当前通过单粒子电感耦合等离子体质谱法分析土壤中纳米材料(NMs)的样品制备策略在准确性方面存在重大限制。样品通量和适用性(即,NMs和土壤的类型)。在这项工作中,系统研究了微波辅助萃取(MAE)对土壤NMs表征的优缺点。为此,测试了不同的萃取剂(超纯水;NaOH,NH4OH,柠檬酸钠和焦磷酸四钠)和MAE操作条件通过实验设计进行了优化。接下来,所开发的方法适用于不同类型的金属(oid)纳米粒子(Se-,Ag-,PT-和AuNP)和土壤(碱性,酸,sandy,clayey,SL36,壤土ERMCC141;污泥修正ERM483)。结果表明,通过使用20mL的0.1MNaOH溶液,可以在800W烘箱中在6分钟(12个循环,每个循环30s)内保存并从土壤中定量提取Pt和AuNPs。该方法适用于除富含粘土的样品外,具有广泛理化性质的土壤。如果黏土分数显著(>15%),NMs被有效地保留在土壤中,从而导致不良的回收率(<10%)。通过这种方法分析不稳定的NM例如Se-和AgNPs是不可行的,因为提取条件有利于溶解。最后,与目前的提取方法相比(例如,超声,浊点提取,等。),由于处理速度和同时处理多个样品的可能性,MAE提供更好或相当的准确度和精密度以及更高的样品处理量。
Current sample preparation strategies for nanomaterials (NMs) analysis in soils by means single particle inductively coupled plasma mass spectrometry have significant constrains in terms of accuracy, sample throughput and applicability (i.e., type of NMs and soils). In this work, strengths and weakness of microwave assisted extraction (MAE) for NMs characterization in soils were systematically investigated. To this end, different extractants were tested (ultrapure water; NaOH, NH4OH, sodium citrate and tetrasodium pyrophosphate) and MAE operating conditions were optimized by means of design of experiments. Next, the developed method was applied to different type of metallic(oid) nanoparticles (Se-, Ag-, Pt- and AuNPs) and soils (alkaline, acid, sandy, clayey, SL36, loam ERMCC141; sludge amended ERM483). Results show that Pt- and AuNPs are preserved and quantitatively extracted from soils in 6 min (12 cycles of 30 s each) inside an 800 W oven by using 20 mL of 0.1 M NaOH solution. This methodology is applicable to soils showing a wide range of physicochemical properties except for clay rich samples. If clay soil fraction is significant (>15%), NMs are efficiently retained in the soil thus giving rise to poor recoveries (<10%). The analysis of labile NMs such as Se- and AgNPs is not feasible by means this approach since extraction conditions favors dissolution. Finally, when compared to current extraction methodologies (e.g., ultrasound, cloud point extraction, etc.), MAE affords better or equivalent accuracies and precision as well as higher sample throughput due to treatment speed and the possibility to work with several samples simultaneously.