Electrochemical fingerprinting of complex solutions using boron-doped diamond electrodes: Advanced classifications by machine learning

Abstract

Boron-doped diamond (BDD) electrochemical sensors exhibit high sensitivity and a wide-ranging voltammogram scan capability, facilitating the generation of unique fingerprinting information. These attributes are invaluable for the rigorous quality control and real-time monitoring of intricate liquid compositions. In this study, we present an advanced approach for the authentication of complex liquid using BDD electrochemical sensors, in conjunction with Principal Component Analysis (PCA) and Support Vector Machine (SVM) algorithms. Leveraging the heightened sensitivity of BDD sensor signals, it was demonstrated 96 % accuracy rate in authenticity assessments from 21 distinct varieties of red wines. Additionally, high accuracy of classification by grape varieties was demonstrated using electrochemical fingerprints combined with machine learning. Our novel non-specific electronic tongue system offers multimodal electrochemical fingerprinting, ensuring fast and user-friendly measurements without relying on sensor arrays.