Solution-Synthesized Multifunctional Janus Nanotree Microswimmer

Synthetic active matters are perfect model systems for non-equilibrium thermodynamics and of great potential for novel biomedical and environmental applications. However, most applications are limited by the complicated and low-yield preparation, while a scalable synthesis for highly functional microswimmers is highly desired. In this paper, an all-solution synthesis method is developed where the gold-loaded titania-silica nanotree can be produced as a multi-functional self-propulsion microswimmer. By applying light, heat, and electric field, the Janus nanotree demonstrated multi-mode self-propulsion, including photochemical self-electrophoresis by UV and visible light radiation, thermophoresis by near-infrared light radiation, and induced-charge electrophoresis under AC electric field. Due to the scalable synthesis, the Janus nanotree is further demonstrated as a high-efficiency, low-cost, active adsorbent for water decontamination, where the toxic mercury ions can be reclaimed with enhanced efficiency.     

SND生物脱氮过程N_2O的产生与关键酶及其活性

废水生物脱氮是目前水处理中重要的去除含氮废水的方法。随着国内外学者的深入研究,一些新型的生物脱氮工艺被开发和应用到污水处理中,从而经济高效地去除废水中的含氮污染物,达到国家的排放标准。同步硝化反硝化(SND)是具有发展潜力的新型脱氮工艺,但在运行过程中不可避免地会产生N2O。N2O是最重要的三种温室气体之一,其温室效应约为CO2的300倍。因此,在注重SND的脱氮效率的同时,也应该关注其产生的气态物对大气环境的影响。文章阐述了SND脱氮过程中N2O产生的机理及相关酶,并分析了SND工艺过程中主要影响N2O释放量的工艺因素。     

工业园区混合能源优化配置方法应用与实践

为了充分挖掘多能源之间的互补潜力,使工业园区混合能源系统的配置方式由传统粗放式转变为精确优化配置并降低系统配置方案的保守性,基于粒子群联合CPLEX求解算法对工业园区的系统配置和运行调度方案进行分析优化,并以某生物园区为例进行了实例分析,得到了目标函数下的最优设计方案和运行策略。仿真分析结果表明,优化配置方法的应用能够协调冷热电多种能源的混合利用,提升系统的综合经济性。同时,为工业园区能源供应项目的规划、设计提供参考性支撑,丰富设计手段。     

Scanning tunneling spectroscopic study of monolayer 1T-TaS2 and 1T-TaSe2

Nano Research - The isostructural and isoelectronic transition-metal-dichalcogenides 1T-TaS2 and 1T-TaSe2 are layered materials with intricate electronic structures. Combining the molecular beam...     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Screening of frozen-thawed conditions for keeping nutritive compositions and physicochemical characteristics of goat milk

Frozen milk can help producers overcome the seasonality of goat milk production, low goat production and short lactation periods, and avoid discarding milk during some special periods. We investigated effects of combination between freezing (cryogenic refrigerator of ?16 to ?20°C or ultra-cryogenic refrigerator of ?76 to ?80°C) and thawing (homeothermy of 20 to 25°C or refrigeration of 2 to 4°C) on nutritive compositions and physicochemical characteristics of raw goat milk during storage period (80 d). Compared with fresh goat milk, the frozen-thawed milk decreased contents of fat, protein, and lactose, as well as surface tension and stability coefficient, whereas increased effective diameter and polydispersity index. The average values of color values (L*, a*, and b*) in 4 group samples changed from 83.01 to 82.25, ?1.40 to ?1.54, 3.51 to 3.81, respectively, and the ΔE of most samples did not exceed 2. In contrast to the other 3 frozen-thawed treatments, goat milk treated with ultra-cryogenic freezing-homeothermic thawing (UFHT) possessed higher fat (5.20 g/100 g), smaller effective particle diameter (0.32 µm), and the lowest polydispersity index value (0.26). The color and confocal laser scanning microscopy images of UFHT were similar to those of fresh goat milk, illustrating UFHT was the optimal approach to maintain the natural quality of goat milk. Our finding provides a theoretical basis for producers to freeze surplus milk.     

电喷雾质谱法示踪钨回收过程离子的转化路径

将环隙式离心萃取器(ACCs)与电喷雾飞行时间质谱(ESI-TOF-MS)相结合，在线监测了回收过程中的钨萃取行为(宏观)和钨形态的转化路径(微观)，发现宏观萃取反应和微观离子形态转化同时发生并相互补充。伯胺N1923萃取钨在144 s内即可达到萃取平衡，萃取率高达98%以上，同时，酸钨比n(H)/n(W)是一个关键变量，当酸钨比n(H)/n(W)=2.4时，全流程钨回收率超过93%。最后，得到了基于钨形态监测的萃取机理，同时，减少原料液中W1含量，增加W10含量，可有效提高钨回收效率。     

基于状态空间法的电动机故障诊断和识别

电动机的初期故障信号一般较弱,不易辨别,而状态空间法在小信号的处理中灵敏度很高。为达到对电动机故障的诊断和识别,试图把状态空间法应用到对电动机的故障诊断中,先通过推导,从数学理论层面分析了状态空间法对于电动机故障信号的可辨别性,再使用Matlab软件搭建状态空间的辨别模型,把实验台测试的三组数据导入到模型中进行测试。测试的结果有力地证明了此方法的可行性,并能克服快速傅里叶变换(FFT)中数据采集量较大、分辨率不高的缺点。