Sensor application and mathematical modeling of new Zn(II) phthalocyanine containing 26-membered tetraoxadithia macrocycle moieties

dc.authorid0000-0003-3222-9056en_US
dc.authorid0000-0003-3776-9633en_US
dc.authorid0000-0003-3416-1083en_US
dc.authorid0000-0002-5803-6255en_US
dc.contributor.authorBaygu, Yasemin
dc.contributor.authorÇapan, İnci
dc.contributor.authorÇapan, Rifat
dc.contributor.authorErdoğan, Matem
dc.contributor.authorAçıkbaş, Yaser
dc.contributor.authorKabay, Nilgün
dc.contributor.authorGök, Yaşar
dc.contributor.authorBüyükkabasakal, Kemal
dc.date.accessioned2024-08-26T10:51:23Z
dc.date.available2024-08-26T10:51:23Z
dc.date.issued2023en_US
dc.departmentFakülteler, Fen-Edebiyat Fakültesi, Fizik Bölümüen_US
dc.descriptionÇapan, İnci (Balikesir Author)en_US
dc.description.abstractA novel phthalonitrile containing 26-member tetraoxadithia macrocycle moiety was synthesized in a multistep reaction sequence. New zinc(II) phthalocyanine was obtained by the cyclomerization reaction of this macrocyclic phthalonitrile. The novel phthalocyanine and the precursor compounds have been characterized by a combination of 1 H and 13C NMR, FT-IR, UV–vis, elemental analysis and MALDI-TOF mass spectral data. 26-membered phthalocyanine was used to fabricate multilayered Langmuir-Blodgett (LB) thin films dedicated to investigating the gas sensing properties of these novel phthalocyanine materials. SEM images of the uncoated substrate, 8- layered and 16-layered LB thin films were compared to observe the successfully transferred layer by layer onto the solid substrates. Sensor parameters such as selectivity, reproducibility, thickness effect, recovery and response rates were examined for highly toxic benzene and toluene vapors using the mass sensitive Quartz Crystal Microbalance (QCM) technique. The first time the thickness effect on the gas sensing mechanism for selected material was also investigated. Validation of the experimental measurements of QCM kinetic was implemented using nonlinear autoregressive with exogenous input neural network for modelling using the frequency shift value. Comparison of these frequency shift of artificial neural network with real-experimental data showed the accuracy of the artificial neural network model.en_US
dc.identifier.doi10.1016/j.inoche.2023.110553
dc.identifier.endpage8en_US
dc.identifier.issn1387-7003
dc.identifier.issn1879-0259
dc.identifier.issueFeben_US
dc.identifier.scopus2-s2.0-85148665823
dc.identifier.scopusqualityQ2
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1016/j.inoche.2023.110553
dc.identifier.urihttps://hdl.handle.net/20.500.12462/15055
dc.identifier.volume150en_US
dc.identifier.wosWOS:000965413600001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofInorganic Chemistry Communicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectSynthetic Macrocycleen_US
dc.subjectZinc(II) Phthalocyanineen_US
dc.subjectCyclotetramerizationen_US
dc.subjectLangmuir-Blodgett, Thin Filmen_US
dc.subjectQCMen_US
dc.subjectChemical Sensoren_US
dc.titleSensor application and mathematical modeling of new Zn(II) phthalocyanine containing 26-membered tetraoxadithia macrocycle moietiesen_US
dc.typeArticleen_US

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