State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China.
State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.
Anal Chem. 2024 Jun 11;96(23):9399-9407. doi: 10.1021/acs.analchem.4c00234. Epub 2024 May 28.
Fast and efficient sample pretreatment is the prerequisite for realizing surface-enhanced Raman spectroscopy (SERS) detection of trace targets in complex matrices, which is still a big issue for the practical application of SERS. Recently, we have proposed a highly performed liquid-liquid extraction (LLE)-back extraction (BE) for weak acids/bases extraction in drinking water and beverage samples. However, the performance efficiency decreased drastically on facing matrices like food and biological blood. Based on the total interaction energies among target, interferent, and extractant molecules, solid-phase extraction (SPE) with a higher selectivity was introduced in advance of LLE-BE, which enabled the sensitive (μg L level) and rapid (within 10 min) SERS detection of both koumine (a weak base) and celastrol (a weak acid) in different food and biological samples. Further, the high SERS sensitivity was determined unmanned by Vis-CAD (a machine learning algorithm), instead of the highly demanded expert recognition. The generality of SPE-LLE-BE for various weak acids/bases (2 < p < 12), accompanied by the high efficiency, easy operation, and low cost, offers SERS as a powerful on-site and efficient inspection tool in food safety and forensics.
快速高效的样品前处理是实现复杂基质中痕量目标表面增强拉曼光谱（SERS）检测的前提，这仍然是 SERS 实际应用中的一个大问题。最近，我们提出了一种高效的液-液萃取（LLE）-反萃取（BE）方法，用于饮用水和饮料样品中弱酸/弱碱的提取。然而，面对食品和生物血液等基质时，其性能效率会急剧下降。基于目标、干扰物和萃取剂分子之间的总相互作用能，我们在 LLE-BE 之前引入了具有更高选择性的固相萃取（SPE），从而能够在不同的食品和生物样品中灵敏（μg L 级）和快速（10 min 内）SERS 检测苦木碱（弱碱）和雷公藤红素（弱酸）。此外，Vis-CAD（一种机器学习算法）可以无人值守地确定高 SERS 灵敏度，而不是高度依赖专家识别。SPE-LLE-BE 对各种弱酸/弱碱（2<p<12）的通用性，以及高效率、易操作和低成本，为食品安全和法医学提供了一种强大的现场和高效的检测工具。
