Chiral separation of amino acids derivatized with fluoresceine-5isothiocyanate by capillary electrophoresis and laser-induced fluorescence detection using mixed selectors of beta-cyclodextrin and sodium taurocholate

Chiral separation of 20 pairs of amino acids derivatized with fluoresceine-5-isothiocyanate (FITC) by capillary electrophoresis and laser-induced fluorescence detection was studied using the mixture of beta-cyclodextrin (beta-CD) and sodium taurocholate (STC) as selector. Resolution was considerably superior to that obtained by using either beta-CD or STC alone. The molar ratio of beta-CD to STC of about 2:3 was found to be critical to achieve maximum separation. At this beta-CD-to-STC ratio, chiral separation occurred at really low total concentration of beta-CD and STC (<0.1 mM). Other impacting factors were investigated including the total concentration of beta-CD and STC, pH, and capillary conditioning procedure between two successive runs. Using a running buffer of 80 mM borate containing 20 mM beta-CD and 30 mM STC at pH 9.3, all of the 20 pairs of FITC-amino acid enantiomers were baseline resolved. The resolutions of the most pairs of the amino acid enantiomers (17 of 20) were higher than 3.0, only three pairs gave a resolution lower than 3.0 but higher than 1.90 (beta-phenylserine, pSer). The highest resolution reached 14.58 (Glu). Two derivatives of beta-CD, 2-hydroxypropyl-beta-CD (HP-beta-CD) and heptakis(2,6-di-O-methyl)-beta-CD (DM-beta-CD) were also explored. HP-beta-CD showed similar cooperative effect with STC, while DM-beta-CD together with STC led to poorer chiral separation.     

SURFACE-ENHANCED RESONANCE RAMAN SCATTERING SPECTROSCOPY AS A SURFACE TOPOGRAPHY PROBE IN PLANT PHOTOSYNTHETIC MEMBRANES

Strong resonance Raman (RR) and surface-enhanced resonance Raman scattering (SERRS) signals from carotenoids were detected from thylakoid (stromal-side out) vesicles and inside-out (lumenal-side out) vesicles isolated from spinach chloroplasts. The intensity of the signals from both types of membranes was comparable, indicating that plant carotenoids are exposed on or close to both surfaces or sides of the thylakoid membrane. This is in contrast to previous studies with bacterial photosynthetic membranes (Picorel et al., 1988, J. Biol. Chem. 263 , 4374–4380; and 1990, Biochemistry 29 , 707–712) that show carotenoids selectively located on the cytoplasmic side. In addition_; strong RR and SERRS signals were detected from stacked and unstacked photosystem-II-enriched membrane fragments, demonstrating that carotenoids are also exposed on both surfaces of the appressed region of the thylakoid membrane. Antibodies against the photosystem (PS) II extrinsic proteins blocked SERRS signals from stacked PS II membrane fragments, but only partially affected the SERRS signals from unstacked membranes. The results indicate that these antibodies, which preferentially cover the surface of the original lumenalside of the appressed region, act as spacers between the membrane and SERRS electrode surfaces. The original stromal-side of the appressed region is unaffected. These findings verify the distance sensitivity of the SERRS technique and underscore the above conclusion about the location of carotenoids in the appressed regions. Finally, SERRS signals are sensitive to membrane aging and storage temperature; caution is suggested to those applying SERRS spectroscopy to intact membrane systems.     

Ring-opening reactions of arylvinylidenecyclopropanes with diaryl diselenide upon heating: formation of 1,2-diarylselenocyclopentene derivatives

Arylvinylidenecyclopropanes undergo a novel reaction upon heating at 150 °C with diaryl diselenide to give the corresponding 1,2-diarylselenocyclopentene derivatives in good to high yields within 1.5 h. The further transformation of 1,2-diarylselenocyclopentene derivatives has been disclosed.     

电爆炸箔断路开关的理论和实验研究

 采用金属箔电爆炸过程的二维数值计算模型，对含电爆炸金属箔断路开关的电感储能脉冲功率调节系统进行了数值计算。以此为基础，研制出了一种低电感型的电爆炸箔断路开关，并以4μF/75kV脉冲电容器组作为初级能源，13Ω电阻作为负载进行实验研究。研究结果表明：在负载上可获得约250kV，脉宽大于400ns的脉冲电压。     

Butterfly and Nest-Shaped Tp*-W-Cu-S Cluster Monomers and Dimers with Hexamethylenetetramine as Ligand: Anion-Dependent Structures and Nonlinear Optical Properties

The assembly of[Et4N][Tp*WS3](1) with CuX (Tp* =hydridotris(3,5-dimethylpyrazol-1-yl)borate;X =Cl,Br,and I) or[Cu(MeCN)4][PF6]in the presence of tetratopic liga...     

