Smartphone-Enabled Copper(II) Ion Quantification with an Optical Platform and Image Processing Algorithm

Area of Science:

• Analytical Chemistry
• Environmental Science
• Optical Sensing

Background:

• Copper(II) ion (Cu(II)) detection is crucial for water quality assessment.
• Traditional methods can be expensive and require specialized equipment.
• Developing accessible and portable detection methods is essential.

Purpose of the Study:

• To develop and validate a smartphone-based optical method for quantifying Cu(II) ions.
• To utilize turbidity changes induced by chelation for ion measurement.
• To assess the method's performance against established analytical techniques.

Main Methods:

• Cu(II) solutions were treated with dithiooxamide, forming insoluble copper dithiooxamide polymer particles.
• Light transmission through the turbid solution was captured using a smartphone camera.
• Image analysis involved RGB to HSV color space conversion and calculation of the V value, correlating to Cu(II) concentration.

Main Results:

• The V value showed a linear relationship with Cu(II) concentration (0.22-15 mg/L).
• The method achieved a limit of detection (LOD) of 0.30 mg/L, below WHO guidelines.
• Results were validated using UV-vis spectroscopy and ICP-MS, with a relative standard deviation (RSD) of 1.2-9%.

Conclusions:

• Smartphone-based turbidity measurement offers a viable, low-cost approach for Cu(II) quantification.
• The developed method is sensitive and accurate enough for monitoring copper levels in drinking water.
• This technology has potential for field-deployable water quality testing.