Abstract

We report on an effective onsite optical sensor strategy using probe-decorated porous polymer monolith (PPM) and aluminum-based metal-organic framework (MIL-53 (Al) MOF) as a reliable colorimetric sensor for the detection of ultra-trace levels of Cr3+. MOFs and PPMs have attracted considerable interest in environmental applications due to their high surface area, perpetual porosity, and tunable structural network. Here, Al-MOF and PPM materials were used as porous templates for the uniform infusion of a chromoionophoric probe, i.e., (Z)-1,2-diphenyl-2-((4-(E)-phenyldiazenyl)phenyl)imino)ethan-1-ol (DPPE), for the solid-state colorimetric recognition and capturing of Cr3+ from aqueous medium. The structural morphology and surface topography of the sensor materials have been characterized using the transmission/scanning electron microscopy, optical spectroscopy, X-ray/electron diffraction, elemental mapping, surface area/pore volume and thermal analysis to understand the surface properties and stability features of the long-range ordered porous framework. The sensor's superior structural and surface features tender faster ion diffusion to the anchored probe sites within 60 s. The sensor induces a selective ligand-to-metal charge transfer (LMCT) chelation with Cr3+, resulting in a sequence of color transition from pale orange to sepia-brown, with incremental levels of Cr3+. The significance of physicochemical factors, such as pH, probe content, sensor dose, kinetics, temperature, reusability, selectivity, sensitivity, and stability, has been optimized to maximize the ion-sensing performance. The sensors' reusability has been tested by replicating the ion-sensing performance up to eight cycles. The solid-state sensor exhibited a linear range of 1.0–200 ppb for Cr3+, with a detection limit of 0.44 and 0.53 ppb and a quantification limit of 1.39 and 2.22 ppb for DPPE-loaded PPM and Al-MOF sensors, respectively. The practical utility of the sensor materials with industrial/environmental water samples reveals excellent data reliability/reproducibility (recovery ≥99.1 %; RSD ≤2.5 %) for real-time monitoring.

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