Rossi Andrea, Cuccioloni Massimiliano, Pellegrino Francesco, Giovannetti Rita, Alladio Eugenio
Department of Chemistry and NIS Centre, University of Torino, Via Giuria 7, 10125 Torino, Italy.
School of Science and Technology, Chemistry Division, University of Camerino, 62032 Camerino, Italy.
Nanomaterials (Basel). 2025 Jan 2;15(1):57. doi: 10.3390/nano15010057.
Heavy metals are life-threatening pollutions because of their great toxicity, long-term persistence in nature and their bioaccumulation in living organisms. In this work, we performed multivariate curve resolution-alternating least squares analysis of UV-Vis raw spectra received by a colorimetric sensor constructed on mercaptoundecanoic acid functionalized silver nanoparticles (AgNPs@11MUA) to detect Cd, Cu, Mn, Ni, and Zn in water. This combined approach allowed the rapid identification and quantification of multiple heavy metals and showed adequate sensitivity and selectivity, thus representing a promising analytical and computational method for both laboratory and field applications such as environmental safety and public health monitoring.
重金属因其极高的毒性、在自然界中的长期持久性以及在生物体中的生物累积性而成为威胁生命的污染物。在本研究中,我们对基于巯基十一烷酸功能化银纳米颗粒(AgNPs@11MUA)构建的比色传感器所接收的紫外-可见原始光谱进行了多元曲线分辨-交替最小二乘法分析,以检测水中的镉、铜、锰、镍和锌。这种联合方法能够快速识别和定量多种重金属,具有足够的灵敏度和选择性,因此是一种用于实验室和现场应用(如环境安全和公共卫生监测)的有前景的分析和计算方法。