Improving the Selectivity in Electrochemical Detection of Chloramphenicol Against Metronidazole With Machine Learning-Reference-Cited by-同舟云学术

Improving the Selectivity in Electrochemical Detection of Chloramphenicol Against Metronidazole With Machine Learning

Published:2023-08-15 Issue:16 Volume:23 Page:17883-17890
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Xu Ying¹^ORCID,Rao Zhikang¹,Liu Zhe¹,Zheng Weiqiang²,Zhou Yunhong²,Lu Ning¹^ORCID,Yang Yuting²^ORCID

Affiliation:

1. School of Automation, Hangzhou Dianzi University, Hangzhou, China

2. School of Sensing Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China

Funder

Zhejiang Provincial Natural Science Foundation of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10217055/10177910.pdf?arnumber=10177910

Reference33 articles.

1. An amperometric sensor for nitric oxide based on a glassy carbon electrode modified with graphene, Nafion, and electrodeposited gold nanoparticles

2. Mild Synthesis of Pt/SnO2 /Graphene Nanocomposites with Remarkably Enhanced Ethanol Electro-oxidation Activity and Durability

3. Synthesis techniques and advances in sensing applications of reduced graphene oxide (rGO) Composites: A review

4. Simultaneous electrochemical determination of uric acid, xanthine and hypoxanthine based on poly(l-arginine)/graphene composite film modified electrode

5. Proportional impact prediction model of animal waste fat-derived biodiesel by ANN and RSM technique for diesel engine

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