Analysis of material reliability features of plasma material interactions

This work presents a statistical methodology for evaluating material surface degradation and reliability based on roughness measurements obtained from Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). Surface roughness metrics were employed to evaluate and model aluminum specimens exposed to helium plasma via a Weibull reliability method. The concordance between AFM-based and SEM-based measurements was assessed by Pearson correlation analysis. Robust and stable strong positive correlations are analyzed across both electrode configurations. For the cathode surfaces, a strong positive correlation (r = 0.99) is generated. Similarly, the updated assessment for the anode surfaces show highly consistent pattern, producing strong positive correlations for both the RMS-Ra (r = 0.992) comparisons. This finding indicates that while SEM-derived optical roughness parameters can effectively and reliably regenerate AFM observations with these experimental conditions. However, given the limited sample size (n = 3) assesed in this work, these strong statistical correlations must be interpreted with caution, as smaller sample groups are inherently susceptible to localized data sensitivity. All of the results indicate that while SEM-based analysis serves as a highly feasible, efficient, and cost-effective alternative for material screening and reliability modeling, its wide application needs carefull calibration and validation across larger experimental datasets.