## 3 Results and Discussion
### Electrochemical Assessment  
#### 3.2.1 AEN Assessments  
Although the wrought sheet and LPBF samples showed differences in AEN assessments (Figure 3), both samples presented fluctuations in OCP (Figure 3a) and ZRA (Figure 3b). The metastable pitting generates activation/passivation cycles, causing the fluctuation on both signals [12]. The wrought sheet samples had high peaks in current  
Figure 1: SEM images of the wrought sheet (**a**) and (**b**), and LPBF (**c**,d**) 316L SS microstructure.  
Figure 2: EDS mapping of the wrought sheet (**a**) and LPBF (**b**) samples before the corrosion.  
density (Figure 3b), indicating the presence of large pitting. The size of the pitting is proportional to the current density peak size [13]. The absence of these peaks on LPBF samples also indicates a high corrosion resistance. The voltage was increased over the time while the current density was reduced, meaning the corrosion resistance was increasing with the time for both samples. The growth of the passive film with time on the samples decreases the chemical activity, as the corrosion resistance is proportional to the passive film thickness [7]. The potential of the LPBF samples was higher than that for the wrought sheet 316L SS, whilst the current density showed the opposite behaviour. This also means that the LPBF samples possessed higher corrosion resistance.  
The corrosion features from AEN analyses can be seen in Table 1. The noise resistance (\(R_{n}\)) of the LPBF samples was higher than the wrought sheet sample \(R_{n}\), indicating the higher corrosion resistance of the LPBF 316L SS. The corrosion rate is inversely proportional to \(R_{n}\). The larger grain size of the LPBF sample increases the corrosion resistance due to the diminishing of the grain boundary area fraction. The grain is the anodic area, and the boundary is the cathodic area. The corrosion resistance is proportional to the anode/cathode area ratio [14]. \(R_{n}\) was calculated with the Equation (1) [15].  
\[R_{n}=\frac{\sigma_{E}}{\sigma_{I}} \tag{1}\]  
where \(\sigma_{E}\) and \(\sigma_{I}\) are the standard deviations of the potential and current density, respectively. The current density root mean square (\(I_{R.M.S}\)) presented opposite behaviour to that of \(R_{n}\) because this feature is inversely proportional to noise resistance.  
The localised index (\(L.I\)) of both samples was between 0.1 and 1.0, indicating the corrosion type was mixed (localised and uniform) for both samples. The \(L.I\) value indicates the type of the corrosion, with <0.1 indicating uniform, from 0.1 to 1.0 indicating mixed, and >1.0 indicating localised [15]. \(L.I.\) was determined using Equation (2) [15].  
\[L.I.=\frac{\sigma_{I}}{I_{R.M.S}} \tag{2}\]  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Samples** & \(\sigma_{I}\) **(nA/cm2)** & \(\sigma_{E}\) **(mV)** & \(R_{n}\) **(k\(\Omega\)/cm2)** & \(I_{R.M.S}\) **(nA/cm2)** & **\(L.I.\)** \\ \hline Wrought & 66 & 4 & 62 & 130 & 0.55 \\ \hline LPBF & 40 & 3 & 97 & 64 & 0.97 \\ \hline \end{tabular}
\end{table}
Table 1: Corrosion features of the LPBF and commercial samples obtained with AEN.  
Figure 3: AEN analyses of the wrought sheet and LPBF samples for 2 h of immersion in 0.6 M NaCl. OCP (**a**) and ZRA (**b**).