A portable smart detection and electrocatalytic mechanism of mycophenolic acid: A machine learning-based electrochemical nanosensor to adapt variable-pH silage microenvironment

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dc.contributor.authorGe, Yu
dc.contributor.authorCamarada, Maria Belen
dc.contributor.authorLiu, Peng
dc.contributor.authorQu, Mingren
dc.contributor.authorWen, Yangping
dc.contributor.authorXu, Lanjiao
dc.contributor.authorLiang, Huan
dc.contributor.authorLiu, En
dc.contributor.authorZhang, Xian
dc.contributor.authorHao, Wenxue
dc.contributor.authorWang, Long
dc.date.accessioned2025-01-20T21:02:08Z
dc.date.available2025-01-20T21:02:08Z
dc.date.issued2022
dc.description.abstractThe pH of silage microenvironment is protean which affects the concentration of mycophenolic acid (MPA) that is an animal health-threatening mycotoxin produced by Penicillium roqueforti. This inspired us to develop a fast portable intelligent method for electrochemical detection of MPA in silage with the variable-pH microenviron-ment using Zn-Co MOF/Ti3C2 MXene/Fe3O4-MGO coupling with machine learning (ML). Zn-Co MOF (metal organic framework), Ti3C2 MXene (graphene-like titanium carbide MXene), Fe3O4-MGO (magnetic Fe3O4-gra-phene oxide) and their nanocompsite with excellent electrocatalytic capacity were prepared and characterized. The electrocatalytic mechanism of MPA was investigated by density functional theory (DFT) and electrochemical experiments, which clarified the most easily redox position of MPA. ML model via artificial neural network (ANN) algorithm for smart output of MPA through input of pH was discussed that adapt to the variable-pH microenvironment and realize intelligent analysis of MPA in silage with the variable-pH microenvironment. R2 near 1, lower both RMSE and MAE, and higher RPD value demonstrate the good predictive performance and high predictive accuracy of the proposed ANN model. This will provide a fast portable wireless intelligent sensing analytical technology for detecting hazardous substances in diverse complicated and changeable outdoor microenvironments
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.snb.2022.132627
dc.identifier.eissn0925-4005
dc.identifier.urihttps://doi.org/10.1016/j.snb.2022.132627
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/93019
dc.identifier.wosidWOS:000862661600006
dc.language.isoen
dc.revistaSensors and actuators b-chemical
dc.rightsacceso restringido
dc.subjectMycophenolic acid
dc.subjectTheory calculation
dc.subjectArtificial neural network
dc.subjectElectrocatalytic mechanism
dc.subjectIntelligent analysis
dc.subjectNanohybrid sensor
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleA portable smart detection and electrocatalytic mechanism of mycophenolic acid: A machine learning-based electrochemical nanosensor to adapt variable-pH silage microenvironment
dc.typeartículo
dc.volumen372
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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