Miaomiao Chen,Meng Zhou,Caihong Mao,Chunchao Wu,Shujie Pang,Xudong Yang
Fluorescent hydrogel were developed for Fe(II) detection to overcome the shortcomings of simple carbon dots solutions (CDs), which are difficult to store and use. CDs were prepared using the hydrothermal synthesis with o -phenylenediamine and dopamine as the carbon sources. Fluorescent hydrogel (CACDs) were obtained by doping CDs in and impregnating them with carboxymethyl cellulose hydrogel (CA) prepared using crosslinked carboxymethyl cellulose (CMC), which was grafted using acrylamide as the substrate. Using CDs and CA as a fluorescent group and a backbone, respectively, enhanced the fluorescence performance and facilitated Fe(II) detection. The surface groups, elemental composition and optical properties of the prepared CDs and CACDs were systematically studied using FTIR, XRD, UV–Vis and fluorescence spectrometer. The effects of pH, temperature, NaCl salt solution and UV irradiation on the stability of CDs in the hydrogel were discussed. CACDs exhibited strong, bright yellow fluorescence with a fluorescence intensity 4.35 times higher than that of CDs. CACDs can be used as fluorescent probes to realise real-time detection of Fe(II) at a low detection limit (0.22 μM), allowing them to be employed for Fe(II) detection in real water samples. CACDs had stable adsorption properties for Fe(II). The adsorption process of metal ions conformed to pseudo-second order kinetics and Langmuir model, respectively. Therefore, CACDs are expected to be bifunctional materials for effective detection and removal of Fe(II).
Zhihao Liu,Tingting Yang,Yuwen Yan,Yongtao Tang,Jianxin Meng,Fengyu Li
Colorimetry is to determine the component content usually comparing or measuring the “RGB” values, which has the advantages of quick response and visual comparison. However, the widely reported “RGB” models are limited by requiring professional operation such as accurate sampling, insufficient information, cumbersome calculation, etc., which has significantly restricted the promotional application. Inspired by the PAA-PVA gel with excellent absorbing-swelling ability and superior response ability, indefinite volume addition has a significant difference in the swelling phenomenon of PAA-PVA hydrogel, the extent of this enlargement is directly related to the amount of testing sample absorbed, which can be applied to reflect testing sample volume added. In addition, benefited from a comprehensive and precise parameter network, the deep learning (DL) algorithm solves the defects such as ambient light effect and manual extract RGB values of the colorimetric sensing analysis strategy. Considering Fe(II) is an essential element for life science and environmental monitoring, we have developed a self-calibrating colorimetric sensor assisted deep learning strategy for the Fe(II) detection with indefinite volume. It can directly complete the analysis of Fe(II) concentration via captured images, without going through a complicated process similar to the RGB model. Specifically, we integrated the advantages of colorimetric sensing strategy, absorbing-swelling hydrogel, and DL algorithm to develop a phenanthroline (PHEN) indicator doped PAA-PVA colorimetric sensor (PHEN-PAA-PVA). Then, 2,500 colorimetric response images were collected as the training dataset and assessed 2 DL algorithms and 7 machine learning (ML) algorithms. The convolutional neural network (CNN) model exhibited the most efficiency to quantify 1×10 −5 -9×10 −4 mol/L Fe(II), with a limit of detection (LOD) of 3.3×10 −6 mol/L. It provides a promising and blooming in-situ detection approach for Fe(II) analysis, contributes to health management and environment monitoring.
Herein, we develop a simple electrochemical sensor based on the confinement effect of vertically ordered mesoporous silica film (VMSF) and the o-phenanthroline (Phen) chelating agent for ultrasensitive determination of ferrous ions (Fe2+). Fe(Phen)32+ obtained from the chelation between Fe2+ and Phen, shows higher electrochemical activity and larger geometric dimensions compared with free Fe2+, which could be effectively preconcentrated into the inner nanochannels of VMSF through spatial and electrostatic confinement effects. Differing from the conventional anodic stripping voltammetry, Fe(Phen)32+ could be enriched by convenient mechanical stirring and further detected by VMSF-modified indium tin oxide (VMSF/ITO), achieving an outstanding detection performance in terms of a linear range (1.0 nM–13.0 μM) and a limit of detection (LOD, 0.66 nM). Moreover, the established electrochemical sensor can accurately measure total iron and distinguish between different valence states (Fe2+ or Fe3+) with the help of reducing agents. Thanks to the outstanding antifouling ability of VMSF, the sensing platform consisting of VMSF/ITO and Phen chelating agent enables the precise determination of Fe2+ in complex real samples including tap water, pond water, FeSO4 tablets, and even colored samples, which can avoid the tedious sample pretreatment process and be applied in a wide range of scenarios.
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