Novel ultrasensitive Raman assay method based on enzyme mimetics for ultra trace of H2O2.

Enzyme mimetics have been widely applied on H2O2 assay, but it is still challenging and interesting to realize the sensitive detection for ultra-trace H2O2. Here, an ultrasensitive Raman assay method based on novel WO3@IP6-Fe3+ enzyme mimetics with peroxidase-like activity was established. WO3 microspheres (MSs) were found to have weak peroxidase-like activity, and the combination of IP6-Fe3+ and WO3 can produce stronger activity. WO3@IP6-Fe3+ MSs showed polyhedron-like structure, uniform size, and smooth surface. Although WO3@IP6-Fe3+ enzyme mimetics have low catalytic efficiency and high absorbance background, the proposed Raman method can bypass the above problems. In Raman method, high concentration of WO3@IP6-Fe3+ can be used to overcome low catalytic efficiency without high absorbance background. Moreover, 3,3',5,5'-tetramethylbenzidine oxide has prominent characteristic Raman peak at 1608 cm-1, greatly improving the sensitivity and eliminating interference of impurities. Due to the high sensitivity and low background, Raman assay showed the ultra-low limit of detection (5.49 × 10-15 M), which was 4-7 orders of magnitude lower than other detection methods. The ultrasensitive Raman assay not only provided the possibility for the enzyme mimetics-based detection of ultra-trace H2O2, but also enable the enzyme mimetics with low activity to be applied.

Self-assembled Cr2O3@nanogel/Au nanozymes to simulate peroxidase activity as a H2O2 sensor.

The low temperature solvothermal method synthesized Cr2O3 NPs has not only peroxidase activity, but also oxidase activity. Then, the oxidase activity of Cr2O3 NPs is effectively shielded by nanogel immobilization using three monomers acrylamide, NIPAAM (N-isopropylacrylamide) and MBA (N,N'-methylene bisacrylamide) in HEPES (4-(2-hydroxyerhyl)piperazine-1-erhanesulfonic acid) buffer. Ultimately, the enzymatic activity of Cr2O3@nanogel/Au is significantly enhanced after doping Au NPs by SERS (Surface Enhanced Raman Spectroscopy) evaluation. A SERS strategy was proposed for the detection of H2O2 by Cr2O3@nanogel/Au. The linear range was 10-8 mol·L-1-10-1 mol·L-1.

Synergistic function of Au NPs/GeO2 nanozymes with enhanced peroxidase-like activity and SERS effect to detect choline iodide.

A novel Au NPs/GeO2 nanozymes are developed as Surface-Enhanced Raman Scattering (SERS) substrates with the promising prospect for detection ChI. Herein, it is discovered that both Au NPs and GeO2 nanozymes have peroxidase-like activity, catalyzing colorless 3,3',5,5'-tetramethylbenzidine (TMB) to produce blue TMBox. Interestingly, compared with single Au NPs or GeO2 nanozymes, the Au NPs/GeO2 nanozymes show stronger peroxidase-like activity, and significantly ameliorated SERS signal of TMBox. The mentioned two enhancements are ascribed to a positive synergistic function of Au NPs/GeO2 nanozymes. Surprisingly, choline iodide (ChI) can inhibit the positive synergy in Au NPs/GeO2 nanozymes, and slow down the reaction of TMB-H2O2-Au NPs/GeO2 system. On this foundation, a new Au NPs/GeO2 SERS technique with high sensitivity, label-free detection method of choline iodide (ChI) is established, suggesting that Au NPs/GeO2 nanozymes have the potential application of water environment.

Simultaneous identification of contaminant sources and hydraulic conductivity field by combining geostatistics method with self-organizing maps algorithm.

In the contaminant remediation of groundwater, the release history of contaminant sources and hydraulic conductivity field are two key parameters that need to know, but their actual values are difficult to obtain and can only be inversely identified by limited measured data. However, the process of solving the inverse problem needs to repeatedly call the forward model of contaminant transport, which is very time-consuming, especially for the high-dimensional inverse problems. In this study, based on the training data generated from a prior range of parameters (the release strength of contaminant sources and hydraulic conductivity at pilot points), the self-organizing maps (SOM) algorithm was employed to construct the surrogate model for the numerical model of contaminant transport in a simplified hypothetical aquifer, then the surrogate model was used to retrieve jointly the contaminant strength of sources and the hydraulic conductivity at pilot points, and the Kriging method of geostatistics was further used to process the estimated K-values at pilot points to obtain the hydraulic conductivity field. Also, to investigate the ability of the SOM-based surrogate model for retrieving both contaminant source strengths and hydraulic conductivity, we gradually expanded the prior range and increased the number of inversion terms in each prior range. Moreover, the robustness of the SOM-based surrogate model for inversion was illustrated by proposing the scarcity of data and different degrees of measurement error in the limited actual observation data. When the actual observation data is reduced by 2/3, the Root Mean Square Error (RMSE) of retrieving source strengths and hydraulic conductivity at pilot points are 1.07 and 0.09, respectively. The results indicated the SOM-based surrogate model shows remarkable inversion precision and robustness, and an accurate estimation of the actual hydraulic conductivity field could be obtained by the Kriging method based on that.

A facile SERS strategy to detect glucose utilizing tandem enzyme activities of Au@Ag nanoparticles.

Surface-Enhanced Raman Scattering (SERS) is a powerful analysis technology, attracting more and more attention due to its high sensitivity and selectivity. Herein, we report a simple seed-mediated method to synthesize Au@Ag nanoparticles (NPs) as a multifunctional biosensor for the label-free detection of hydrogen peroxide (H2O2) and glucose by SERS. Au@Ag NPs, as an ultrasensitive SERS substrate, show the dual activities (peroxidase-like and GOx-like activities). Under the condition of pH 4.0 NaAc buffer solution, the glucose and H2O can be catalyzed by Au@Ag NPs to produce glucose acid and H2O2, and then H2O2 can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to form a blue oxidation product oxidic TMB (oxTMB) which exhibits strong SERS signals at 1188, 1330, 1605 cm-1. Thus, we have developed a new SERS strategy for analysis of glucose with a detection limit of 5 × 10-10molL-1, suggesting that Au@Ag NPs have the potential for biosensor, immunoassay and medical treatment.