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Borosilicate glass nanopipettes enhanced by synergistic electrostatic interactions and steric hindrance for ultrasensitive electrochemical detection of nanoplastics in environmental water samples
Summary
Researchers developed an electrochemical sensor using borosilicate glass nanopipettes enhanced with electrostatic interactions to detect nanoplastics in environmental water samples, achieving ultrasensitive trace-level detection without complex sample pretreatment.
The widespread use of plastic products has resulted in the accumulation of nanoplastics in the environment. These particles pose serious threats to ecosystems and human health owing to their persistence and potential for bioaccumulation. However, conventional methods for detecting nanoplastics are limited by complex sample pretreatment, time-consuming procedures, and inadequate sensitivity, making them unsuitable for trace-level analysis in environmental matrices. This study achieved ultrasensitive detection of polystyrene (PS) nanoplastics using borosilicate glass nanopipettes enhanced by synergistic electrostatic interactions and steric hindrance effects. This method enables highly sensitive, single-particle detection of PS nanoplastics through electrostatic interactions between amino groups and the negatively charged nanoplastics. By leveraging electrostatic interactions between the positively charged 3-aminopropyltriethoxysilane and negatively charged PS nanoplastics, the sensing platform detects charge neutralization-induced changes in surface charge characteristics. In addition, the steric hindrance caused by nanoplastics with sizes comparable to the nanopipette aperture further constricts the ion transport pathway, producing distinct variations in current signals. This synergistic mechanism enables a low detection limit of 3.2 μg L-1 and delivers reliable performance in real-world water samples, including spring water and tap water, without the need for extensive pretreatment. The developed platform not only simplifies the detection process but also offers high spatiotemporal resolution, making it highly promising for real-time monitoring of environmental nanoplastics and addressing the pressing need for advanced analytical tools in nanoplastic research.
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