Bioactive Chemical Constituents of Cercis chinensis

Chemistry of Natural Compounds -     

单斜ZnP2负极材料的锂化机理及性能

过渡金属磷化物电位低且比容量高, 是有发展前景的锂离子电池(LIBs)负极材料. 其中, ZnP₂属于双活性负极材料, Zn与P都能与Li⁺发生反应, 储Li⁺性能更具有竞争力. 但是, 对于ZnP₂的锂化机理及产物尚不明确. 采用第一性原理计算和电化学测试方法研究了ZnP₂的电子性质和电化学性能, 通过理论计算和实验测试相结合阐述了ZnP₂的锂化机制. 首先, 以密度泛函理论(DFT)计算揭示了ZnP₂的锂化机理、Li⁺扩散路径、势垒和理论比容量(1477 mAh/g). 其次, 通过直流电弧等离子体法及固相烧结法合成ZnP₂, 并测试其首圈放电曲线, 显示放电容量为1439 mAh/g, 与理论计算结果相近. 此外, 薄膜X射线衍射(XRD)检测最终产物成分为LiZn和Li₃P, 与DFT计算结果一致.     

A visible light responsive molecularly imprinted photoelectrochemical sensor for the sensitive detection of BSA

Journal of Solid State Electrochemistry - A molecularly imprinted photoelectrochemical (PEC) cathodic sensor was developed for the detection of bovine serum albumin (BSA). The PEC sensor was...     

Tissue distribution and excretion study of neopanaxadiol in rats by ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry

Neopanaxadiol (NPD), a major ginsenoside in Panax ginseng C. A. Meyer (Araliaceae), was reported to have neuroprotective effect. In this study, a method of ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry (UPLC/QTOF‐MS) was developed and validated for quantitative analysis of NPD in tissues, urine and feces, using liquid–liquid extraction (LLE) to isolate NPD from different biological samples, and chromatographic separation was performed on an Agilent Zorbax Stable Bond C₁₈ (2.1 × 50 mm, 1.8 µm) column with 0.1% formic acid in water and acetonitrile. All standard calibration curves were linear (all r² > 0.995) within the test range. After oral administration, NPD was extensively distributed to most of the tissues without long‐term accumulation. The higher levels were observed in stomach and intestine, followed by kidney and liver. Approximately 64.56 ± 20.32% of administered dose in feces and 0.0233 ± 0.0356% in urine were found within 96 h, which indicated that the major elimination route was fecal excretion. This analytical method was applied to the study of NPD distribution and excretion in rats after oral intake for the first time. The results we found here are helpful for us to understand the pharmacological effects of NPD, as well as its toxicity. Copyright © 2014 John Wiley & Sons, Ltd.     

Molecular structure and properties of click hydrogels with controlled dangling end defect

In this study, controlled amount of dangling ends is introduced to the two series of poly(ethylene glycol)‐based hydrogel networks with three and four crosslinking functionality by using click chemistry. The structure of the gels with regulated defect percentage is confirmed by comparing the results of low‐field NMR characterization and Monte Carlo simulation. The mechanical properties of these gels were characterized by tensile stress–strain behaviors of the gels, and the results are analyzed by Gent model and Mooney–Rivlin model. The shear modulus of the swollen gels is found to be dependent on the functionality of the network, and decreases with the defect percentage. Furthermore, the value of shear modulus well obeys the Phantom model for all the gels with varied percentage of the defects. The maximum extension ratio, obtained from the fitting of Gent model, is also found to be dependent on the functionality of the network, and does not change with the defect percentage, except at very high defect percentage. The value of the maximum extension ratio is between that predicted from Phantom model and the Affine model. This indicates that at the large deformation, the fluctuation of the crosslinking points is suppressed for some extend but still exists. Polymer volume fractions at various defect percentages obtained from prediction of Flory–Rehner model are found to be in well agreement with the swelling experiment. All these results indicate that click chemistry is a powerful method to regulate the network structure and mechanical properties of the gels. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 1227–1236     

Correlation‐assisted nearest shrunken centroid classifier with applications for high dimensional spectral data

High throughput data are frequently observed in contemporary chemical studies. Classification through spectral information is an important issue in chemometrics. Linear discriminant analysis (LDA) fails in the large‐p‐small‐n situation for two main reasons: (1) the sample covariance matrix is singular when p > n and (2) there is an accumulation of noise in the estimation of the class centroid in high dimensional feature space. The Independence Rule is a class of methods used to overcome these drawbacks by ignoring the correlation information between spectral variables. However, a strong correlation is an essential characteristic of spectral data. We proposed a new correlation‐assisted nearest shrunken centroid classifier (CA‐NSC) to incorporate correlation information into the classification. CA‐NSC combines two sources of information [class centroid (mean) and correlation structure (variance)] to generate the classification. We used two real data analyses and a simulation study to verify our CA‐NSC method. In addition to NSC, we also performed a comparison with the soft independent modeling of class analogy (SIMCA) approach, which uses only correlation structure information for classification. The results show that CA‐NSC consistently improves on NSC and SIMCA. The misclassification rate of CA‐NSC is reduced by almost half compared with NSC in one of the real data analyses. Generally, correlation among variables will worsen the performance of NSC, even though the discriminatory information contained in the class centroid remains unchanged. If only correlation structure information is used (as in the case of SIMCA), the result will be satisfactory only when the correlation structure alone can provide sufficient information for classification. Copyright © 2015 John Wiley & Sons, Ltd.