A 3×3 visible-light cross-reactive sensor array based on the nanoaggregation of curcumin in different pH and buffers for the multivariate identification and quantification of metal ions.

Here, a facilely constructed 3 × 3 visible-light cross reactive sensor array based on nanoaggregation of curcumin (Cur) is proposed for the identification and quantification of metal ions (MIs). Synthesis of nanocurcumin (NCur) was characterized by UV-Vis spectrophotometry, transmission electron microscopy (TEM) and Fourier transform infrared (FT-IR). The average particle size was estimated about 5.21 ± 1.13 nm) n = 50 (. Our sensor array consists of nine receptors with distinct but overlapping specificities for 11 MIs: Al, Cd, Co, Cu, Hg, Fe, Fe, Mn, Ni, Pb, and Zn. The receptors include the nine solutions of NCur at three buffers of phosphate, ammonium, and tris each at three pH of 7, 8, and 9 (in total 9 receptors). On account of different pH and buffers, NCur-MI binding affinities can be distinguished by monitoring the UV-Vis absorbance changes. These changes are optical fingerprints that can be used to identify each MI. The absorption values in sixteen wavelengths (i.e. 332, 352, 372, 392, 412, 432, 452, 472, 492, 512, 532, 552, 572, 592, 612, and 632 nm) are considered as analytical signals to quantitatively evaluate of the absorbance responses of the sensor array. A color difference map is provided to qualitatively visualize of the colorimetric sensor array responses. Under optimal conditions, the MIs are successfully discriminated in the range of 4-48 μmol L. The limit of detections (LODs) values ranged from 0.47 (for Fe) to 1.40 μmol L (for Pb). Furthermore, two different mixing sets of the MIs are prepared for multivariate multicomponent analysis. Finally, the suggested sensor array is employed to evaluate its practicability in the discrimination of MIs in samples of river water and serum. Moreover, it can identify the MIs in these samples. The sensor array presents a simple, save time, cost-effective, and environmentally friendly method for the identification and quantification of MIs.