Machine learning-assisted pesticide detection on a flexible surface-enhanced raman scattering substrate prepared by silver nanoparticles

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buir.contributor.authorOnses, M. Serdar
buir.contributor.orcidOnses, M. Serdar|0000-0001-6898-7700
dc.citation.epage13122en_US
dc.citation.issueNumber9en_US
dc.citation.spage13112en_US
dc.citation.volumeNumber5en_US
dc.contributor.authorOnses, M. Serdar
dc.contributor.authorRuzi, M.
dc.contributor.authorCeylan, A.
dc.contributor.authorSakir, M
dc.contributor.authorCamdal, A.
dc.contributor.authorCelik, N.
dc.contributor.authorSahin, F.
dc.date.accessioned2023-02-14T11:24:49Z
dc.date.available2023-02-14T11:24:49Z
dc.date.issued2022-09-12
dc.departmentInstitute of Materials Science and Nanotechnology (UNAM)en_US
dc.description.abstractAccess to clean water is a pressing challenge affecting millions of lives and the aquatic body of the Earth. Sensitive detection of pollutants such as pesticides is particularly important to address this challenge. This study reports eco-friendly preparation of the surface-enhanced Raman scattering (SERS) substrate for machine learning-assisted detection of pesticides in water. The proposed SERS platform was prepared on a copy paper by reducing a silver salt using the extract of a natural plant, Cedrus libani. The fabricated SERS platform was characterized in detail using scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The high-density formation of silver nanoparticles with an average diameter of 41 nm on the surface of the paper enabled detection of analytes with a nanomolar level sensitivity. This SERS capability was used to collect Raman signals of four different pesticides in water: myclobutanil, phosmet, thiram, and abamectin. Raman spectra of the pesticides are highly complex, challenging accurate determination of the pesticide type. To overcome this challenge and distinguish pesticides, machine learning (ML) approach was used. The ML-mediated detection of harmful pesticides on a versatile, green, and inexpensive SERS platform appears to be promising for environmental applications.en_US
dc.identifier.doi10.1021/acsanm.2c02897en_US
dc.identifier.eissn2574-0970
dc.identifier.urihttp://hdl.handle.net/11693/111259
dc.language.isoEnglishen_US
dc.publisherAmerican Chemical Societyen_US
dc.relation.isversionofhttps://doi.org/10.1021/acsanm.2c02897en_US
dc.source.titleACS Applied Nano Materialsen_US
dc.subjectSilver nanoparticlesen_US
dc.subjectCedrus libanien_US
dc.subjectEco-friendly fabricationen_US
dc.subjectSERS platformen_US
dc.subjectPesticidesen_US
dc.subjectMachine learningen_US
dc.titleMachine learning-assisted pesticide detection on a flexible surface-enhanced raman scattering substrate prepared by silver nanoparticlesen_US
dc.typeArticleen_US

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