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Updated: May 1, 2026

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A Microfluidic Chip for the Versatile Chemical Analysis of Single Cells
Published on: October 15, 2013
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Sequential injection analysis of thiocyanate ions using a microfluidic polymer chip with an embedded ion-selective
Benjaporn Tossanaitada1, Takashi Masadome, Toshihiko Imato
1Department of Applied Chemistry, Faculty of Engineering, Shibaura Institute of Technology.
Summary
A new sequential injection analysis (SIA) system was developed for detecting thiocyanate (SCN-) ions using a microfluidic chip and ion-selective electrode. This method accurately measures SCN- in saliva samples with good throughput.
Area of Science:
- Analytical Chemistry
- Microfluidics
- Electrochemistry
Background:
- Thiocyanate (SCN-) ion determination is crucial for various applications, including clinical diagnostics and environmental monitoring.
- Existing methods for SCN- detection can be complex or time-consuming.
Purpose of the Study:
- To develop a novel sequential injection analysis (SIA) system for efficient SCN- ion determination.
- To integrate a microfluidic polymer chip with an embedded SCN- ion-selective electrode (SCN(-)-ISE) for sensitive detection.
Main Methods:
- A sequential injection analysis (SIA) system was designed and optimized.
- A microfluidic polymer chip featuring an integrated SCN(-)-ISE was employed as the detector.
- The system's performance was evaluated using standard SCN- solutions.
Main Results:
- The developed SIA system demonstrated a good linear relationship between peak heights and logarithmic SCN- concentrations (1.0 × 10(-5) to 1.0 × 10(-1) mol dm(-3)).
- A Nernstian slope of 59.4 ± 3.8 mV decade(-1) was achieved, indicating reliable electrode performance.
- The system achieved a sample throughput of approximately 12 samples per hour.
Conclusions:
- The proposed SIA system offers a sensitive and efficient method for SCN- ion determination.
- The system's applicability was successfully demonstrated through the analysis of SCN- levels in human saliva samples.
- This microfluidic-based approach provides a promising platform for rapid SCN- analysis.

