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Clustered Regularly Interspaced Short Palindromic Repeat-Based Colorimetric Aptasensor Combined with Smartphone Imaging and Deep Learning Enables Selective Recycling and Visual Prediction of Microplastics in the Environment
Summary
Researchers developed a CRISPR-based colorimetric aptasensor paired with smartphone imaging and deep learning to detect and quantify PVC and polystyrene microplastics in environmental samples, achieving nanogram-per-milliliter detection limits and enabling rapid visual monitoring without laboratory equipment.
μg/mL. In smartphone detection mode, the limits of detection for PVC and PS reached 3.1 ng/mL and 3.7 ng/mL, respectively. This approach significantly enhances detection performance and stability, enabling visual monitoring of microplastics in complex real samples. Collectively, this work provides a rapid and effective strategy for the extraction and real-time quantification of small molecules.