This research utilises Artificial Intelligence (AI) to enhance electrochemical peak resolution and lower detection limits in voltammetric analysis, focusing on complex, multiplex real matrices analyses. The study investigated the quinone family, hydroquinone, benzoquinone, and catechol analysed individually and in mixtures using cyclic and square wave voltammetry. The ferrocyanide/ferricyanide redox couple was included as a standard redox probe to provide a reference for method validation.
Cancelliere, R., Molinara, M., Licheri, A., Maffucci, A., Micheli, L. (2025). Artificial intelligence-assisted electrochemical sensors for qualitative and semi-quantitative multiplexed analyses. DIGITAL DISCOVERY, 2025(4), 338-342 [10.1039/D4DD00318G].
Artificial intelligence-assisted electrochemical sensors for qualitative and semi-quantitative multiplexed analyses
Rocco Cancelliere
;Antonio Licheri;Laura Micheli
2025-01-01
Abstract
This research utilises Artificial Intelligence (AI) to enhance electrochemical peak resolution and lower detection limits in voltammetric analysis, focusing on complex, multiplex real matrices analyses. The study investigated the quinone family, hydroquinone, benzoquinone, and catechol analysed individually and in mixtures using cyclic and square wave voltammetry. The ferrocyanide/ferricyanide redox couple was included as a standard redox probe to provide a reference for method validation.| File | Dimensione | Formato | |
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Digital Discovery 2024 - Molinara.pdf
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