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A g-C3N4-stabilized Au nanozyme-based sensor with AI-powered “recognition–extraction–interpretation–report” for bias-minimized in-field monitoring of mercury ions
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DOI：10.1039/D6AN00581K.png)
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Abstract
En 中文
Mercury ions (Hg2+) pose serious threats to human health owing to their toxicity and bioaccumulative properties; requiring timely and accurate in-field monitoring. Although laboratory-based analytical techniques can offer excellent detection performance; they need expensive instrumentation and professional operators; making them unsuitable for on-site self-detection; existing portable optical approaches still rely on manual operation; inevitably introducing underestimated biases arising from operators’ subjectivity and hardly meeting the demand for reliable monitoring. To fill this gap; here we introduced g-C3N4 as a favorable support to stabilize agglomeration-prone gold nanoparticles (AuNPs) and constructed an AI-powered “recognition–extraction–interpretation–report” automatic signal-on optical sensor for Hg2+ quantification with minimized biases based on target-triggered enhancement of enzyme-like activity. The g-C3N4/AuNP nanozyme exhibited synergistic catalytic performance compared with individual g-C3N4 or AuNPs; providing a stable signal generation route for Hg2+ sensing. Importantly; the nanozyme response was integrated into a smartphone-based portable platform to achieve point-of-need monitoring at environmental sites. More importantly; by incorporating a standardized attachment and a deep-learning-assisted workflow; the developed sensor effectively eliminated subjective and objective biases associated with imaging conditions; manual region selection; operator dependency; and inconsistent signal interpretation. Our sensor was totally free from the need for spectrophotometers and human intervention; enabling user-independent Hg2+ in-field quantitative analysis. Our contribution offers a route to smart sensing by fusing advanced nanozyme materials and portable devices with AI algorithms; which can inspire the future development of intelligent sensors for broader analytical applications.
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3.3
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1.6W
Citations:
3.3W
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