Your browser doesn't support javascript.
loading
The Long-Lasting Story of One Sensor Development: From Novel Ionophore Design toward the Sensor Selectivity Modeling and Lifetime Improvement.
Lvova, Larisa; Monti, Donato; Natale, Corrado Di; Paolesse, Roberto.
Afiliação
  • Lvova L; Department of Chemical Science and Technologies, University of Rome "Tor Vergata", 00133 Rome, Italy.
  • Monti D; Department of Chemistry, La Sapienza University of Rome, 00185 Rome, Italy.
  • Natale CD; Department of Electronic Engineering, University of Rome "Tor Vergata", 00133 Rome, Italy.
  • Paolesse R; Department of Chemical Science and Technologies, University of Rome "Tor Vergata", 00133 Rome, Italy.
Sensors (Basel) ; 21(4)2021 Feb 17.
Article em En | MEDLINE | ID: mdl-33671289
ABSTRACT
The metalloporphyrin ligand bearing incorporated anion-exchanger fragment, 5-[4-(3-trimethylammonium)propyloxyphenyl]-10,15,20-triphenylporphyrinate of Co(II) chloride, CoTPP-N, has been tested as anion-selective ionophore in PVC-based solvent polymeric membrane sensors. A plausible sensor working mechanism includes the axial coordination of the target anion on ionophore metal center followed by the formed complex aggregation with the second ionophore molecule through positively charged anion-exchanger fragment. The UV-visible spectroscopic studies in solution have revealed that the analyte concentration increase induces the J-type porphyrin aggregation. Polymeric membranes doped with CoTPP-N showed close to the theoretical Nernstian response toward nitrite ion, preferably coordinated by the ionophore, and were dependent on the presence of additional membrane-active components (lipophilic ionic sites and ionophore) in the membrane phase. The resulting selectivity was a subject of specific interaction and/or steric factors. Moreover, it was demonstrated theoretically and confirmed experimentally that the selection of a proper ratio of ionophore and anionic additive can optimize the sensor selectivity and lifetime.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article