4.6 Article

Combined Colorimetric and Electrochemical Measurement Paper-Based Device for Chemometric Proof-of-Concept Analysis of Cocaine Samples

期刊

ACS OMEGA
卷 6, 期 1, 页码 594-605

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsomega.0c05077

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资金

  1. CAPES [3359/2014]
  2. FAPESP [2018/08782-1, 2019/16491-0, 2017/10522-5, 2016/21070-5]
  3. CNPq [444498/2014-1, 305605/2017-8, 141853/2015-8]

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Cocaine is a commonly abused illegal drug worldwide, often adulterated. A study developed a multiple detection paper-based analytical device to discriminate cocaine samples based on adulterants, aiding law enforcement in tracking criminal organization networks.
Cocaine (COC) is one of the most widely consumed illegal drugs around the world. Street COC is commonly adulterated with pharmaceutical compounds that mimic or intensify the COC's sensory effect. Adulteration is performed to increase the profit of criminal organizations and each one has their own way of doing it. Therefore, determining the composition of seized COC samples (chemical profile) provides evidence for the police to track criminal organization networks and their activity patterns. Using filter paper as a substrate, we developed a multiple detection paper-based analytical device (PAD) that combines colorimetric and electrochemical measurements to discriminate COC samples according to adulterant's content. A regular graphite lead modified with a gold film made from Au leaf (graphite/Au) to improve electron transfer was used as a working electrode. Silver and Ag/AgCI were used as auxiliary and reference electrodes, respectively. The colorimetric device was patterned using a laser cutter and coupled to the electrochemical device using a double-sided tape, allowing simultaneous analysis to gather more analytical information about COC samples. Graphite/Au was characterized by scanning and transmission electron microscopies and electrochemical assays. The simultaneous colorimetric and electrochemical analyses combined to principal component analysis improved the analytical characterization of COC trial samples and provided a fast discrimination based on the assembled database.

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