aceA spatial-temporal deep learning method for heavy metal ion detection
Heavy metal ions such as Cd 2+ , Pb 2+ , and Cu 2+ pose severe threats to public health and aquatic ecosystems. Traditional electrochemical detection faces significant challenges including high sample consumption, manual intervention, and difficulties parsing overlapping signals. To address these issues we propose an intelligent metal ion detection platform integrating a microfluidic chip with a deep learning framework. The microfluidic system enables precise droplet manipulation for automated signal acquisition…
Combining a convolutional and a temporal convolutional network lifted ion classification accuracy by 25.9% over an unmodified CNN and beat LSTM variants and traditional machine learning in a microfluidic electrochemical sensing platform.
Evidence
- Peer-reviewedThe Analyst2026-10-01
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Truvace Impact Record TRV-2026-1494, v1: “A spatial-temporal deep learning method for heavy metal ion detection.” Truvace, 2026-10-15. /record/TRV-2026-1494 (accessed at citation time). sha256 2a73da18d1e2f9c2…
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