Simultaneous Measurement of Surface Tension and Viscosity Using a Liquid Dynamics Sensor

IF 9.1 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2025-02-18 DOI:10.1002/smtd.202401983
Naruhito Seimiya, Kuniharu Takei
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Abstract

The dynamics of liquids upon impact with an object exhibit distinctive behaviors influenced by physical parameters such as surface tension and viscosity, which can be determined by analyzing a liquid's dynamic response. However, measuring these parameters typically requires different tools, a complicated setup, increased space, and higher costs. To streamline this process, a liquid dynamic sensor capable of simultaneously extracting surface tension and viscosity via a single-step measurement is proposed. The proposed measurement method uses a superhydrophobic sensor comprising three electrode pairs, which are fabricated using laser-induced graphene on polydimethylsiloxane. The sensor monitors time-series resistance changes triggered by liquid impact dynamics. The results show that time-series liquid dynamics on the sensor surface vary with the liquid's surface tension and viscosity, allowing for the differentiation of these properties. By implementing an echo state network algorithm, surface tension and viscosity are successfully estimated simultaneously. In addition, the system demonstrates reliable generalization capability, accurately estimating the properties of unknown liquids, which confirms the proposed sensor's robustness for simultaneous measurement of liquid physical parameters.

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用液体动力学传感器同时测量表面张力和粘度。
液体与物体碰撞时的动力学表现出受表面张力和粘度等物理参数影响的独特行为,这些物理参数可以通过分析液体的动态响应来确定。然而,测量这些参数通常需要不同的工具、复杂的设置、增加的空间和更高的成本。为了简化这一过程,提出了一种能够通过单步测量同时提取表面张力和粘度的液体动态传感器。所提出的测量方法使用由三对电极组成的超疏水传感器,这三对电极是用激光诱导石墨烯在聚二甲基硅氧烷上制成的。传感器监测由液体冲击动力学触发的时间序列阻力变化。结果表明,传感器表面的时间序列液体动力学随液体表面张力和粘度的变化而变化,从而允许这些特性的区分。通过回声状态网络算法,成功地同时估计了表面张力和黏度。此外,该系统具有可靠的泛化能力,能够准确地估计未知液体的性质,验证了该传感器对同时测量液体物理参数的鲁棒性。
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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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