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Talanta ; 276: 126217, 2024 Aug 15.
Article in English | MEDLINE | ID: mdl-38759361

ABSTRACT

In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Representative compounds of different families, including cocaine, 3,4-methylenedioxy-methamphetamine (MDMA), amphetamine and cathinone derivatives, pyrrolidine cathinones, and 3,4-methylenedioxy cathinones, have been analyzed and classified after appropriate reaction with Marquis, gallic acid, sulfuric acid, Simon and Scott reagents. A picture of the colored products was acquired using a smartphone, and the corrected RGB values were used as input data in the chemometric treatment. ANN using two active layers of nodes (6 nodes in layer 1 and 2 nodes in layer 2) with a sigmoidal transfer function and a minimum strict threshold of 0.50 identified illicit drug samples with a sensitivity higher than 83.4 % and a specificity of 100 % with limits of detection in the microgram range. The 3D printed device can operate connected to a rechargeable lithium-ion cell portable battery, is inexpensive, and requires minimal training. The analytical device has been able to discriminate the analyzed psychoactive substances from cutting and mixing agents, being a useful tool for law enforcement agents to use as a screening method.


Subject(s)
Illicit Drugs , Neural Networks, Computer , Printing, Three-Dimensional , Smartphone , Illicit Drugs/analysis , Colorimetry/instrumentation , Colorimetry/methods , Substance Abuse Detection/methods , Substance Abuse Detection/instrumentation , Humans
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