New metrics for describing atomic force microscopy data of nanostructured surfaces through topological data analysis

• Published in: Applied surface science 2024-10, Vol.670, p.160640, Article 160640
• Main Authors: Aglikov, Aleksandr S., Zhukov, Mikhail V., Aliev, Timur A., Kozodaev, Dmitry A., Nosonovsky, Michael, Skorb, Ekaterina V.
• Format: Article
• Language: English
• Subjects: Atomic force microscopy; Nanostructured surfaces; Topography; Topological data analysis
• ISSN: 0169-4332; 1873-5584
• DOI: 10.1016/j.apsusc.2024.160640

By leveraging this novel approach, researchers will delve deeper into the nuances of surface topography, providing a more nuanced understanding of the intricate features present. Moreover, it will enable scientists to discern subtle variations between surfaces, thereby enhancing our ability to characterize and differentiate diverse materials and structures at the nanoscale level. [Display omitted] •In this paper, we introduce a comprehensiveapproach designed specifically for the TDA of AFM data.•The primary objective of this approach is to offer an enhanced and intricate depiction of surface topography characteristics.•Through the utilization of TDA techniques, our proposed approach aims to construct a distinct “fingerprint” of these AFM data sets.•This unique topological signature serves as a new way for comparative analysis between various surfaces.•It facilitates the comparison process by employing calculations of bottleneck and q-Wasserstein distances.•These metrics play a pivotal role in quantifying the dissimilarities and similarities between different surface profiles. The nanoscale topographic features of surfaces, such as vertical, lateral, and multiscale structures, are essential for understanding and identifying correlations with properties in various applications. These features are critical in applications ranging from biomedical devices to electronic components, as they play a significant role in determining the functionality of these systems. Despite the capabilities of traditional surface analysis methods, which rely on standard vertical profile and area measurements, these techniques often fail to capture the subtle and specific features that differentiate between surfaces with different morphologies. To address this challenge, this paper proposes applying of a topological data analysis of atomic force microscopy data to create a unique topological signature for each surface. This approach can help us better understand complex relationships between topography and functional characteristics in various applications and enable further advanced surface comparison.