Sulphonamide-imprinted sol–gel materials as ionophores in potentiometric transduction

• Autor(a) principal: Almeida, Sofia A. A.
• Data de Publicação: 2011
• Outros Autores: Moreira, Felismina T. C., Heitor, A.M., Montenegro, M.C.B.S.M., Aguilar, G., Sales, M. Goreti F.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.22/6760
• topic: Sulfadiazine; Sulfamethoxazole; Sol–gel; Molecularly-imprinted; Potentiometry

This work proposes different kind of solid-contact graphite-based electrodes for the selective determination of sulphonamides (SPHs) in pharmaceuticals, biological fluids and aquaculture waters. Sulfadiazine (SDZ) and sulfamethoxazole (SMX) were selected for this purpose for being the most representative compounds of this group. The template molecules were imprinted in sol–gel (ISG) and the resulting material was used as detecting element. This was made by employing it as either a sensing layer or an ionophore of PVC-based membranes and subsequent potentiometric transduction, a strategy never reported before. The corresponding non-imprinted sol–gel (NISG) membranes were used as blank. The effect of plasticizer and kind/charge of ionic lipophilic additive was also studied. The best performance in terms of slope, linearity ranges and signal reproducibility and repeatability was achieved by PVC membranes including a high dielectric constant plasticizer and 15 mg of ISG particles. The corresponding average slope was −51.4 and −52.4 mV/decade, linear responses were 9.0 × 10−6 and 1.7 × 10−5 M, and limits of detection were 0.74 and 1.3 μg/mL for SDZ and for SMX, respectively. Good selectivity with log Kpot < −0.3 was observed for carbonate, chloride, fluoride, hydrogenocarbonate, nitrate, nitrite, phosphate, cyanide, sulfate, borate, persulphate, citrate, tartrate, salicylate, tetracycline, ciprofloxacin, sulphamerazine, sulphatiazole, dopamine, glucose, galactose, cysteine and creatinine. The best sensors were successfully applied to the analysis of real samples with relative errors ranging from −6.8 to + 3.7%.