控制结晶-微波碳热还原法制备高密度LiFePO4/C

应用控制结晶法从溶液相制备球形FePO4.xH2O,再高温烧结得到FePO4前驱体,最后用微波碳热还原法合成高密度L iFePO4/C.由XRD和SEM表征该材料的结构、形貌,并测试其电化学性能.     

Investigation of Metastable Low Dimensional Halometallates

The solvothermal synthesis, structure determination and optical characterization of five new metastable halometallate compounds, [1,10-phenH][Pb_3.5I₈] (1), [1,10-phenH₂][Pb₅I₁₂]·(H₂O) (2), [1,10-phen][Pb₂I₄] (3), [1,10-phen]₂[Pb₅Br₁₀] (4) and [1,10-phenH][SbI₄]·(H₂O) (5), are reported. The materials exhibit rich structural diversity and exhibit structural dimensionalities that include 1D chains, 2D sheets and 3D frameworks. The optical spectra of these materials are consistent with bandgaps ranging from 2.70 to 3.44 eV. We show that the optical behavior depends on the structural dimensionality of the reported materials, which are potential candidates for semiconductor applications.     

基于集群架构的OTN设备管理系统的实现

针对传统光传送网络(OTN)设备业务单盘数量过少,且槽位扩容会造成业务中断,成本过高的问题,文章提出了基于集群架构的光传送网(COTN)通信系统.COTN设备管理系统的设计是实现现网设备从OTN升级到COTN的可靠技术保障,是保障COTN中业务承载单盘的兼容性与扩展性的有效技术手段,文章采用单网元多子框的形式对COTN...     

玻色化方法在超对称可积系统的应用

利用玻色化方法可以避免超对称可积系统中反对易费米场带来的计算困难. 本文以N=1超对称mKdVB系统为例, 利用玻色化方法, 将其转化为只有玻色场的耦合系统. 应用标准的WTC方法, 证明了该耦合系统具有Painlevé性质. 运用Painlevé截断方法, 可以得到玻色化后超对称mKdVB系统的非局域对称. 为了求解与非局域对称相关的Lie第一性原理, 引入新的场将玻色化后系统拓展为更大的系统. 通过引入新的场, 该非局域对称局域化为Lie点对称. 因此, 可以利用Lie点对称约化方法研究拓展后的系统, 得到超对称mKdVB系统的孤子与其他孤波相互作用解.     

基于L1正则化的随机梁式结构静力损伤识别方法

提出了一种结合摄动法和L1正则化方法的随机梁式结构静力损伤识别方法。考虑初始模型误差和测量误差的影响,建立了关于随机损伤指数的控制方程,并将摄动法和L1正则化方法相结合,对随机损伤指数的控制方程进行求解,进而从概率的角度对结构的损伤进行识别。损伤试验结果表明,和传统的最小二乘求解法相比,本文方法能够更为准确地识别多处局部损伤的位置及大小,对实际结构损伤检测具有较好的参考价值。     

One-step ultrasonic synthesis of Co/Ni-catecholates for improved performance in oxygen reduction reaction

The inherent periodically arranged M−N_X, M−S_X and M−O_X units (M are usually Fe, Co, Ni, etc.) in metal–organic frameworks (MOFs) can be promising active centers in electrocatalysis. In previous studies, MOFs were usually constructed by energy-consuming hydro- or solvo-thermal reactions. Ultrasonic synthesis is a rapid and environment-friendly technique when envisaging MOFs’ industrial applications. In addition, different synthetic pathways for MOFs may lead to difference in their microstructure, resulting in different electrocatalytic performance. Nevertheless, only a handful of MOFs were successfully prepared by ultrasonic synthesis and few were applied in electrochemical catalysis. Herein, we constructed Ni/Co-catecholates (Ni/Co-CATs) synthesized by one-step ultrasonic method (250 W, 40 KHz, 25 W/L, Ultrasonic clearing machine) and compared their performance in oxygen reduction reaction (ORR) with that of Ni/Co-CATs synthesized by hydrothermal method. Ni-CAT and Co-CAT prepared by ultrasonic showed the half-wave potential of −0.196 V and −0.116 V (vs. Ag/AgCl), respectively. The potentials were more positive than those prepared by hydro-thermal method. And they showed excellent electrochemical stability in neutral solution. The latter was only 32 mV lower than that of commercial Pt/C. The improved performance in ORR was attributed to higher specific surface area and mesopore volume as well as more structural defects generated in the ultrasonic synthesis process, which could facilitate their exposure of electrocatalytic active sites and their mass transport. This work gives some perspective into cost-effective synthetic strategies of efficient MOFs-based electrocatalysts.     

Code2vect: An efficient heterogenous data classifier and nonlinear regression technique

The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.     

Deep Hierarchical Ensemble Model for Suicide Detection on Imbalanced Social Media Data

As a serious worldwide problem, suicide often causes huge and irreversible losses to families and society. Therefore, it is necessary to detect and help individuals with suicidal ideation in time. In recent years, the prosperous development of social media has provided new perspectives on suicide detection, but related research still faces some difficulties, such as data imbalance and expression implicitness. In this paper, we propose a Deep Hierarchical Ensemble model for Suicide Detection (DHE-SD) based on a hierarchical ensemble strategy, and construct a dataset based on Sina Weibo, which contains more than 550 thousand posts from 4521 users. To verify the effectiveness of the model, we also conduct experiments on a public Weibo dataset containing 7329 users’ posts. The proposed model achieves the best performance on both the constructed dataset and the public dataset. In addition, in order to make the model applicable to a wider population, we use the proposed sentence-level mask mechanism to delete user posts with strong suicidal ideation. Experiments show that the proposed model can still effectively identify social media users with suicidal ideation even when the performance of the baseline models decrease significantly.     

PCBs的超(亚)临界水催化氧化及还原裂解

简要分析了多氯联苯(PCBs)的来源及其对环境构成的危害,介绍了PCBs在超（亚）临界水中的反应及其处理效果。分别从超临界水氧化、超临界水裂解及亚临界水还原三个方面阐明了超临界反应过程中PCBs降解的反应路径和降解效率,解释了共溶剂（甲醇、苯）、碱催化剂（Na₂CO₃、NaOH）、氧化剂（NaNO₃、NaNO₂）等对PCBs脱氯和分解的增效作用机理。发现在超临界水氧化与超临界水裂解条件下CH3OH对PCBs降解反应的促进机制有所不同,碱催化剂通过中和反应过程中产生的HCl生成NaCl沉淀导致体系中Cl的含量降低,从而促进脱氯反应的进行。对反应器防腐、处理的经济性方面略作讨论,在总结上述研究工作的基础上提出了PCBs的超临界反应处理技术未来发展的若干研究方向。