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Using a cotton thread-based colorimetric sensor modified by carboxymethylcellulose and cuprizone with smartphone
Josiane Lopes de Oliveira1, Willian Toito Suarez1, Vagner Bezerra Dos Santos2
1Department of Chemistry, Centre for Exact Sciences and Technology, Federal University of Viçosa - UFV, Viçosa, 36570-900, MG, Brazil.
Analytical Methods : Advancing Methods and Applications
|October 20, 2023
Summary
A new cotton thread sensor using carboxymethylcellulose and cuprizone offers a low-cost, smartphone-based method for detecting cupric ions in water and cachaça. This colorimetric approach enables real-time, on-field copper analysis with high precision.
Area of Science:
- Analytical Chemistry
- Environmental Science
Background:
- Accurate determination of cupric ions (Cu(II)) is crucial for water and beverage quality assessment.
- Existing methods for copper detection can be expensive and require laboratory settings, limiting accessibility.
Purpose of the Study:
- To develop a novel, affordable, and portable colorimetric sensor for quantifying cupric ions.
- To enable real-time, on-field copper determination in water and cachaça samples using smartphone technology.
Main Methods:
- Modification of cotton threads with carboxymethylcellulose (CMC) and cuprizone (CPZ) to create a colorimetric sensor.
- Utilizing the complexation reaction between Cu(II) and CPZ, inducing a visible color change on the cotton thread.
- Smartphone-based image analysis for quantitative determination of copper concentration.
Main Results:
- The sensor enabled quantitative determination of copper in the range of 1 to 12 mg L⁻¹, with a low limit of detection of 0.21 mg L⁻¹.
- Recovery assays in water and cachaça samples showed high accuracy, with percentages ranging from 84.9% to 107%.
- Validation against flame atomic absorption spectrometry confirmed the method's precision and reliability.
Conclusions:
- The developed cotton thread/smartphone colorimetric sensor is a cost-effective and practical tool for on-site copper determination.
- This method offers a viable alternative for real-time water and cachaça quality monitoring, especially in resource-limited environments.
