Magnetic amino-functionalized metal-organic frameworks as a novel solid support in ionic liquids-based effervescent tablets for efficient extraction of polycyclic aromatic hydrocarbons in milks
Herein, a kind of novel multi-layer core-shell nanocomposites (NSPN) was prepared by employing SiO2 and polyvinylpyrrolidone (PVP) polymers as modifiers and amino-functionalized metal-organic frameworks (NH2-MIL101(Fe)) as coating. It was referred to as the NSPN and ILs-based effervescence-assisted...
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Veröffentlicht in: | Ecotoxicology and environmental safety 2021-10, Vol.222, p.112482-112482, Article 112482 |
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Sprache: | eng |
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Zusammenfassung: | Herein, a kind of novel multi-layer core-shell nanocomposites (NSPN) was prepared by employing SiO2 and polyvinylpyrrolidone (PVP) polymers as modifiers and amino-functionalized metal-organic frameworks (NH2-MIL101(Fe)) as coating. It was referred to as the NSPN and ILs-based effervescence-assisted dispersive solid-phase microextraction, hereafter abbreviated as NIE-DSM. In terms of extraction efficiency, SiO2 and PVP as modifiers and NH2-MIL(Fe) as coating onto the surface of NiFe2O4 cores played a synergistically enhancing effect on adsorption/extraction. Effervescent tablets were prepared by integrating the NSPN magnetic nanoparticles as adsorbents with imidazolium-based ionic liquids (ILs) as extractants as well as acidic and alkaline sources. Under vigorous dispersion of CO2 bubbles, the NIE-DSM method realized the goal of rapidly diffusing and separating the adsorbent/extractant (~3 min) without needing conventional vortexing or centrifugation step. Consequently, the NIE-DSM approach combined dispersion and adsorption/extractant in a synchronous way. Under optimized conditions, the NIE-DSM/HPLC-FLD method gave low limits of detection (0.008–0.034 μg kg−1) and satisfactory extraction recoveries (74.1–101.6%) for five polycyclic aromatic hydrocarbons (PAHs; fluorene, anthracene, pyrene, chrysene and benzo(a)pyrene) in milk samples. The intra-day and inter-day precision, expressed as relative standard deviations, was |
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ISSN: | 0147-6513 1090-2414 |
DOI: | 10.1016/j.ecoenv.2021.112482 |