High-throughput analysis of contact angle goniometry data using DropPy

被引:4
|
作者
Orella, Michael Julian [1 ]
Leonard, McLain Evan [1 ]
Roman-Leshkov, Yuriy [1 ]
Brushett, Fikile Richard [1 ]
机构
[1] MIT, Dept Chem Engn, 77 Massachusetts Ave, Cambridge, MA 02141 USA
基金
美国国家科学基金会;
关键词
Contact angle goniometry; High-throughput image analysis; Automatic edge detection; SURFACE-TENSION; WATER MANAGEMENT; WETTABILITY; PENDANT; !text type='PYTHON']PYTHON[!/text; LAYERS;
D O I
10.1016/j.softx.2021.100665
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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. (C) 2021 The Author(s). Published by Elsevier B.V.
引用
收藏
页数:8
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