文献类型：期刊文献

英文题名：Rational Design of a Molecularly Imprinted Sensor on a Biomass Carbon Platform for Glyphosate Monitoring in Traditional Chinese Medicines

作者：Wang, Xin[1];Zhou, Delai[1];Liu, Xuxia[1];Lu, Guodi[1];Hou, Jia[1];Xu, Jian[2];Yang, Fude[1]

第一作者：王馨;王昕;王鑫;王欣

通信作者：Yang, FD[1]

机构：[1]Gansu Univ Tradit Chinese Med, Coll Pharm, Lanzhou 730101, Peoples R China;[2]Chinese Acad Sci, Lanzhou Inst Chem Phys, Res Ctr Nat Med & Chem Metrol, Lanzhou 730000, Peoples R China

第一机构：甘肃中医药大学药学院（西北中藏药协同创新中心办公室）

通信机构：[1]corresponding author), Gansu Univ Tradit Chinese Med, Coll Pharm, Lanzhou 730101, Peoples R China.|[1073501e14fb35863569f]甘肃中医药大学药学院（西北中藏药协同创新中心办公室）;[10735]甘肃中医药大学;

年份：2025

卷号：18

期号：1

外文期刊名：POLYMERS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001658501900001)】；

基金：This research was funded by Key Laboratory of Quality Control for Chinese Herbal Medicines and Sliced Herbs, National Medical Products Administration (2024GSMPA-KL/5); Gansu Higher Education Institutions Industry Support Program (2021CYZC-40); Lanzhou Talent Innovation and Entrepreneurship Project (2023-RC-9); 2025 Gansu Provincial Drug Regulatory Science Research Project (2025GSMPA072).

语种：英文

外文关键词：molecularly imprinted polymer; glyphosate; electrochemical sensor; biomass-derived carbon; Traditional Chinese Medicine analysis

摘要：A molecularly imprinted electrochemical sensor was developed for the selective and sensitive detection of glyphosate in Traditional Chinese Medicine samples. An excellent conductive hierarchical porous carbon substrate made from sodium alginate and ammonium chloride co-carbonization was used to build the sensor. The molecularly imprinted polymer layer was systematically designed using Density Functional Theory calculations, which identified nicotinamide as the optimal functional monomer. A deep eutectic solvent was utilized as an effective green eluent for template removal. Under optimized conditions, the sensor demonstrated a wide linear detection range from 1.0 x 10(-9) to 1.0 x 10(-6) M with an exceptionally low detection limit of 8.8 x 10(-10) M. The sensor exhibited satisfactory reproducibility (RSD = 3.35%, n = 6), repeatability (RSD = 5.0% over 6 cycles), and robust stability (retaining >90% initial response after 10 days). The sensor displayed satisfactory recovery rates of 94.47-112.23% and RSD values ranging from 1.37-3.01% when applied to real traditional Chinese medicine samples, thereby confirming its accuracy and practical utility for glyphosate residue analysis in complex matrices. This study introduces an effective sensing platform that integrates rational design principles with environmentally friendly synthesis strategies for quality control in traditional medicine applications.