Artificial intelligence-assisted electrochemical sensors for qualitative and semi-quantitative multiplexed analyses†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY
Rocco Cancelliere, Mario Molinara, Antonio Licheri, Antonio Maffucci and Laura Micheli
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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.

Abstract Image

用于定性和半定量多路分析的人工智能辅助电化学传感器
本研究利用人工智能(AI)来提高电化学峰分辨率和降低伏安分析的检出限,重点是复杂的、多重的实矩阵分析。该研究调查了醌族,对苯二酚、苯醌和儿茶酚分别使用循环伏安法和方波伏安法进行分析。将亚铁氰化物/铁氰化物氧化还原对作为标准氧化还原探针,为方法验证提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.80
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0.00%
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