聚多巴胺涂敷的聚酰胺-胺功能化二氧化硅复合材料用于水样中苯甲酰脲类杀虫剂的分散微固相萃取

Polyamidoamine dendrimer-functionalized silica nanocomposite with polydopamine coating for dispersive micro solid-phase extraction of benzoylurea insecticides in water samples

近年来,由农药残留导致的环境污染问题已引起社会的广泛关注,开发便捷高效的分析方法对农药残留进行检测和监测十分必要。研究设计并成功制备了聚多巴胺涂敷的聚酰胺-胺树状分子功能化的二氧化硅复合材料(SiO-PAMAM-PDA),并采用透射电镜对其进行表征。开发了以此复合材料为吸附剂的分散微固相萃取方法(D-μ-SPE),并结合高效液相色谱对水基质中的4种苯甲酰脲类杀虫剂(BUs)残留进行了富集检测。多巴胺结构中含有丰富的苯环、氨基及羟基,可与目标物形成氢键、π-π相互作用,从而增强了材料对苯甲酰脲的萃取能力。对吸附剂用量、萃取时间等可能影响萃取效率的条件进行了单因素优化。在最优条件下,该方法的线性范围在10~500μg/L之间,根据3倍信噪比(S/N)计算所得的检出限(LOD)为1.1~2.1μg/L,回收率为82.8%~94.1%,相对标准偏差(RSD)为2.1%~8.0%。将建立的方法与已报道的以苯甲酰脲作为目标物的方法进行了对比,发现方法样品用量及萃取剂用量均较少,且所需前处理时间较短,有机溶剂消耗也较少,为苯甲酰脲类农药的检测提供了更快速、绿色的选择。为评估所开发方法的实际样品适用性,将其应用于3种河水样品中4种苯甲酰脲类杀虫剂的分析检测,所得回收率及RSD分别为69.5%~99.4%和0.2%~9.5%,表明此方法在实际样品中同样具有较高的准确性和精密度。

Pesticides are used in the agricultural production process to ensure the yield and quality of agricultural products. However, in recent years, environmental pollution issues caused by pesticide residues have sparked widespread concern in society. It is important to develop convenient and efficient approaches to detect and monitor pesticide residues. In this study, targeting benzoylurea insecticides(BUs), polyamidoamine dendrimer-functionalized silica nanocomposite with polydopamine coating(SiO-PAMAM-PDA) was designed and successfully synthesized. First, monodisperse silica nanoparticles were prepared by the hydrolysis of tetraethyl orthosilicate(TEOS) in mixed solution of ethanol, water and ammonia. The silane coupling agent(3-aminopropyl)triethoxysilane was then employed to introduce amino groups into the silica. Silica with the zeroth generation of polyamidoamine(PAMAM) modification(SiO-PAMAM-G0) was obtained through Michael addition reaction of methyl acrylate. Ethylenediamine was added to polymerize with methyl acrylate using an amidation reaction to form the first-generation PAMAM(SiO-PAMAM-G1). Finally, by polymerizing dopamine under alkaline conditions(pH=8.5), the SiO-PAMAM-G1 was coated with PDA. Thus, the final product named SiO-PAMAM-PDA was obtained. The composite was characterized using a transmission electron microscope(TEM) and an increase in surface roughness indicated the successful grafting of PDA coating. Dopamine structure contains abundant benzene rings and amino and hydroxyl groups. It could bind with BUs through multiple secondary interactions, such as hydrogen bond and π-π stacking interaction. Therefore, the introduction of PDA could effectively enhance the affinity of the material toward benzoylurea insecticides. The prepared nanocomposites were used as sorbents in a dispersive micro solid-phase extraction approach(D-μ-SPE). The established approach was employed to extract and enrich the BUs in water samples before high-performance liquid chromatography(HPLC) analysis. Diflubenzuron, triflumuron, hexaflumuron, and teflubenzuron were chosen as target analytes. The following was a typical D-μ-SPE procedure. The prepared adsorbents measuring 40 mg were first dispersed in an 8-mL sample solution containing 150 g/L NaCl. The dispersion was assisted by 120-s vortexing to ensure full contact between the SiO-PAMAM-PDA and the targets. Next, the adsorbents were separated from the liquid phase by 4-min centrifugation(5 000 r/min). Thereafter, the adsorbed benzoylureas were eluted using 1 mL acetonitrile as desorption solvent by 120-s vortexing. Separated by centrifugation, the eluate was dried under a mild nitrogen stream. The solid remains were redissolved in 0.1 mL of acetonitrile, filtered by filter membrane(0.22 μm), and then analyzed by HPLC. The experimental conditions in the D-μ-SPE process could have a great impact on the extraction efficiency. Experimental conditions were optimized using a single factor optimization approach to further enhance the extraction recoveries. The optimized conditions included adsorbent amount, extraction time, desorption solvent type, desorption solvent volume, desorption time, and NaCl addition amount. Under the optimal conditions, a linearity range of 10-500 μg/L and limits of detection(LODs, S/N=3) of 1.1-2.1 μg/L were obtained. The extraction recoveries and relative standard deviations(RSDs) of the four BUs were 82.8%-94.1% and 2.1%-8.0%, respectively. The established approach was compared with reported approaches targeting benzoylurea insecticides. It was discovered that this approach consumed less sample, material, organic solvent, and pretreatment time. It provided a more rapid and green choice for the determination of benzoylurea pesticides. To determine the applicability, the proposed approach was applied to analyze the four benzoylurea insecticides in three river water samples. The real water samples were pretreated using the developed approach ahead of instrumental analysis, and no benzoylurea pesticides residue was detected. Next, standard addition experiments were performed under three spiking levels, including 15, 50, and 200 μg/L. The established approach had good accuracy and feasibility with satisfactory recoveries(69.5%-99.4%) and RSDs(0.2%-9.5%).