Investigation of vortex assisted magnetic deep eutectic solvent based dispersive liquid–liquid microextraction for separation and determination of vanadium from water and food matrices: Multivariate analysis

ALTUNAY N., Farooque Lanjwani M., Tuzen M., Boczkaj G.

Journal of Molecular Liquids, cilt.396, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 396
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.molliq.2024.124000
  • Dergi Adı: Journal of Molecular Liquids
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Chemical Abstracts Core, Chimica, Compendex, INSPEC
  • Anahtar Kelimeler: Atomic absorption spectrometry, Dispersive liquid–liquid microextraction, Multivariate statistical analysis, Vanadium, Vortex assisted magnetic deep eutectic solvent, Water and food samples
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

A new and simple vortex assisted magnetic deep eutectic solvent dispersive liquid–liquid microextraction procedure (VA-MDES-DLLME) was developed for the determination of vanadium (V) in food and water samples by flame atomic absorption spectrometry (FAAS). In the extraction medium, a bis(acetylpivalylmethane) ethylenediimine (H2APM2en) was used for the complexation of V(V) in sample solution at pH 6. The VA-MDES-DLLME was optimized by different operation parameters, pH level of solution, MDESs volume, vortex time, concentration of complexing agent and samples volume. The accuracy of VA-MDES-DLLME was confirmed by analysis of certified reference materials (CRMs) and standard additional method in respect to real samples. The detection limit, quantification limit and enhancement factor were found 0.3, 1.0 ng mL−1 and 120, respectively. The linearity was confirmed for wide concentration range from 1 to 600 ng mL−1 and relative standard deviation (RSD) is 2.8 %. The multivariate statistical analysis was used for factorial design to explore the effects of extraction parameters on recovery of V(V) and also significant level of variables.