MOFs-derived metal/carbon materials have been considered as promising candidates for the electrochemical detection of micropollutants. However, the aggregation of metal nanoparticles and structure collapse of precursor MOFs during pyrolysis significantly hamper the improvement on detecting performance. Herein, a dicyandiamide-assisted strategy is utilized to synthesize well-dispersed Cu/N-doped porous carbon nanoarchitecture (CuNC) for the electrochemical detection of acetaminophen (AP). The constructed CuNC sensor exhibits excellent electro-analytical performance for monitoring AP with linear range from 0.01 μM to 921.2 μM, and the low detection limit of 2.46 nM (S/N = 3). The improved performance of CuNC sensor is ascribed to the introduction of dicyandiamide, which can prevent HKUST-1 framework breakage and reduce the aggregation tendency of Cu, leading to the evenly distributed small Cu nanoparticles, abundant N species, hierarchical channel structure, and high conductivity carbon framework. These advantages endow predominant repeatability, stability, and selectivity of CuNC sensor. This strategy provided a novel approach to preparing MOFs-derived carbon nanoarchitectures with excellent electroanalysis performance to monitor micropollutants.

MOFs 衍生的金属/碳材料被认为是微污染物电化学检测的有希望的候选者。然而，热解过程中金属纳米颗粒的聚集和前体 MOF 的结构崩溃显着阻碍了检测性能的提高。在此，利用双氰胺辅助策略合成分散良好的 Cu/N 掺杂多孔碳纳米结构 (CuNC)，用于对乙酰氨基酚 (AP) 的电化学检测。构建的 CuNC 传感器表现出优异的电分析性能，用于监测 AP，线性范围为 0.01 μM 至 921.2 μM，检测下限为 2.46 nM ( S / N = 3)。CuNC传感器性能的提高归因于双氰胺的引入，它可以防止HKUST-1骨架断裂并降低Cu的聚集趋势，导致Cu纳米颗粒分布均匀，N物种丰富，分层通道结构和高电导率碳框架。这些优势赋予了 CuNC 传感器主要的可重复性、稳定性和选择性。该策略为制备具有优异电分析性能以监测微污染物的 MOF 衍生的碳纳米结构提供了一种新方法。