FigsharePub Date : 2024-07-30DOI: 10.1021/acs.langmuir.4c01050.s001
DanielG. Shaw (19260065), Ran Liang (2033797), Tian Zheng (42929), Jianzhong Qi (13497673), Joseph D. Berry (3943193)
{"title":"Accurate andnRobust Static Hydrophobic Contact AnglenMeasurements Using Machine Learning","authors":"DanielG. Shaw (19260065), Ran Liang (2033797), Tian Zheng (42929), Jianzhong Qi (13497673), Joseph D. Berry (3943193)","doi":"10.1021/acs.langmuir.4c01050.s001","DOIUrl":"https://doi.org/10.1021/acs.langmuir.4c01050.s001","url":null,"abstract":"We present a machine learning (ML) approach to staticncontact anglenmeasurement, trained on a large data set (>7.2 million) of halfndropncontours based on solutions to the Young–Laplace equation wherenthe contact angle is known <i>a priori</i> (removing allnsources of error from human input). The data set included the effectsnof surface roughness, gravity, the size of drop relative to the image,nand reflections of the drop on the surface. The presented ML modeln(valid for contact angles >110°), in combination with a newnautomatednimage and contour processing approach, is shown to be more accuratenthan other methods when benchmarked against an experimental data set,nwith an estimated error of 1°. The ML model is also 2 ordersnof magnitude faster at predicting contact angles than Young–Laplacenfitting (the current best practice approach). The accuracy and speednof the presented approach provides a viable pathway toward robustnand reproducible high-throughput contact angle analysis. This approach,nConan-ML, is open-source and provided for the use and developmentnof new approaches to goniometry.","PeriodicalId":522452,"journal":{"name":"Figshare","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://figshare.com/articles/journal_contribution/Accurate_and_Robust_Static_Hydrophobic_Contact_Angle_Measurements_Using_Machine_Learning/26408393","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147897322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}