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Monitoring Amphetamine and Methamphetamine Mixtures Based on Deep Learning Involves Colorimetric Sensing
Sifan Cao1,2, Yuan Liu1,2, Yuwan Du1
1Xinjiang Key Laboratory of Trace Chemical Substances Sensing, Xinjiang Joint Laboratory of Illicit Drugs Control, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi 830011, China.
Analytical Chemistry
|April 25, 2025
Summary
This study developed a colorimetric sensor to differentiate amphetamine (AMP) and methamphetamine (MA) by altering probe structure. The method successfully distinguishes these similar drugs and quantifies their mixtures.
Area of Science:
- Analytical Chemistry
- Materials Science
- Chemical Sensing
Background:
- Distinguishing structurally similar analytes like amphetamine (AMP) and methamphetamine (MA) is crucial for applications such as drug detection and environmental monitoring.
- Existing sensing methods often struggle with precise discrimination due to minimal structural differences (e.g., a single methyl group).
- Developing sensitive and selective optical sensors is essential for reliable analyte identification.
Purpose of the Study:
- To develop a novel colorimetric differentiation strategy for distinguishing amphetamine (AMP) and methamphetamine (MA).
- To modulate probe structure to influence aggregate behavior and enhance colorimetric responses for improved discrimination.
- To enable the quantitative analysis of AMP and MA mixtures for the first time.
Main Methods:
- A colorimetric differentiation strategy was designed by modulating the probe structure to influence the aggregate behaviors of reaction products.
- A furan-based probe with specific electron-withdrawing groups was selected and optimized for differentiating AMP and MA.
- A porous polymer substrate was used to embed the probe, accelerating response times for trace analyte detection.
Main Results:
- The developed strategy successfully discriminated between amphetamine (AMP) and methamphetamine (MA) based on distinct colorimetric responses.
- The probe-embedded porous polymer substrate significantly accelerated the sensing response for trace levels of AMP and MA.
- The quantitative judgment of AMP and MA doping ratios in mixtures was achieved by integrating the sensor with a 'Drugs Analyst' system and deep learning algorithms.
Conclusions:
- Structural modulation of probes can effectively control aggregate behaviors, leading to enhanced colorimetric differentiation of similar analytes.
- This approach offers a promising method for the sensitive and selective detection of amphetamine (AMP) and methamphetamine (MA).
- The integration with advanced algorithms opens new avenues for multidisciplinary fusion in optical sensing and analyte discrimination.
