电化学
检出限
材料科学
电催化剂
电化学气体传感器
二硫代氨基甲酸盐
兴奋剂
锰
分析化学(期刊)
纳米技术
化学
物理化学
电极
光电子学
有机化学
冶金
色谱法
作者
Fan Wang,Junhua Li,Xiangxiong Chen,Hao Feng,Huiyang Liao,Jinlong Liu,Dong Qian,Geoffrey I. N. Waterhouse
标识
DOI:10.1016/j.cej.2024.148607
摘要
Metal single-atom catalysts offer the dual advantages of high electrochemical activity and near 100 % metal atom utilization, leading to their potential use in low-cost electrochemical sensor development. Herein, a novel electrocatalyst comprising atomically-dispersed Mn on B,N co-doped bamboo-derived carbon (MnSAs-BN-BC) was synthesized via a facile pyrolysis procedure. A high dispersion of Mn single atoms in MnSAs-BN-BC was confirmed by aberration-corrected transmission electron microscopy and elemental mapping. The Mn loading in the MnSAs-BN-BC determined by inductively coupled plasma mass spectrometry was 255 mg kg−1. MnSAs-BN-BC displayed outstanding electrocatalytic performance for levodopa (LD) oxidation, allowing a robust electrochemical sensing platform for LD detection to be established. The MnSAs-BN-BC/GCE sensing platform offered a wide LD detection range (concentrations from 2 to 683 µM) and a very low limit of detection (LOD) of 0.45 µM, outperforming almost all electrochemical sensors reported to date for LD sensing. The MnSAs-BN-BC/GCE platform also featured outstanding repeatability, reproducibility, selectivity, and stability. The as-developed sensing platform was successfully applied to LD quantification in commercial tablets with satisfactory recoveries (85.2–102.4 %), with the analytical precision of method validated against a traditional UV–vis spectrophotometry method. Density functional theory (DFT) calculations showed that Mn single atom sites lowered the reaction energy barrier for LD oxidation, with the favorable d-band center position of Mn single atom sites in MnSAs-BN-BC contributing to the enhanced LD sensing performance. This work encourages the use of single-atom metal catalysts in design of high-performance electrochemical sensors for the rapid detection of LD.
科研通智能强力驱动
Strongly Powered by AbleSci AI