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A facile, sensitive and rapid sensing platform based on CoZnO for detection of fipronil; an environmental toxin.
Kumar, Sanni; Vasylieva, Natalia; Singh, Vikrant; Hammock, Bruce; Singh, Shiv Govind.
Afiliación
  • Kumar S; Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502285.
  • Vasylieva N; Department of Entomology & Nematology, University of California, Davis, USA.
  • Singh V; School of Medicine, University of California, Davis, USA.
  • Hammock B; Department of Entomology & Nematology, University of California, Davis, USA.
  • Singh SG; Department of Electrical Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502285.
Electroanalysis ; 32(9): 2056-2064, 2020 Sep.
Article en En | MEDLINE | ID: mdl-33456276
A sensitive detection of extremely toxic phenylpyrazole insecticide, 'Fipronil' is presented. Currently, the advancement of approaches for the detection of insecticides at low concentrations with less time is important for environmental safety assurance. Considering this fact, an effort has been made to develop an electrospun CoZnO nanofiber (NF) based label-free electrochemical system for the detection of fipronil. The CoZnO NF were characterized using different techniques including field emission scanning electron microscopy (FE-SEM), Energy Dispersive X-Ray Analysis (EDX), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Raman Spectroscopy. Based on the experimental results, the proposed platform displayed a linear response for fipronil in the attogram/mL range despite the multiple interfering agents. The sensitivity of the device was found to be 3.99 Kῼ (g/ml)-1 cm-2. Limit of detection (LOD) and limit of quantification (LOQ) were calculated and found to be 112 ag mL-1 and 340 ag mL-1 respectively. Further, this proposed sensor will be implemented in the fields for the rapid and proficient detection of the real samples.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Electroanalysis Año: 2020 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Electroanalysis Año: 2020 Tipo del documento: Article