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Hydrogen peroxide detection has been widely applied in the fields of biology, medicine, and chemistry. Colorimetric detection of hydrogen peroxide has proven to be a fast and convenient method. In this work, 5,10,15,20-tetrakis(4-chlorophenyl) porphyrin modified Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$ nanocomposites (H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}})$ were prepared via a facile one-step hydrothermal method. H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$ nanocomposites were demonstrated to possess an enhanced mimetic peroxidase activity toward the substrate, 3,3$\prime$,5,5$\prime$-tetramethylbenzidine (TMB), which can be oxidized to oxTMB (oxidized TMB) in a buffer solution of hydrogen peroxide with a color change from colorless to blue. The catalytic activity of H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$ was further analyzed by steady-state kinetics, and H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$ had high affinity towards both TMB and H${}_{\mathrm{\text{2}}}$O${}_{\mathrm{\text{2}}}$. Furthermore, fluorescence and ESR data revealed that the catalytic mechanism of the peroxidase activity of H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$ is due to hydroxyl radicals generated from decomposition of H${}_{\mathrm{\text{2}}}$O${}_{\mathrm{\text{2}}}$. Based on the catalytic activity of H${}_{\mathrm{\text{2}}}$TClPP-Co${}_{\mathrm{\text{9}}}$S${}_{\mathrm{\text{8}}}$, a sensitive colorimetric sensor of H${}_{\mathrm{\text{2}}}$O${}_{\mathrm{\text{2}}}$ with a detection limit of 6.803 $\mu$M as well as a range of 7–100 $\mu$M was designed.

The development of peroxidase mimics with enhanced peroxidase-like activity is critical to building a convenient and fast glucose colorimetric sensor. Herein, a porphyrin-based conjugated microporous polymer (FePCMP) was synthesized through a Pd-/CuI catalyzed Sonogashira coupling reaction. The FePCMP exhibited specific and superior POD-like activity evaluated by the fast oxidation of 3,3$\prime$,5,5$\prime$-tetramethylbenzidine (a chromogenic substrate, TMB) to form the blue product (oxTMB) in the presence of H₂O₂. The outstanding POD-like activity is mainly ascribed to the Fe-N₄ active sites and the cross-linked porous framework of FePCMP. Furthermore, the FePCMP was applied in selective colorimetric detection of glucose through a glucose oxidase biocatalytic cascade reaction with a low detection limit (LOD) of 0.031 $\mu$M in the linear range of 0.2–5 $\mu$M. This study not only provided a new method for the design and synesis of specific POD-like nanozymes, but also the prepared FePCMP can be used as a POD-like enzyme for the colorimetric detection of other molecules, such as cholesterol, acetylcholine, etc.

A new method has been proposed to realize the visual detection of Cr³⁺ using 4-nitrobenzenethiol (4-NBT) and 4-mercaptobenzoic acid (4-MBA) modified silver nanoparticles (AgNPs). The presence of Cr³⁺ induces the aggregation of AgNPs through cooperative metal–ligand interaction, resulting in a color change from bright yellow to purple. Consequently, Cr³⁺ could be monitored by colorimetric response of AgNPs by a UV-Vis spectrophotometer or even naked eyes. We firstly used ethylene diamine tetraacetic acid (EDTA) as a masking agent to selectively detect Cr³⁺, and other metal ions have little influence on the Cr³⁺–AgNPs system. The cofunctionalized AgNPs exhibited a highly sensitive detection limit of Cr³⁺, which is as low as 5 × 10^-9 mol L^-1, and the absorbance ratio (A_600nm/A_387nm) is linear with the concentration of Cr³⁺ ranging from 5 × 10^-9 mol L^-1 to 2 × 10^-6 mol L^-1 with a coefficient of 0.993. Particularly, the sensor has been further evaluated to monitor the concentration of Cr³⁺ in drinking water, the recovery was in good agreement with those obtained by ICP-MS, indicating that this proposed method is successfully applied in real samples.

Cartap is among the most popular pesticides that are widely used to boost food production, however, its residues pose a great threat to human health and the environment. We presented simple and effective colorimetric sensor based on aggregation of gold nanoparticles (AuNPs) with appropriate diameter and fluorescent sensor via inner filter effect (IFE) of AuNPs on cadmium telluride quantum dots (CdTe QDs), respectively. Firstly, effect of diameter of AuNPs was investigated and the results indicated that AuNPs with diameter of 13nm (AuNPs${}_{13\mathrm{\text{nm}}})$ showed better sensitivity toward cartap. Thus, AuNPs${}_{13\mathrm{\text{nm}}}$ was chosen for colorimetric and fluorescent cartap assay. On one hand, mercaptoacetic acid (MA) was functionalized on AuNPs${}_{13\mathrm{\text{nm}}}$ for the improvement of anti-disturbance ability for discrimination study. A decent linear relationship for cartap was obtained in the range from 1$\mu$M to 50$\mu$M with detection limit of 1.32$\mu$M for colorimetric readout; on the other hand, fluorescent sensor based on AuNPs${}_{13\mathrm{\text{nm}}}$ displayed excellent linear relationship with cartap concentration varying from 20nM to 100nM with low detection limit of 4.02nM. And the above-mentioned sensor showed acceptable anti-disturbance ability for cartap discrimination. These results demonstrated that the sensor as-developed would be a great potential candidate for cartap detection in real application.

Predicting relative visual salient regions on three-dimensional (3D) meshes benefits many computer graphics applications. Most computation models for mesh saliency focus on geometrical information alone. Nevertheless, the ignored texture, lighting and material also provide more detailed appearance information, especially in the context of static scene rendering. In this paper, we propose a mesh saliency detection algorithm considering both geometrical and colorimetric information to address this challenge. Our model first computes the local curvature entropy at multi-scale to capture the geometrical details. Second, a set of images are projected onto the screen at several viewpoints with specified material and lighting model. Potentially salient regions on the rendered images are detected by fusion of multiple color difference maps measured with an approximated multi-scale Laplacian of Gaussian filter. A Gaussian distribution-based central bias model is applied to the image saliency map to emphasize the global rarity of salient regions. Third, the saliency maps of rendered images are projected back to the 3D mesh via the ray casting method. In the end, both saliency maps are combined linearly as the saliency map of 3D mesh. Experiment on the human fixation database demonstrates the performance of our method compared to the classic methods in terms of linear correlation coefficient and AUC.