Research output: Contribution to journal › Review article › peer-review
Heavy metal pollution has severe threats to the ecological environment and human health. Thus, it is urgent to achieve the rapid, selective, sensitive and portable detection of heavy metal ions. To overcome the defects of traditional methods such as time-consuming, low sensitivity, high cost and complicated operation, QDs (Quantum dots)-based nanomaterials have been used in sensors to significantly improve the sensing performance. Due to their excellent physicochemical properties, high specific surface area, high adsorption and reactive capacity, nanomaterials could act as potential probes or offer enhanced sensitivity and create a promising nanosensors platform. In this review, the rapidly advancing types of QDs for heavy metal ions detection are first summarized. Modified with ligands, nanomaterials, or biomaterials, QDs are assembled on sensors by the interaction of electrostatic adsorption, chemical bonding, steric hindrance, and base-pairing. The stability of QDs-based nanosensors is improved by doping the elements to QDs, providing the reference substance, optimizing the assemble strategies and so on. Then, according to transducer principles, the two most typical sensor categories based on QDs: optical and electrochemical sensors are highlighted to be discussed. In the meanwhile, portable devices combining with QDs to adapt the practical detection in complex situations are summarized. The deficiencies and future challenges of QDs in toxicity, specificity, portability, multi-metal co-detection and degradation during the detection are also pointed out. In the end, the development trends of QDs-based nanosensors for heavy metal ions detection are discussed. This review presents an overall understanding, recent advances, current challenges and future outlook of QDs-based nanosensors for heavy metal detection.
Original language | English |
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Article number | 122903 |
Journal | Talanta |
Volume | 239 |
DOIs | |
State | Published - 1 Mar 2022 |
ID: 94820222