0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Nanoplastics Sign in to save

High-sensitivity SERS sensor leveraging three-dimensional Ti3C2Tx/TiO2/W18O49 semiconductor heterostructures for reliable detection of trace micro/nanoplastics in environmental matrices

Talanta 2024 8 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Konghao Han, Zilong Yan, Zhuang Ding, Pengfei Zhou, Pengfei Zhou, Cheng Ye, Cheng Ye, Ling Qin, Zhiyong Bao, Maofeng Zhang, Wei Zhang

Summary

Researchers developed a new sensor that can detect trace amounts of micro- and nanoplastics in environmental samples like rainwater, soil, and wastewater. The sensor uses a layered semiconductor structure to enhance Raman spectroscopy signals, achieving high sensitivity and the ability to identify multiple plastic types at once. This technology could make it faster and more practical to monitor plastic pollution in real-world settings.

Models
Study Type Environmental

The proliferation of micro/nanoplastics (MNPs) has emerged as a pivotal environmental issue, largely due to their potential for human exposure. Consequently, the development of sensitive and efficient detection methodologies is paramount for elucidating their environmental footprint. Here, we report a novel three-dimensional (3D) surface-enhanced Raman scattering (SERS) sensor, which integrate TiCT/TiO/WO semiconductor heterostructure, for the rapid and sensitive detection of MNPs in environmental matrices. The sensor's unique layered architecture and efficient charge transfer mechanism endow it with high sensitivity. It has demonstrated remarkable detection capabilities, achieving a sensitivity of 10 M for Rhodamine 6G (R6G), equating to an enhancement factor (EF) of 2.33 × 10. This level of sensitivity allows for the detection of polystyrene (PS) microplastics at concentration as low as 25 μg/mL, with a relative standard deviation (RSD) of 12.58 %, signifying superior reproducibility. Moreover, the sensor's fingerprinting capabilities enable the identification of a variety of MNPs, including polyethylene (PE) and polyethylene terephthalate (PET), thus facilitating the analysis of complex MNPs mixtures. The sensor's applicability to real-world samples was confirmed through the quantitative detection of PS microplastics in rainwater, soil, and industrial wastewater, with a detection limit of 25 μg/mL and exhibiting good linearity. It is concluded that the 3D SERS sensor is a promising tool for the rapid and precise detection of MNPs across diverse environmental matrices. The advent of this technology marks a significant leap forward in environmental analysis, providing a robust method for the monitoring of MNPs pollution.

Share this paper