Wei Dali, Zhang Hu, Tao Yu, Wang Kaixuan, Wang Ying, Deng Chunmeng, Xu Rongfei, Zhu Nuanfei, Lu Yanyan, Zeng Kun, Yang Zhugen, Zhang Zhen
School of Emergency Management, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China.
School of Water, Energy, and Environment, Cranfield University, Milton Keynes MK43 0AL, U.K.
Anal Chem. 2024 Mar 26;96(12):4987-4996. doi: 10.1021/acs.analchem.4c00108. Epub 2024 Mar 11.
Surfactants are considered as typical emerging pollutants, their extensive use of in disinfectants has hugely threatened the ecosystem and human health, particularly during the pandemic of coronavirus disease-19 (COVID-19), whereas the rapid discrimination of multiple surfactants in environments is still a great challenge. Herein, we designed a fluorescent sensor array based on luminescent metal-organic frameworks (UiO-66-NH@Au NCs) for the specific discrimination of six surfactants (AOS, SDS, SDSO, MES, SDBS, and Tween-20). Wherein, UiO-66-NH@Au NCs were fabricated by integrating UiO-66-NH (2-aminoterephthalic acid-anchored-MOFs based on zirconium ions) with gold nanoclusters (Au NCs), which exhibited a dual-emission features, showing good luminescence. Interestingly, due to the interactions of surfactants and UiO-66-NH@Au NCs, the surfactants can differentially regulate the fluorescence property of UiO-66-NH@Au NCs, producing diverse fluorescent "fingerprints", which were further identified by pattern recognition methods. The proposed fluorescence sensor array achieved 100% accuracy in identifying various surfactants and multicomponent mixtures, with the detection limit in the range of 0.0032 to 0.0315 mM for six pollutants, which was successfully employed in the discrimination of surfactants in real environmental waters. More importantly, our findings provided a new avenue in rapid detection of surfactants, rendering a promising technique for environmental monitoring against trace multicontaminants.
表面活性剂被视为典型的新兴污染物,它们在消毒剂中的广泛使用对生态系统和人类健康构成了巨大威胁,尤其是在新型冠状病毒肺炎(COVID-19)大流行期间,而快速鉴别环境中的多种表面活性剂仍然是一项巨大挑战。在此,我们设计了一种基于发光金属有机框架(UiO-66-NH@Au NCs)的荧光传感器阵列,用于特异性鉴别六种表面活性剂(AOS、SDS、SDSO、MES、SDBS和吐温-20)。其中,UiO-66-NH@Au NCs是通过将UiO-66-NH(基于锆离子的2-氨基对苯二甲酸锚定的金属有机框架)与金纳米团簇(Au NCs)整合而制备的,其具有双发射特征,发光良好。有趣的是,由于表面活性剂与UiO-66-NH@Au NCs的相互作用,表面活性剂可以差异性地调节UiO-66-NH@Au NCs的荧光特性,产生多样的荧光“指纹”,并通过模式识别方法进一步识别。所提出的荧光传感器阵列在识别各种表面活性剂和多组分混合物方面达到了100%的准确率,六种污染物的检测限在0.0032至0.0315 mM范围内,该阵列已成功应用于实际环境水样中表面活性剂的鉴别。更重要的是,我们的研究结果为表面活性剂的快速检测提供了一条新途径,为针对痕量多污染物的环境监测提供了一项有前景的技术。