A machine learning strategy-incorporated BiFeO

Lead Reproducibility of Results Titanium Electrochemical Techniques Machine Learning
Electrochemical sensor MXene Machine learning Optimal conditions Pb(2+) determination

Journal

Chemosphere
ISSN: 1879-1298
Titre abrégé: Chemosphere
Pays: England
ID NLM: 0320657

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 12 05 2023
revised: 23 07 2023
accepted: 02 08 2023
medline: 11 9 2023
pubmed: 10 8 2023
entrez: 9 8 2023
Statut: ppublish

Résumé

The electrochemical technique has been increasingly used for the detection of heavy metal ions in the water system. However, the process for determining the optimum experimental conditions was cumbersome, time-consuming, and unsynchronized, resulting in unsatisfactory detection efficiency. Herein, a new machine learning (ML) strategy combined with BiFeO

Identifiants

DOI: 10.1016/j.chemosphere.2023.139728 PMID: 37557997
pubmed: 37557997
pii: S0045-6535(23)01995-1
doi: 10.1016/j.chemosphere.2023.139728
pii:
doi:

Substances chimiques

MXene 0
Lead 2P299V784P
Titanium D1JT611TNE

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

139728

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Hang Yao (H)

College of Software, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, PR China.

Ruimei Wu (R)

College of Software, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, PR China.

Jin Zou (J)

East China Woody Fragrance and Flavor Engineering Research Center of NF&GA, College of Chemistry and Materials, Jiangxi Agricultural University, Nanchang 330045, China.

Jiawei Liu (J)

East China Woody Fragrance and Flavor Engineering Research Center of NF&GA, College of Chemistry and Materials, Jiangxi Agricultural University, Nanchang 330045, China.

Guanwei Peng (G)

East China Woody Fragrance and Flavor Engineering Research Center of NF&GA, College of Chemistry and Materials, Jiangxi Agricultural University, Nanchang 330045, China.

Xu Wang (X)

College of Software, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, PR China.

Weiqi Zhou (W)

College of Software, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, PR China.

Shirong Ai (S)

College of Software, College of Engineering, Jiangxi Agricultural University, Nanchang 330045, PR China. Electronic address: aisrong@163.com.

Limin Lu (L)

East China Woody Fragrance and Flavor Engineering Research Center of NF&GA, College of Chemistry and Materials, Jiangxi Agricultural University, Nanchang 330045, China. Electronic address: lulimin816@hotmail.com.

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Classifications MeSH

questionsmedicales.fr › Produits chimiques inorganiques › Métaux › Métaux lourds › Plomb › A machine learning strategy-incorporated BiFeO
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Méthodologie en recherche épidémiologique › Reproductibilité des résultats › A machine learning strategy-incorporated BiFeO
questionsmedicales.fr › Produits chimiques inorganiques › Métaux › Métaux légers › Titane › A machine learning strategy-incorporated BiFeO
questionsmedicales.fr › Techniques d'investigation › Techniques électrochimiques › A machine learning strategy-incorporated BiFeO
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Apprentissage machine › A machine learning strategy-incorporated BiFeO