The plot illustrates the distortion (sum of squared distances from points to their assigned cluster centroids) as a function of the number of clusters (𝑘). A sharp decrease in distortion is observed when increasing 𝑘 from 1 to 2, representing the most significant improvement in clustering quality. Beyond this point, additional clusters yield diminishing returns, as indicated by the more gradual reduction in distortion. Given that the primary goal of segmentation was to distinguish key differences in the passive film rather than over-segment the data, we selected 𝑘 = 2 to balance accuracy and interpretability. This choice minimizes overfitting while still capturing the essential variation in the system.