{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/periodic-feature-characterization-in","title":"Periodic feature characterization in nanostructured surfaces and emulsions","arxiv_id":"2505.04057","date":"2025-05-07","proceeding":null,"authors":["André Guerra","Ziheng Wang","Samuel Mathews","Alejandro D. Rey","Kevin De France"],"abstract":"Understanding structure-function relationships is essential to advance the manufacturing of next-gen materials with desired properties and functionalities. Precise and rapid measurement of features like wrinkle size, droplet diameter, and surface roughness is essential to establishing such structure-function relationships. To this end, this work developed feature size and surface morphology characterizations through image analysis in Python and validated them with both synthetic and experimental images. Manual measurements of bio-based surfaces resulted in between 3.3% (N=50, visually simple) and 51.2% error (N=100, visually complex) compared to Python analysis results. This analysis was also used to accurately distinguish multiple feature size populations in a given image (which were missed entirely in manual measurements), and to determine the skewness and kurtosis of biological surfaces in a surface roughness map. This work contributes to a larger goal of developing a robust and computationally cheap platform to analyze complex materials to accelerate structure-function discovery.","url_abs":"https://arxiv.org/abs/2505.04057v1","url_pdf":"https://arxiv.org/pdf/2505.04057v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"periodic-feature-characterization-in","repo_url":"https://github.com/dreguerra/morpholopy","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}