Functionalized hexagonal mesoporous silica monoliths with hydrophobic azo-chromophore for enhanced Co(II) ion monitoring

Abstract

We introduce here new optical strips for the colorimetric monitoring of Co(II) ions in an aqueous solution. The optical nanosensors were designed by direct immobilizing azo-chromophore with long hydrophobic tails onto hexagonal mesoporous silica monoliths (HOM-2). Although, azo-dye probe was used as signaling reporter for selective detection of the Co(II) analyte up to 10−6 mol/dm3 in solution, the tailoring of the Co(II) ion-sensing functionality was successfully manipulated up to 10−9 mol/dm3 with the incorporation of azo-chromophore into hexagonal mesoporous silica monoliths (HOM-2), which led to small, easy-to-use optical sensor strips. However, our simple design of colorimetric sensors is based on a physical adsorption of chemically responsive dyes onto HOM materials followed by stronger dye-analyte interactions in aqueous sensing systems. No elution of the probe molecules was evident with the addition of Co(II) analyte ions during the sensing process. The binding of Co(II) ions with probes led to the color change of nanosensors corresponding to the formation of the metal-chelate [Co(II)-Probe]n+ complexes. Results indicated that hexagonal nanosensors offer one-step and simple sensing procedures for both quantification and visual detection of Co(II) ions without the need for sophisticated instruments. However, the solid HOM-2 materials immobilized by the these indicator dyes, in principle, could be used as preconcentrators to yield high adsorption capacity and preconcentration efficiency, leading to simultaneously visual inspection and simple detection over a wide, adjustable range of Co(II) ions even at trace levels. For Co(II) ion selectivity assays, negligible changes in either the developed color or the reflectance intensities of the [Co-Probe]n+ complex were observed, despite the addition of competitive cations. Moreover, the hexagonal nanosensors are reversible and have the efficient potential to serve for multiple analyses.