Trace determination of safranin O dye using ultrasound assisted dispersive solid-phase micro extraction: Artificial neural network-genetic algorithm and response surface methodology

In this study, ultrasound assisted dispersive solid-phase micro extraction combined with spectrophotometry (USA-DSPME-UV) method based on activated carbon modified with Fe₂O₃ nanoparticles (Fe₂O₃-NPs-AC) was developed for pre-concentration and determination of safranin O (SO). It is known that the efficiency of USA-DSPME-UV method may be affected by pH, amount of adsorbent, ultrasound time and eluent volume and the extent and magnitude of their contribution on response (in term of main and interaction part) was studied by using central composite design (CCD) and artificial neural network-genetic algorithms (ANN-GA). Accordingly by adjustment of experimental conditions suggested by ANN-GA at pH 6.5, 1.1 mg of adsorbent, 10 min ultrasound and 150 μL of eluent volume led to achievement of best operation performance like low LOD (6.3 ng mL⁻¹) and LOQ (17.5 ng mL⁻¹) in the range of 25–3500 ng mL⁻¹. In following stage, the SO content in real water and wastewater samples with recoveries between 93.27–99.41% with RSD lower than 3% was successfully determined.     

Ultrasonic-assisted micro solid phase extraction of arsenic on a new ion-imprinted polymer synthesized from chitosan-stabilized pickering emulsion in water,rice and vegetable samples

Pickering emulsion polymerization has been employed for the Ultrasonic assisted-micro solid phase extraction (UA-µSPE) of ultra trace arsenic species by a new magnetic ion imprinted polymer (MIIP) prior to hydride generation atomic absorption spectrometry. 2-acetyl benzofuran thiosemicarbazone (2-ABT) as a new chelating agent and core- shell hydrophobic magnetic nanoparticles was synthesized and the polymerization was carried out at the presence of arsenic – ligand complex, crosslinker, monomer, initiator, stabilizing agent and water-oil emulsion magnetic carrier. In second step, the nanoparticles and polymers were characterized. The analytical parameters such as pH, amount of polymer and ultrasonic time were selected and optimozed by Plackett–Burman and Box–Behnken designs respectively. Linear dynamic range, detection limit and relative standard deviation were 0.01–85.000 µg·L^−l, 0.003 µg·L^−l, and 3.21%, respectively. The proposed preconcentration procedure was successfully applied to the determination of arsenic ion in a wide range of food samples with different and complex matrixes.