少量有机碳对单级自养脱氮工艺性能的影响

采用序批式生物膜反应器(SBBR),经过4个阶段的培养,快速富集好氧氨氧化细菌(AOB)和厌氧氨氧化细菌(AnAOB),并考察不同低碳氮比对工艺脱氮性能的影响。结果表明,NH4^+-N去除率可达到99%以上,TN去除率可达到90%以上。对应C/N=0、1和2时,反应器出水NH4^+-N和TN去除率分别为99.59%、99.5%、98.47%和93.75%、97.22%、98.11%。说明少量COD的存在,可实现同步硝化-厌氧氨氧化-反硝化,且在一定程度上提高脱氮效率。     

高性能有机氟材料制备科学及应用进展

有机氟材料具有优异的热氧稳定性、耐化学腐蚀性、耐老化性、不黏性、电绝缘性以及极小的摩擦系数等特性，因此作为一种不可替代的材料广泛应用于高新技术产业。近年来高新技术产业发展对高性能有机氟材料的需求引发了学术界和工业界对氟材料的研究兴趣。依据本文作者的研究经历及有机氟材料的发展方向，本文介绍了氟树脂（新型含氟聚合物、电活性含氟聚合物、新型全氟磺酸聚合物、聚四氟乙烯3D打印）及氟橡胶（过氧化物硫化氟橡胶、耐低温氟醚橡胶、耐高温全氟醚橡胶、全氟聚醚基类玻璃橡胶）的制备科学及应用进展，特别阐述为了满足航空航天、能源、信息等高新技术产业需求发展的新一代高性能有机氟材料。本文也介绍了近期出现的聚四氟乙烯新成型技术及类玻璃氟橡胶。文章指出发展绿色环保和高效的高性能有机氟材料制备及成型加工方法是今后的发展方向。     

大规模多状态计算系统的容错性能分析

针对异构计算节点组成的大规模多状态计算系统的容错性能分析问题，提出了一种计算系统容错性能的评估方法。该方法采用自定义的两级容错性能形式化描述框架进行系统描述，通过构造多值决策图（Multi-value Decision Diagram，MDD）模型对系统进行容错性能建模，并基于构造的模型高效地计算出部件故障的条件下计算系统在特定性能水平上运行的概率，减少了计算的冗余性。实验结果表明，该方法在模型的大小和构建时间上均优于传统方法。该方法的提出将对系统操作员或程序设计者具有重要意义，使其确保系统适合预期应用。     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Platinum nanoparticles decorated on graphitic carbon nitride-ZIF-67 composite support: An electrocatalyst for the oxidation of butanol in fuel cell applications

In the present study, we report an eco-friendly and simple route to design and synthesize novel nanocomposite catalyst based on platinum nanoparticles anchored on binary support of graphitic carbon nitride (g-C₃N₄) and cobalt-metal-organic framework (ZIF-67). For this purpose, ZIF-67 was prepared by precipitation method and g-C₃N₄ was prepared through thermal polymerization method. Later, ZIF-67 and g-C₃N₄ were hybridized through sonication to get homogeneous g–C₃N₄–ZIF-67 nanocomposite support material. Platinum nanoparticles (PtNPs) were uniformly deposited on g–C₃N₄–ZIF-67 by an electrochemical method. The as-developed nanocatalyst was characterized by morphological, structural and electrochemical techniques. The electrocatalytic activity of PtNPs@g–C₃N₄–ZIF-67 nanocatalyst towards butanol oxidation was evaluated via CV, CA, LSV and EIS in an alkaline medium. Results revealed that the proposed catalyst showed greatly enhanced electrooxidation of butanol in terms of high magnificent current density, lower oxidation potential, excellent long-term stability, large surface area, low charge transfer resistance and less toxic ability. Enhanced catalytic performance of the proposed catalyst could be ascribed to the synergistic effect of g–C₃N₄–ZIF-67 nanocomposite and PtNPs. The PtNPs@g–C₃N₄–ZIF-67 catalyst holds promising potential applications to be used as an anodic electrocatalyst for the development of high-performance alkaline fuel cells.     

A review on ultrasonic spot welding of copper alloys

As a solid state joining process, ultrasonic spot welding has been proven to be a promising technique for joining copper alloys. However, challenges still remain in employing ultrasonic spot welding to join copper alloys. This article comprehensively reviews the current state of ultrasonic spot welding of copper alloys with a number of critical issues including materials flow, plastic deformation, temperature distribution, vibration, relative motion, vertical displacement, interface friction coefficient, online monitoring technique, coupled with the macrostructure and microstructure, the mechanical properties and electrical conductivity. In addition, the future trends in this field are provided.     

不同硬度PTMG型CPUE与硫化橡胶的性能对比研究

通过改变硬段含量、扩链系数等制备了几种不同硬度的四氢呋喃均聚醚(PTMG)浇注型聚氨酯弹性体(CPUE),讨论了PTMG型CPUE与硫化橡胶(VR)的物理机械性能、拉伸应力应变行为以及动态力学性能的区别。结果表明,随CPUE硬度的提高,材料的刚性增强,力学性能是低硬度VR的数倍。通过对CPUE硬度的调节,可以使之兼具聚氨酯和橡胶的优良性能。在玻璃态温度下CPUE的储能模量随硬度的减小而降低,但都高于VR,而且CPUE的硬度越大,二者相差越大,温度越低,相差也越大;在室温以上温度范围内,CPUE具有比VR更小的力学损耗。     

Temperature adaptability of the soluble lead flow battery using different solutions of fluoborate,perchlorate, methanesulfonate and trifluoromethanesulfonate

The evaluation of cell's weatherability is of practical interest. To further improve the soluble lead flow battery's weatherability, physiochemical properties of electrolytes containing fluoborate, perchlorate, methanesulfonate and trifluoromethanesulfonate are investigated from ?60 to 50 °C. Activities of CF₃SO₃H and HClO₄ are poor in trifluoromethanesulfonate and perchlorate solutions due to common anion effect. The solubility of lead salt can be improved by increasing temperature, but worsened by increasing acid's content. With the temperature increasing, the conductivity is enhanced, and the viscosity is lowered for four solutions. The same results have been found by increasing acid's content except for CF₃SO₃H. The high energy efficiency can be achieved for cells over ?40–0 °C using fluoborate and perchlorate solutions, 73.2% at ?40 °C and 78.1% at ?30 °C respectively. Over the temperature range of 20–50 °C, the cells with methanesulfonate and trifluoromethanesulfonate solutions have good performance, 77.4% and 73.7% at 50 °C respectively.     

外部气体辅助注塑制品翘曲变形数值模拟

基于聚合物黏弹性理论与外部气体辅助注塑（EGAIM）的特点，构建了EGAIM气体保压阶段及脱模后自然冷却阶段制品内应力?应变的力学模型。在此基础上，采用耦合有限元法（FEM）对EGAIM平板制件的翘曲变形进行模拟计算，模拟结果与实验结果基本一致，验证了所建计算模型有效可靠。