Efficient Image Processing Technique for Detecting Spatio-Temporal Erosion in Boron Nitride Exposed to Iodine Plasma

一种用于检测碘等离子体处理下氮化硼时空侵蚀的高效图像处理技术

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Abstract

Erosion detection in materials exposed to plasma-generated species, such as those used for space propulsion systems, is critical for ensuring their reliability and longevity. This study introduces an efficient image processing technique to monitor the evolution of the erosion depth in boron nitride (BN) subjected to multiple cycles of iodine plasma exposure. Utilising atomic force microscopy (AFM) images from both untreated and treated BN samples, the technique uses a modified semi-automated image registration method that accurately aligns surface profiles-even after substantial erosion-and overcomes challenges related to changes in the eroded surface features. The registered images are then processed through frequency-domain subtraction to visualise and quantify erosion depth. Our technique tracks changes across the BN surface at multiple spatial locations and generates erosion maps at exposure durations of 24, 48, 72 and 84 min using both one-stage and multi-stage registration methods. These maps not only reveal localised material loss (up to 5.5 μm after 84 min) and assess its uniformity but also indicate potential re-deposition of etched material and redistribution across the surface through mechanisms such as diffusion. By analysing areas with higher elevations and observing plasma-treated samples over time, we notice that these elevated regions-initially the most affected-gradually decrease in size and height, while overall erosion depth increases. Progressive surface smoothing is observed with increasing iodine plasma exposure, as quantified by AFM-based erosion mapping. Notably, up to 89.3% of surface heights were concentrated near the mean after 72-84 min of plasma treatment, indicating a more even distribution of surface features compared to the untreated surface. Iodine plasma was compared to argon plasma to distinguish material loss during degradation between these two mechanisms. Iodine plasma causes more aggressive and spatially selective erosion, strongly influenced by initial surface morphology, whereas argon plasma results in milder and more uniform surface changes. Additional scale-dependent slope and curvature analyses confirm that iodine rapidly smooths fine features, whereas argon better preserves surface sharpness over time. Tracking such sharpness is critical for maintaining the fine structures essential to the fabrication of modern semiconductor components. Overall, this image processing tool offers a powerful and adaptable method for accurately assessing surface degradation and morphological changes in materials used in plasma-facing and space propulsion environments.

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