This study presents a dual-functional thin film, known as Ag nanoparticles decorated, ZnO nanorods coated silica nanofibers (AgNP-ZnONR-SNF), which demonstrates remarkable capabilities in both water purification and organic pollutants sensing. The 3D fibrous structure of ZnONR-SNF provides a large surface-area-to-volume ratio for piezo- and photo-catalytic degradation of organic pollutants under UV irradiation, achieving over 98% efficiency. Ag nanoparticles decorated on ZnONR-SNF form “hot-spot” that significantly enhance the surface-enhanced Raman spectroscopy (SERS) signal, resulting in an enhancement factor of 1056 and an experimental detection limit of 1 pg mL⁻¹. Furthermore, a machine learning algorithm is developed for the qualitative and quantitative detection of multiple contaminants, achieving high accuracy (92.3%) and specificity (89.3%) without the need for preliminary processing of Raman spectra. This work provides a promising nanoengineering solution for water purification and sensing with improved detection accuracy, purification efficiency, and cost-effectiveness.

这项研究提出了一种双功能薄膜，称为银纳米颗粒装饰、氧化锌纳米棒涂覆的二氧化硅纳米纤维（AgNP-ZnONR-SNF），它在水净化和有机污染物传感方面表现出卓越的能力。ZnONR-SNF的3D纤维结构为紫外线照射下的有机污染物的压电和光催化降解提供了大的表面积与体积比，实现了超过98%的效率。装饰在ZnONR-SNF上的Ag纳米粒子形成“热点”，显着增强表面增强拉曼光谱（SERS）信号，导致增强因子为1056，实验检测限为1 pg mL ^-1。此外，还开发了一种机器学习算法，用于多种污染物的定性和定量检测，无需对拉曼光谱进行初步处理即可实现高精度（92.3%）和特异性（89.3%）。这项工作为水净化和传感提供了一种有前景的纳米工程解决方案，提高了检测精度、净化效率和成本效益。