Smartphone-Based Colorimetric Detection of Heavy Metal Copper (II) Ion by Help of Surface Acoustic Wave

A smartphone application algorithm to detect heavy metal copper (II) ion for Android operating system was developed. Droplets of copper (II) ion solution were driven to a testing zone in strip by help of surface acoustic wave, and implemented color development reaction. A reference zone was used to decrease ambient light effects. The images of test zone and reference zone were captured by the smartphone, and then analyzed to quantify the analyte concentration by compensating algorithm and gradient location algorithm using self-developed app. The quantificational detection of 2 mg/dl and 5 mg/dl heavy metal copper (II) ion in water was used to demonstrate the utility of presented algorithm. The results showed that the maximal relative error is 7.11%.