基于纳米金显色反应的阵列传感器结合化学计量学检测重金属离子

Sensor Array for Qualitative and Quantitative Analysis of Metal Ions and Metal Oxyanion Based on Colorimetric and Chemometrics

实验设计了一种灵敏度高、操作简单、价格低廉的阵列传感器可同时测定多种金属离子和金属含氧酸根。该方法基于纳米金显色反应的原理,结合化学计量学方法,利用230~800nm波段的光谱代替传统的单变量(A620/A520)分析方法建立PLS定量分析模型和PLS-DA分类模型,得到了满意的结果。我们利用氨基酸可以防止纳米金溶胶在高浓度氯化钠溶液中聚沉的性质设计一个基于氨基酸、纳米金颗粒和待测物之间竞争反应为基础的阵列传感器检测金属离子和金属含氧酸根。基于Cd^(2+),Ba^(2+),Mn^(2+),Ni ^(2+),Cu^(2+),Fe^(3+),Cr^(3+),Cr_2O_7^(2-),Sn^(4+),Pb^(2+)诱导氨基酸-AuNPs聚沉体系的紫外-可见光谱具有明显差异。PLS-DA模型成功地识别了水溶液中的九种金属阳离子和一个含氧酸根,分类准确率达到100%。利用化学计量学方法和上述阵列传感器同时定量分析了二元和三元体系(Cr^(3+)/Cr_2O_7^(2-),Fe^(3+)/Cd^(2+),Fe^(3+)/Cr^(3+)/Cr_2O_7^(2-))中的金属离子和金属含氧酸根。传感单元的增加进一步提高了该方法的准确性和可靠性,为复杂体系中金属离子和金属含氧酸根的定量分析提供了可能性。

A sensitive,flexible,and low cost method for the qualitative and quantitative analysis of metal ions and metal oxyanion based on the wide range ultraviolet and visible spectroscopy（UV-Vis）spectra of amino acid-gold nanoparticles（amino acidAuNPs）sensors in the range of 230800 nm was proposed.Different amino acids（L-Histidine,L-Lysine,L-Methionine,DPenicillium）which can prevent the AuNPs from aggregation of the in NaCl solution,were investigated to build multi-channel sensors responding to different ions induced AuNPs aggregation.The UV-Vis spectra of Cd2+,Ba2+,Mn2+,Ni 2+,Cu2+,Fe3+,Cr3+,Cr2 O72-,Sn4+,Pb2+induced amino acid-AuNPs were used for classification of different ions by using PLS-DA.Taking the advantage of the multivariate analysis,we quantified the ions in binary and ternary mixture systems(Cr3+/Cr2 O72-,Fe3+/Cd2+,Fe3+/Cr3+/Cr2 O72-),simultaneously.Data fusion further improved the prediction accuracy of the PLS models built on multiple amino acids-AuNPs sensors.The proposed method can also be used to analysis the metal ions or and metal oxyanion in more complex mixtures.