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    The widespread use of herbicides in agriculture and gardening causes environmental and safety issues such as water pollution. Thus, efficient and convenient analysis of the levels of herbicide residues is of significant importance. Here, we employed 3D-printing to design a multiplex immunosensor for simultaneous detection of two widely used herbicides, atrazine and acetochlor. Multiplexing was achieved through customization of a lateral flow immunoassay, and then integrated with an electrochemical analyzer for ultrasensitive detection. Quantification of herbicide residues was realized through the detection of a novel nanomaterial label, the mesoporous core-shell palladium@platium nanoparticle (Pd@Pt NP), for its outstanding peroxidase-like property. During the electrochemical analysis, the catalytic activity of Pd@Pt NPs on the redox reaction between thionin acetate and hydrogen peroxide provided an electrochemically driven signal that accurately indicated the level of herbicide residues. Using this Nanomaterial-enhanced multiplex electrochemical immunosensing (NEMEIS) system, simultaneous detection of atrazine and acetochlor was realized with a limit of detection of 0.24 ppb and 3.2 ppb, respectively. To further evaluate the feasibility, the optimized NEMEIS was employed for detection in atrazine and acetochlor residue-containing spiked samples, and an overall recovery with 90.8% - 117% range was obtained. The NEMEIS constructed with the aid of 3D-printing provides a rapid, precise, economical, and portable detection device for herbicides, and its success suggests potential broad applications in chemical analysis, biosensors and point-of-care monitoring. Copyright © 2021 Elsevier B.V. All rights reserved.

    Citation

    Xiaofan Ruan, Yijia Wang, Eunice Y Kwon, Limin Wang, Nan Cheng, Xiangheng Niu, Shichao Ding, Bernard J Van Wie, Yuehe Lin, Dan Du. Nanomaterial-enhanced 3D-printed sensor platform for simultaneous detection of atrazine and acetochlor. Biosensors & bioelectronics. 2021 Jul 15;184:113238

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    PMID: 33878594

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