Facile Solvothermal Preparation of Mn2CuO4 Microspheres: Excellent Electrocatalyst for Real-Time Detection of H2O2 Released from Live Cells

检出限 材料科学 电催化剂 纳米技术 生物传感器 电化学 过氧化氢 电极 溶剂热合成 离子液体 安培法 微球 化学工程 催化作用 色谱法 化学 物理化学 工程类 有机化学 生物化学
作者
Paramasivam Balasubramanian,Muthaiah Annalakshmi,Shen‐Ming Chen,Tamilarasan Sathesh,Tie-Kun Peng,T.S.T. Balamurugan
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:10 (50): 43543-43551 被引量:89
标识
DOI:10.1021/acsami.8b18510
摘要

Hydrogen peroxide (H2O2) is an eminent biomarker in pathogenesis; a selective, highly sensitive real-time detection of H2O2 released from live cells has drawn a significant research interest in bioanalytical chemistry. Binary transition-metal oxides (BTMOs) displayed a recognizable benefit in enhancing the sensitivity of H2O2 detection; although the reported BTMO-based H2O2 sensor's detection limit is still insufficient, it is not appropriate for in situ profiling of trace amounts of cellular H2O2. In this paper, we describe an efficient, reliable electrochemical biosensor based on Mn2CuO4 (MCO) microspheres to assay cellular H2O2. The Mn2CuO4 microspheres were prepared through a superficial solvothermal method. It is obvious from impedance studies, introduction of manganese into copper oxide lattice significantly improved the ionic conductivity, which is beneficial for the electrochemical sensing process. Thanks to the distinct microsphere structure and excellent synergy, MCO-modified electrode exhibited excellent nonenzymatic electrochemical behavior toward H2O2 sensing. The MCO-modified electrode delivered a broad working range (36 nM to 9.3 mM) and an appreciable detection limit (13 nM), with high selectivity toward H2O2. To prove its practicality, the developed sensor was applied in the detection of cellular H2O2 released by RAW 264.7 cells in presence of CHAPS. These results label the possible appliance of the sensor in clinical analysis and pathophysiology. Thus, BTMOs are evolving as a promising candidate in designing catalytic matrices for biosensor applications.
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