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Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing

[Image: see text] Evaluating the presence of a slight amount of water plays a crucial role in practical applications such as the advanced detection of dew condensation and the microdetermination of perspiration and transpiration. For this purpose, we have developed a configuration for the moisture s...

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Autores principales: Mekawy, Moataz, Terada, Eiji, Inoue, Shinji, Sakamoto, Yukihiro, Kawakita, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600636/
https://www.ncbi.nlm.nih.gov/pubmed/34805710
http://dx.doi.org/10.1021/acsomega.1c05161
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author Mekawy, Moataz
Terada, Eiji
Inoue, Shinji
Sakamoto, Yukihiro
Kawakita, Jin
author_facet Mekawy, Moataz
Terada, Eiji
Inoue, Shinji
Sakamoto, Yukihiro
Kawakita, Jin
author_sort Mekawy, Moataz
collection PubMed
description [Image: see text] Evaluating the presence of a slight amount of water plays a crucial role in practical applications such as the advanced detection of dew condensation and the microdetermination of perspiration and transpiration. For this purpose, we have developed a configuration for the moisture sensor that consists of a microgalvanic cell composed of narrow metal arrays. It is inferred that the output response current arising from this sensor should depend on the geometric parameters (e.g., number, area, volume, etc.) of water droplets attaching on the sensor surface. In this study, the output current was recorded, while the microscopic images of the sensor surface were captured. The droplets on the sensor surface were analyzed manually and by computational image processing with deep learning and ImageJ. The deep learning technique shortened the processing time to 1/1000 of the manual one and was able to match 90–100% of the manual count. The results revealed that the response current increased with the total projected area of droplets bridging the galvanic-coupled arrays on the sensor surface. In addition, a straight line with relatively strong positive correlation was obtained between the response current and the total volume of the bridging droplets. These findings suggested that our sensor can be practically used to estimate the presence of a slight amount of water.
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spelling pubmed-86006362021-11-19 Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing Mekawy, Moataz Terada, Eiji Inoue, Shinji Sakamoto, Yukihiro Kawakita, Jin ACS Omega [Image: see text] Evaluating the presence of a slight amount of water plays a crucial role in practical applications such as the advanced detection of dew condensation and the microdetermination of perspiration and transpiration. For this purpose, we have developed a configuration for the moisture sensor that consists of a microgalvanic cell composed of narrow metal arrays. It is inferred that the output response current arising from this sensor should depend on the geometric parameters (e.g., number, area, volume, etc.) of water droplets attaching on the sensor surface. In this study, the output current was recorded, while the microscopic images of the sensor surface were captured. The droplets on the sensor surface were analyzed manually and by computational image processing with deep learning and ImageJ. The deep learning technique shortened the processing time to 1/1000 of the manual one and was able to match 90–100% of the manual count. The results revealed that the response current increased with the total projected area of droplets bridging the galvanic-coupled arrays on the sensor surface. In addition, a straight line with relatively strong positive correlation was obtained between the response current and the total volume of the bridging droplets. These findings suggested that our sensor can be practically used to estimate the presence of a slight amount of water. American Chemical Society 2021-11-04 /pmc/articles/PMC8600636/ /pubmed/34805710 http://dx.doi.org/10.1021/acsomega.1c05161 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Mekawy, Moataz
Terada, Eiji
Inoue, Shinji
Sakamoto, Yukihiro
Kawakita, Jin
Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title_full Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title_fullStr Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title_full_unstemmed Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title_short Quantitative Correlation of Droplets on Galvanic-Coupled Arrays with Response Current by Image Processing
title_sort quantitative correlation of droplets on galvanic-coupled arrays with response current by image processing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600636/
https://www.ncbi.nlm.nih.gov/pubmed/34805710
http://dx.doi.org/10.1021/acsomega.1c05161
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