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

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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Publication Details

Journal
Small Methods
Published
2025-02-18
DOI
https://doi.org/10.1002/smtd.202401983
Citations
1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
2.48

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article

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

Kuniharu Takei, Naruhito Seimiya
1 citations
Small Methods
Neural Networks and Reservoir Computing
2.48
article

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

Kuniharu Takei, Naruhito Seimiya
article en
1 citations

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.

Small MethodsVol. 9(7)
Hokkaido University (JP)
Murata Science Foundation, Japan Society for the Promotion of Science, Advanced Low Carbon Technology Research and Development Program
Affordable and clean energy
Openalex Percentile: Top 12%
Neural Networks and Reservoir Computing
2.48
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Simultaneous Measurement of Surface Tension and Viscosity Using a Liquid Dynamics Sensor — Kuniharu Takei, Naruhito Seimiya · Small Methods (2025) | TGRS Research Map | TGRS