Evidence map›Paper›PMID 40764409›Full record

ArticleMikrochimica acta2025

Atomically dispersed Fe-Mn dual sites in N-doped carbon nanozymes with peroxidase-mimetic activity for the determination of thiocyanate.

Huan Liang, Jia-Qi Wang, Min Zhang, Xiao-Dong Sun, Peng-Jiao Wang, Shuo Zhang, Xiu-Li Gao

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Article in Mikrochimica acta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Huan Liang *State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Jia-Qi Wang *State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Min ZhangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Xiao-Dong SunState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Peng-Jiao WangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Shuo ZhangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China.
Xiu-Li GaoState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine & School of Pharmaceutical Sciences, Guizhou Medical University, Guiyang, Guizhou, 561113, PR China. gaoxl@gmc.edu.cn.

Funding

the China Postdoctoral Science Foundation 2024M760676the Guizhou Provincial Major Scientific and Technological Program [2024]01503-3the Guizhou Provincial Science and Technology Projects QKHJC[2024] youth 222the High-level Talents Program Foundation of Guizhou Medical University J[2023]059
6 · The paper itself

Abstract

FeMn dual-active-site single-atom catalyst (FeMn-N-C), featuring manganese-enhanced Fe-N-doped carbon with abundant FeMn-N4 and C-N active groups, was fabricated via hydrothermal synthesis followed by high-temperature pyrolysis. Thiocyanate (SCN⁻) can be adsorbed onto the FeMn-N-C surface by binding to Fe/Mn atoms, blocking the active sites of the mimic peroxidase and thereby inhibiting the corresponding chromogenic reaction of 3,3',5,5'-tetramethylbenzidine, achieving rapid and sensitive colorimetric detection of SCN⁻. Under optimal conditions, the established biosensor exhibited a linear range of 0.2-11 μmol L

Indexed as

Biomimetic MaterialsCarbonIronManganeseNanostructuresPeroxidaseThiocyanatesBenzidinesBiosensing TechniquesCatalysisColorimetryLimit of DetectionNitrogen3,3',5,5'-tetramethylbenzidineBenzidinesCarbonIronManganeseNitrogenPeroxidasethiocyanateThiocyanatesColorimetric detectionFeMn-N–CNanozymesPeroxidase activityThiocyanate

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.