• Publications
Project outcomes

Voltammetric Sensing Using an Array of modified SPCE Coupled with Machine Learning Strategies for the Improved Identification of Opioids in Presence of Cutting Agents

A recent work prepared by researchers from the Autonomous University of Barcelona (UAB) and the University of Antwerp reports for the first time the qualitative analysis for the determination of three drugs of abuse (heroin, morphine and codeine) and their corresponding cutting agents (caffeine and paracetamol) combining the use of modified screen-printed electrodes for voltammetric sensing with chemometrics tools, in what has been named a multisensory analysis system or an electronic tongue approach.

The samples were analyzed by Square Wave Voltammetry technique for extracting the fingerprint of the individual substances, coupled with advanced data treatment such as PCA (Principal Component Analysis) and Silhouette parameter calculation. The use of PCA allowed firstly the pre-selection of the best sensors to define the candidates for the sensor array and secondly, after calculation of the Silhouette parameter, its accurate optimization, showing the most suitable combination of working electrodes. Thanks to the application of both tools, the final combination selected was with electrodes modified with Graphite, Cobalt (II) phthalocyanine and Pd nanoparticle inks. With the optimized sensor array, different identification models were tested demonstrating that a K-nearest neighbor classifier (kNN) could be easily developed, and showing performance among the best.

Full article, published in the Journal of Electroanalytical Chemistry, can be found here.


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