A novel, simple, and rapid method is presented for the analysis of aflatoxin B1, aflatoxin B2, and ochratoxin A in rice samples by dispersive liquid–liquid microextraction combined with LC and fluorescence detection. After extraction of the rice samples with a mixture of acetonitrile/water/acetic acid, mycotoxins were rapidly partitioned into a small volume of organic solvent (chloroform) by dispersive liquid–liquid microextraction. The three mycotoxins were simultaneously determined by LC with fluorescence detection after precolumn derivatization for aflatoxin B1 and B2. Parameters affecting both extraction and dispersive liquid–liquid microextraction procedures, including the extraction solvent, the type and volume of extractant, the volume of dispersive solvent, the addition of salt, the pH and the extraction time, were optimized. The optimized protocol provided an enrichment factor of approximately 1.25 and with detection of limits (0.06–0.5 μg/kg) below the maximum levels imposed by current regulations for aflatoxins and ochratoxin A. The mean recovery of three mycotoxins ranged from 82.9–112%, with a RSD less than 7.9% in all cases. The method was successfully applied to measure mycotoxins in commercial rice samples collected from local supermarkets in China. 相似文献
By using light sensors of the cellphone, we build a simple photometer which can be used in quantitative analysis experiments. We have performed 5 replicate measurements of iron with phenanthroline to verify reproducibility and stability. We find the absorbance of the sample has a good linear relationship with the concentrations of iron with a R2 value around 0.999 and the RSD of 2.81%. The result is 4.94 μg·mL-1 with spectrophotometer and 5.11 μg·mL-1 with our photometer. The photometer is simple, convenient, accurate and realistic by using a phone as detector, which can replace the traditional spectrophotometer in the laboratory class. The students can enhance their understanding of the structure and principle of spectrophotometer by the DIY photometer experiment. 相似文献
The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid‐liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research. 相似文献
Science China Chemistry - Controlling molecular magnetic anisotropy via structural engineering is delicate and fascinating, especially for single-molecule magnets (SMMs). Herein a family of... 相似文献
Aiming at the difficult identification of fractional order Hammerstein nonlinear systems, including many identification parameters and coupling variables, unmeasurable intermediate variables, difficulty in estimating the fractional order, and low accuracy of identification algorithms, a multiple innovation Levenberg–Marquardt algorithm (MILM) hybrid identification method based on the fractional order neuro-fuzzy Hammerstein model is proposed. First, a fractional order discrete neuro-fuzzy Hammerstein system model is constructed; secondly, the neuro-fuzzy network structure and network parameters are determined based on fuzzy clustering, and the self-learning clustering algorithm is used to determine the antecedent parameters of the neuro-fuzzy network model; then the multiple innovation principle is combined with the Levenberg–Marquardt algorithm, and the MILM hybrid algorithm is used to estimate the linear module parameters and fractional order. Finally, the academic example of the fractional order Hammerstein nonlinear system and the example of a flexible manipulator are identified to prove the effectiveness of the proposed algorithm.
Separators are indispensable components of modern electrochemical energy storage devices such as lithium-ion batteries (LIBs).They perform the critical function... 相似文献