能量选择中子成像技术及其应用

能量选择中子成像技术是利用特定范围波长(能量)的中子进行成像。在热/冷中子范围内(<25meV),能量选择中子成像技术主要基于布拉格边效应和衍射机制,相比常规中子成像技术不但可以显著提高图像对比度,而且能分析应变、应力、织构。在超热中子范围内(>1eV),能量选择中子成像技术主要基于中子共振吸收,中子截面随能量变化是同位素特有的,存在明显的共振吸收峰,因此可以进行同位素的“指纹”识别。能量选择中子成像技术在工程、材料、化学、物理、生物、考古等众多科研领域中有着非常广阔的应用前景。     

基于激光诱导击穿光谱(LIBS)的煤灰熔点快速检测

炉内结渣是影响火电机组和气化工艺可靠运行的关键因素之一,准确预测灰熔点可以提前调整炉膛出口温度以避免结渣。本论文采用激光诱导击穿光谱（LIBS）采集煤灰样中金属元素的光谱,分别建立煤灰中的金属元素的谱线强度与煤灰熔点的随机森林模型、支持向量机回归模型和线性回归模型,直接预测煤灰熔点温度。采用基于马氏距离(MD)的异常数据剔除算法和基于稀疏矩阵的基线估计与降噪算法（BEADS）,对粉煤灰样的全光谱数据进行了预处理。随机森林模型对粉煤灰熔点的预测平均相对误差（MRE）为54.74%,支持向量机回归模型的预测平均相对误差为60.08%,而线性回归模型的预测平均相对误差达到了9.78%。研究结果表明,线性回归模型对煤灰熔点的预测结果更准确。     

桑白皮中21种无机元素的测定及其质量评价

为准确了解不同产区桑白皮中多种元素分布及含量情况,用65%硝酸溶液对其样品进行微波消解处理,后采用电感耦合等离子体质谱（ICP-MS/MS）法测定桑白皮样品中21种元素的含量。得到21种元素的线性关系良好,R2 > 0.999,方法学考察试验的RSD均小于3%,加样回收率在91.32%~108.84%之间,RSD均小于4%;Al、Ga、Sr、Ba相比而言含量较大,且不同产区的特异性较明显;主成分分析中17批样品得到4个主成分,累计方差贡献率达 87.380%,确定V、Co、Al、Li、As、Se、Pb、U、Zn、Cr、Cd、Ga、Ba、Cs、Ni等15种元素为桑白皮药材的特征元素;相关性分析可知,元素间的相关性较强, P≤0.05的元素与主成分分析的特征元素基本一致。参照2020年版《中国药典》中对中药材中有害元素的限量规定,发现桑白皮样品中Pb、Cd、As、Cu有害元素的含量均未超过限量要求。ICP-MS/MS能准确快速测定桑白皮中21种元素含量情况,这对评价不同产区桑白皮质量,完善桑白皮质量标准具有一定参考价值。     

粉末压片-X荧光光谱法测定过磷酸钙中硫含量

硫是过磷酸钙中重要营养指标之一,为准确快速测定过磷酸钙中硫的含量,试验采用粉末压片-X荧光光谱法,将过磷酸钙试样充分干燥后研磨至粒度小于74 μm,采用硼酸镶边,在压力18 Mpa条件下保压30 s,制成样片。通过在过磷酸钙样品中添加不同质量的纯物质硫酸钙（质量分数范围1.52 %～17.21 %）,经过专用混匀设备混合均匀后,与试样压片相同条件下压制标准样片,作为过磷酸钙中硫的标准样品,建立硫标准曲线,曲线线性相关系数R2为0.9995,采用经验系数法校正干扰,建立了粉末压片-波长色散X射线荧光光谱法测定过磷酸钙中硫含量的方法, 方法检出限为0.002 %。对3个不同硫含量的过磷酸钙样品采用本实验方法重复测量7次,RSD在1.4 %~3.1 %,方法精密度性好,同时用高温燃烧红外光谱法和电感耦合等离子发射光谱法对比,三者测量结果相对极差小于2.0 %,测量结果无显著性差异。此方法不需要对样品进行熔融或溶解,样品制备简单,数据准确度和稳定性好,分析效率高,适合大批量样品中硫的测定。     

水体透射光谱结合主成分分析(PCA )改进化学需氧量(COD)含量估算研究

化学需氧量（Chemical Oxygen Demand,COD）是水体有机污染的一项重要指标,化学需氧量越高,表示水污染程度越严重。 为了解决传统的COD测量方法耗时较长,不利于快速、实时地获取水体中COD的信息等问题。本文提出了基于透射光谱测量结合主成分分析(Principal Component Analysis, PCA)改进水体COD含量估算模型。具体的,采集100组COD水体光谱信息,分别使用3种不同的高光谱数据预处理方法对光谱数据进行预处理,分析不同预处理方法对模型精度的影响,并基于不同的预处理方法分别建立高斯过程回归模型(Gaussian Process Regression, GPR)和BP神经网络模型,分析不同预处理方法对模型精度的影响;并对各模型结合PCA数据降维方法进行模型的改进,通过比较模型的精度选择最优模型进行水体COD含量的检测。结果显示,相比于原始光谱数据建立的GPR模型和BP神经网络模型,数据预处理后的模型精度明显提升;且结合PCA对预处理后的数据进一步降维处理后,模型精度得到了进一步的提升。其中,基于标准正态变量变换特征结合PCA改进BP神经网络模型基于PCA改进的BP神经网络模型R^2高达0.9940,均方根误差RMSE为0.022540。证明了基于PCA改进的BP神经网络数据降维方法对预处理后的光谱数据进行降维处理,有利于去除光谱中的冗余信息,提取特征信息,可以实现高光谱检测方法可以实现COD含量估算模型的优化,从而为传统COD测量方法存在的问题提出了一种新的解决思路。