Open Source Automated Flow Analysis Instrument for Detecting Arsenic in Water

Area of Science:

• Analytical Chemistry
• Environmental Science
• Embedded Systems Engineering

Background:

• Arsenic contamination in water poses a significant global health risk.
• Accurate and accessible detection methods are crucial for public safety.
• Existing methods for arsenic detection can be complex and costly.

Purpose of the Study:

• To design and implement an automated, open-source embedded system for detecting arsenic in water.
• To integrate Quartz Crystal Microbalance (QCM) sensor technology with a Field-Programmable Gate Array (FPGA) admittance meter.
• To provide a foundation for developing future analytical methodologies for arsenic quantification.

Main Methods:

• Development of an embedded system utilizing Flow-Batch methodology.
• Integration of a Quartz Crystal Microbalance (QCM) sensor.
• Employment of a commercial FPGA admittance meter for real-time measurements.
• System assembly and operation instructions provided.

Main Results:

• Successful design and implementation of the embedded detection system.
• Evaluation of system performance using laboratory-prepared samples.
• Characterization of the system's dynamic range and linear regression coefficients.
• Demonstration of the system's potential for arsenic detection.

Conclusions:

• The developed open-source automated flow instrument is a viable tool for detecting arsenic in water.
• The system design facilitates the development of future analytical methods for arsenic quantification.
• This approach offers a cost-effective and accessible solution for water quality monitoring.