Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

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

dc.contributor.authorAfifi, Ahmed S.en
dc.contributor.authorWeerasinghe, Janithen
dc.contributor.authorPrasad, Karthikaen
dc.contributor.authorLevchenko, Igoren
dc.contributor.authorAlexander, Katiaen
dc.date.accessioned2026-06-11T09:40:45Z
dc.date.available2026-06-11T09:40:45Z
dc.date.issued2025en
dc.description.abstractErosion 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.en
dc.description.sponsorshipThis work was supported by the ARC Future Fellowship [grant number FT190100819]. This work used the ACT node of the NCRIS-enabled Australian National Fabrication Facility (ANFF-ACT). The authors acknowledge the support from the Australian Research Council (FT190100819) and The Australian National University Futures Scheme.en
dc.description.statusPeer-revieweden
dc.identifier.otherORCID:/0000-0002-2215-7450/work/217154289en
dc.identifier.scopus105010469228en
dc.identifier.urihttps://hdl.handle.net/1885/733810725
dc.language.isoenen
dc.rightsPublisher Copyright: © 2025 by the authors.en
dc.sourceNanomaterialsen
dc.subjectboron nitride erosionen
dc.subjecterosion mappingen
dc.subjectimage registration algorithmen
dc.subjectiodine and argon plasmaen
dc.subjectplasma–material interactionen
dc.subjectsurface morphology evolutionen
dc.titleEfficient Image Processing Technique for Detecting Spatio-Temporal Erosion in Boron Nitride Exposed to Iodine Plasmaen
dc.typeJournal articleen
dspace.entity.typePublicationen
local.contributor.affiliationAfifi, Ahmed S.; Australian National Universityen
local.contributor.affiliationWeerasinghe, Janith; School of Engineering, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationPrasad, Karthika; School of Engineering, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationLevchenko, Igor; Nanyang Technological Universityen
local.contributor.affiliationAlexander, Katia; School of Engineering, ANU College of Systems and Society, The Australian National Universityen
local.identifier.citationvolume15en
local.identifier.doi10.3390/nano15130961en
local.identifier.pure7cdf8c5c-ef0c-4f50-a026-9b3ff285431cen
local.identifier.urlhttps://www.scopus.com/pages/publications/105010469228en
local.type.statusPublisheden

Downloads