electrochemical measurements were performed on four selected coatings. The results showed that Zn-6%Mg-19%Al coating exhibited the lowest corrosion current density (915 μA/cm 2 ). While previous studies have primarily focused on corrosion products, the key distinction of this work is that it elucidates the corrosion mechanism from the perspective of microstructural constituency. Microstructural analysis revealed that the dendrites consist of an α-Al core and a shell of Zn-Al eutectoid microstructure. The volume fraction of this core-shell dendritic structure was found to determine the corrosion resistance of the Zn-6%Mg-x%Al coatings. SKPFM measurements demonstrated that the Volta potential of α-Al phase in the dendritic core was −567 mV, which is higher than that of Zn (−653 mV). In contrast, the Zn-Al eutectoid structure in the dendritic shell exhibited the lowest Volta potential of −711 mV. The Zn-6%Mg-19%Al coating achieves its optimal corrosion resistance by balancing the area ratios of the α-Al dendritic core and the Zn-Al eutectoid shell.

Surface Engineering
China Iron and Steel Research Institute Group (CN)
Openalex Percentile: Top 11%
Magnesium Alloys: Properties and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.