Colorimetric sensor array based on pH-modulated inhibitory effect of a single nanozyme'activity for antioxidant recognition.

To address the need for simultaneous identification of different antioxidants in complex samples, we constructed a simple and effective nanozyme-based colorimetric sensor array. The sensor array employs GaZn nanozymes with peroxidase-like activity as sensing units. Under three distinct pH conditions, the inhibitory effects of antioxidants on the enzymatic activity of the GaZn nanozyme were differentially modulated. Consequently, the nanozyme generates pH-dependent colorimetric responses, producing a unique signal pattern for each antioxidant. In this study, cysteine (Cys), glutathione (GSH), gallic acid (GA), chlorogenic acid (CA), and ascorbic acid (AA) were selected as target analytesto verify the recognition ability of our designed sensor array. Linear discriminant analysis (LDA) was applied to reduce the dimensionality of the colorimetric response data, achieving clear discrimination among the five substances, while a correlation between colorimetric response intensity and concentration was also observed. On this basis, further combined with machine learning algorithms such as random forest, the accuracy of the model in distinguishing blind samples and actual water samples has been effectively improved.