## 3 Results and Discussion
### Analysis of Deposited Zinc Mass and Zinc Coating Quality
#### 3.2.1 Electrolytic Zinc Coating

\begin{tabular}{c c c c c} \hline \hline
**Type of MP** & \multicolumn{4}{c}{**Hot-Dip Zinc Deposition Time (s)**} \\ \hline  & **70** & **105** & **140** & **175** & **210** \\ \hline SCB & 164.17 \(\pm\) 3.77 & 278.24 \(\pm\) 5.29 & 356.32 \(\pm\) 6.73 & 439.84 \(\pm\) 8.02 & 507.91 \(\pm\) 9.81 \\ SGB & 145.85 \(\pm\) 2.93 & 242.80 \(\pm\) 4.36 & 326.37 \(\pm\) 5.87 & 409.58 \(\pm\) 7.39 & 458.44 \(\pm\) 8.23 \\ G & 209.83 \(\pm\) 3.94 & 297.51 \(\pm\) 5.07 & 368.74 \(\pm\) 5.98 & 424.69 \(\pm\) 6.78 & 477.13 \(\pm\) 7.87 \\ E & 184.39 \(\pm\) 3.31 & 266.89 \(\pm\) 4.17 & 334.28 \(\pm\) 4.80 & 393.95 \(\pm\) 5.53 & 442.21 \(\pmcorrosion-mechanical properties of the deposited coatings, the graphical representation in Figure 9 suggests that for electroplating applications involving localized mechanical pre-treatment, the most suitable method is steel grit blasting. This is because the resulting coating thickness after steel grit blasting is statistically closest to that of the reference sample. Consequently, the outer layer of the coating is more uniform, with a smoother transition in thickness between different substrate areas compared to other mechanical pre-treatments. In technical practice, partial mechanical pre-treatment is commonly applied for the following:  
* Slag removal from weld joints. * Addressing localized corrosion damage. * Cleaning areas contaminated with residual old coatings. Additionally, results indicate that grinding produces a zinc mass increase nearly comparable to steel grit blasting. This suggests that combining these two techniques could be beneficial when applying multiple mechanical pre-treatments. From a practical perspective, steel grit blasting can be used for cleaning hard-to-reach areas (e.g., fillet welds), while grinding is better suited for easily accessible surfaces (e.g., flat rolled semi-finished products). However, it is important to note that these recommendations are based solely on coating thickness analysis. Whether similar conclusions apply to corrosion-mechanical properties will be examined in the subsequent section of this study. Experimental measurements reported in [13] demonstrated that coating adhesion was highest on substrates with the greatest average Ra roughness value, making synthetic corundum blasting the most effective mechanical pre-treatment in this regard. However, the same authors also noted that higher adhesion can be achieved on surfaces with a homogeneous texture. Based on this assertion, grinding appears to be the most effective pre-treatment method, a conclusion further supported by previous studies [32; 33]. Findings from these studies suggest the existence of an optimal roughness profile, as excessive surface roughness can lead to localized variations in coating adhesion. Ultimately, coating adhesion is a critical factor influencing both corrosion resistance and the overall effectiveness of anti-corrosion protection for the underlying substrate [34]. Figure 9: Mass increase of electrolytic zinc coating on different substrate types as a function of immersion time in the zinc bath. Further roughness analysis revealed that electrolytic zinc coating had a statistically insignificant levelling effect (Figure 10). Although a slight decrease in average Ra and Rz values was observed across all cases--likely due to the optimized zinc bath composition [24; 35]--this reduction was statistically negligible given the standard deviation values. This phenomenon can be attributed to the low electrolyte temperature used during the electrolytic plating process, which results in minimal Fe/Zn atomic diffusion [36]. Consequently, the smoothing of steel surface protrusions through diffusion does not occur. Another contributing factor is the relatively thin electrolytic zinc coating layer, typically measuring 6-20 \(\upmu\)m, which primarily replicates the underlying steel surface geometry [37]. The findings were further validated through metallographic specimen analysis (Figure 11).