FeNi foam with specifically boosted peroxidase-like activity for smartphone-based rapid visual detection

交货地点 过氧化物酶 材料科学 计算机科学 纳米技术 检出限 催化作用 化学 生物化学 色谱法 农学 生物
作者
Yu Zhang,Tian Luan,Qi Fang,Zhimin Song,Xudong Shang,Lehui Lu,Yan Du
出处
期刊:Sensors and Actuators B-chemical [Elsevier BV]
卷期号:401: 135068-135068 被引量:19
标识
DOI:10.1016/j.snb.2023.135068
摘要

Smartphone-based analysis is an emerging technique that provides a wide range of biomedical applications in point-of-care testing (POCT). Here, we have developed a portable and rapid sensing platform. It integrates an activated FeNi foam with specifically boosted peroxidase (POD)-like activity as signal generator, a lower light photography device and an image digitization application (APP) that help to realize direct signal readout through a smartphone. Significantly, by introducing polydopamine nanoparticles (PDNPs) on activated FeNi foam, the POD-like activity can be enhanced over tenfold, in sharp contrast to the silent oxidase (OXD)-like activity. It is determined that the improved catalytic performance originates from the winkle structures on activated FeNi foam, synergistic effect between Fe and Ni and the cycles between Fe3+/Fe2+ and catechol/quinones for electron transfer and mass transport. Further, the use of PDNPs as an immobilization linker enables the construction of an integrated nanozyme by immobilizing natural enzymes like glucose oxidase. Combined with a multifunctional photography system, sensitive and rapid detection of H2O2 and glucose were achieved, the limit of detection (LOD) was 10.2 µM and 40.6 µM, respectively, and detection time was less than 6 min. This highlights the potential of the smartphone-based sensing platform for online monitoring biomarkers in a high-throughput and point-of-care format. Considering the significance of efficient catalysts and the growing demand for POCT, our study contributes to the development of peroxidase mimics based on metal foam and provides valuable insights for improving the performance of photography devices in visual detection.
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