High-throughput analysis of contact angle goniometry data using DropPy
| Autor: | McLain E. Leonard, Yuriy Román-Leshkov, Michael J. Orella, Fikile R. Brushett |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Interface (computing) 01 natural sciences Computational science Contact angle 03 medical and health sciences QA76.75-76.765 Software 0103 physical sciences Redundancy (engineering) Computer software 010306 general physics 030304 developmental biology computer.programming_language 0303 health sciences Data collection business.industry High-throughput image analysis Python (programming language) Automatic edge detection Computer Science Applications Characterization (materials science) Contact angle goniometry Goniometer business computer |
| Zdroj: | SoftwareX, Vol 14, Iss, Pp 100665-(2021) |
| ISSN: | 2352-7110 |
| Popis: | At present, surface wettability measurements are an underutilized segment of the characterization toolkit, in part due to the redundancy inherent in manual analysis. Even so, there have been numerous advances in contact angle data collection and analysis methods. The emergence of inexpensive and powerful hardware in increasingly small form-factors and the development of robust and versatile software packages would enable interrogation of wetting phenomena across a range of platforms. Here, we introduce DropPy, an open-source Python implementation of the classic axisymmetric drop shape analysis technique to fit droplet profiles from images while providing an easy interface through which casual users may interpret their findings. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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