富晶格位错的多孔铋纳米花高效电还原二氧化碳制甲酸盐※

二氧化碳转化已成为现今世界研究的热点. 本工作采用原位电化学转化的策略, 将简单溶剂热法合成的层状甲酸氧铋纳米花(BiOCOOH NFs)还原为带有大量晶格位错的多孔铋纳米花(p-Bi NFs). 研究结果表明, p-Bi NFs电催化二氧化碳转化为甲酸盐具有较小的过电位(436 mV). 在–1.8 V(相对饱和甘汞电极, vs. SCE)时, 甲酸盐的分电流密度(j_formate)高达24.4 mA•cm^-2, 法拉第效率(FE_formate)为96.7%, 且在超过500 mV的宽电位窗口内FE_formate超过90%, 并具有很好的稳定性. 该催化剂的高催化性能可归因于前驱体晶格坍塌和重构而形成特殊的多孔粗糙的微纳多级结构, 其表面富含晶格位错和缺陷等高本征活性位, 且具有较强的电子传递能力. 本研究为设计合成高性能的电催化二氧化碳还原产甲酸催化剂提供了新的思路.     

一种轿车车轮应力状态测量与分析方法

基于台架应变测试试验方法,研究轿车车轮在疲劳试验中的应力状态。结果表明:车轮的径向疲劳试验时,轮胎会对车轮的载荷产生较大的影响,轮胎与转鼓的挤压变形以及正反转动都会对车轮的应力状态产生影响;车轮径向疲劳试验时,最大应变出现在轮辋与轮胎接触位置沿车轮圆周方向,而在靠近轮心位置的应变较小;车轮弯曲疲劳试验时,最大应变出现在轮辐靠近轮心的位置,最大应变出现在轮辐的长度方向;不同的载荷对车轮应变的变化规律并没有影响,但是会对最大和最小峰值产生影响。     

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.     

Proteome profile of salt gland‐rich epidermis extracted from a salt‐tolerant tree species

Preparation of proteins from salt‐gland‐rich tissues of mangrove plant is necessary for a systematic study of proteins involved in the plant's unique desalination mechanism. Extraction of high‐quality proteins from the leaves of mangrove tree species, however, is difficult due to the presence of high levels of endogenous phenolic compounds. In our study, preparation of proteins from only a part of the leaf tissues (i.e. salt gland‐rich epidermal layers) was required, rendering extraction even more challenging. By comparing several extraction methods, we developed a reliable procedure for obtaining proteins from salt gland‐rich tissues of the mangrove species Avicennia officinalis. Protein extraction was markedly improved using a phenol‐based extraction method. Greater resolution 1D protein gel profiles could be obtained. More promising proteome profiles could be obtained through 1D‐LC‐MS/MS. The number of proteins detected was twice as much as compared to TUTS extraction method. Focusing on proteins that were solely present in each extraction method, phenol‐based extracts contained nearly ten times more proteins than those in the extracts without using phenol. The approach could thus be applied for downstream high‐throughput proteomic analyses involving LC‐MS/MS or equivalent. The proteomics data presented herein are available via ProteomeXchange with identifier PXD001691.     

两种高分辨率数值方法计算波前有非均匀流的变截面管内激波传播规律的比较

本文采用两种对间断解具有高分辨率的数值方法基于推广Riemann问题解的二阶Godunov型有限差分法和分裂算子的随机选取法,计算了微波在波前有非均匀定常流的一维变截面管道中的传播和波后流场特征,得到一致结果,用数值模拟方法揭示了这类运动的一些特殊规律。对比两种方法的计算过程和结果,可以看出,二阶Godunov型方法明显优于随机选取法。     

基于简单MOPA结构实现3.08 kW全光纤窄线宽线偏振激光输出

基于简单的主振荡功率放大结构,演示了一种高功率窄线宽线性偏振全光纤激光器,其最大输出功率为3.08 kW,3 dB线宽为0.2 nm。在整个功率缩放过程中,偏振消光比约为94%,光束质量M 2约为1.4。这是国内外首次实现3 kW全保偏光纤激光输出,与基于相位调制的窄线宽激光器相比,该激光器可实现近似的线宽,同时具有受激布里渊散射阈值高、系统结构简单、成本低等特点。     

碳水化合物衍生的手性配体——25含碳水化合物单元的膦配体在钯催化的Heck反应中的应用

评价了一种碳水化合物衍生的具有较大立体位阻及较三苯基膦更富电子的膦配体(甲基3-脱氧-3-二苯膦基-4,6-氧-苯次甲基-α-D-吡喃阿卓糖苷,3-MBPA)在Pd催化的Heck反应中的性能.发现在N,N-二甲基乙酰胺溶刺中K2CO3是该催化体系较适合的碱;在该配体的支持下催化剂中钯的用量可低至0.5 mo1%;可催化苯乙烯与带给电子基团的溴代芳烃及带吸电子基团的氯代芳烃发生反应,高产率地生成相应的偶联产物;反应区域选择性表明,Pd(OAc)2/3-MBPA体系在催化苯乙烯与卤代芳烃的Heck反心中并存阳离子催化途径,说明3-MBPA中的氧原了可能也参与配位;同时发现,加入助配体四丁基溴化胺(TBAB)后,可能是Br-参与配位有利于增加中性催化途径的机会而提高了反应区域选择性.     

不同产地杜仲叶中金属元素的含量及其变化趋势分析

采用火焰原子吸收光谱法测定了陕西杨凌、陕西安康和河南灵宝产杜仲叶中Fe、Cu、Mg、Ca、Mn、Zn 6种金属元素的含量,并对其含量的变化趋势进行了分析比较.结果表明,杜仲叶中含有丰富的人体必需金属元素,且不同产地来源的样品中金属元素的含量有明显差异,其中尤以Fe、Zn、Mn和Mg含量差异最大,Cu和Ca的差异不明显....     

醚基化二茂铁基膦配体的合成及其对钯催化的Suzuki偶联反应的促进作用

通过乙酸1-(2-二苯膦基二茂铁基)-乙基酯和二甘醇反应,制得新的醚基化的二茂铁基膦配体2-二苯膦基二茂铁基-乙基-5-羟基-3-氧杂戊醚(产率77%),其结构经1H NMR、13C NMR、31P NMR及MS鉴定。 初步研究发现,该醚基化的二茂铁基膦可作为支持配体应用于钯催化的Suzuki反应中,可催化溴代芳烃及带吸电子基的氯代芳烃与苯基硼酸偶联反应制得相应的联芳烃。 催化反应数据表明,配体中的醚氧与Pd中心的配位作用对提高该Pd催化剂的催化性能有一定贡献。