College of Information and Electrical Engineering, Shenyang Agricultural University, Shenyang, 110866, China.
Beijing Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, 100097, China.
Sci Rep. 2019 Jul 18;9(1):10443. doi: 10.1038/s41598-019-46924-z.
The determination of heavy metals in drinking water is of great importance, but it is hard to realize rapid and in-situ measurement. Laser-induced breakdown spectroscopy is an effective method for both solid and liquid sample analysis with advantages of fast and micro-destructive. However, the concentrations of heavy metals in drinking water is too low to be directly detected using LIBS. In this study, we enhanced the sensitivity of LIBS by coupling with chelating resin, which is usually used for water purification. The resin provided a rapid enrichment of the heavy metal, so the limits of detection of common LIBS system was much enhanced. Using Cadmium as the representative heavy metal, PLSR model for predicting Cd were built based on the spectral intensity (Cd 214.4 nm) with concentrations from 0 to 100 µg/L, and resulted in correlation coefficient of 0.94433 and RMSE of 7.1517 µg/L. The LoD was 3.6 µg/L. Furthermore, the volume, resin mass, adsorption time, and LIBS system parameters were optimized for practical applications. We also demonstrated that the resin can be recycled without loss in sensing ability. The combination of chelating resin with LIBS provides inexpensive, rapid, and sensitive detection method of trace heavy metal contaminants in drinking water.
饮用水中重金属的测定非常重要，但很难实现快速现场测量。激光诱导击穿光谱学是一种用于固体和液体样品分析的有效方法，具有快速和微破坏性的优点。然而，饮用水中重金属的浓度太低，无法直接使用 LIBS 进行检测。在本研究中，我们通过与螯合树脂耦合来提高 LIBS 的灵敏度，螯合树脂通常用于水净化。树脂提供了重金属的快速富集，因此大大提高了常见 LIBS 系统的检测限。以镉为例，基于浓度为 0 至 100μg/L 的光谱强度（Cd 214.4nm），建立了用于预测 Cd 的 PLSR 模型，相关系数为 0.94433，RMSE 为 7.1517μg/L。检测限为 3.6μg/L。此外，还优化了体积、树脂质量、吸附时间和 LIBS 系统参数，以满足实际应用的要求。我们还证明了树脂可以在不损失传感能力的情况下回收利用。螯合树脂与 LIBS 的结合为饮用水中痕量重金属污染物提供了一种廉价、快速和灵敏的检测方法。
