Self‐assembly of Carbon Particles as a Heat Sink Coating to Promote Radiative Cooling

Novel composite carbon particles are developed that can self‐assemble as a coating on a substrate without a binder. These carbon particles were used as a coating to enhance thermal dissipation and their thermal conductivity, surface emissivity and cooling performance were measured. Carbon particles with both thiol and epoxy functional groups self‐assembled to form a coating on the surface of a heat sink without a binder, which greatly improved the thermal conductivity of the coating. Coating a heat sink with the carbon particles yielded a higher thermal conductivity and emissivity than could be obtained with the addition of binder in the conventional approach, and significantly enhanced the cooling performance. In addition, the cooling performance of the carbon nanotube outperformed all other particles when coated on a substrate, because it had the highest thermal conductivity and good radiation emissivity. We developed an equation to describe the various parameters affecting the cooling performance of the thermally dissipative coating. This equation was confirmed by the experimental data.     

Time-dependent optimization of a multi-item uncertain supply chain network: A hybrid approximation algorithm

We consider the uncertain least cost shipping problem. The input is a multi-item supply chain network with time-evolving uncertain costs and capacities. Exploiting the operational law of uncertainty theory, a mathematical model of the problem is established and the indeterminacy factors are tackled. We use the scaling idea together with transformation approach and uncertainty programming to develop a hybrid algorithm to optimize and obtain the uncertainty distribution of the total shipping cost. We analyze the practical performance of the algorithm and present an illustrative example.     

A short review on latest developments in catalytic depolymerization of Poly (ethylene terephathalate) wastes

Chemical recycling of plastic wastes is top among the effective management of the solid wastes. Particularly the post-consumer polyethylene terephthalate (PET) plastic wastes mainly generated from the disposal of beverage bottles and placed third most produced polymeric waste. However, PET wastes could be chemically recycled using several types of homo-/heterogeneous acid or base catalysts, and an effective recycling process has yet to be achieved. Therefore, the present short review is intended to display recent reports on the depolymerization of PET polymer wastes. The review aimed to cover glycolysis and aminolytic depolymerization using various catalytic systems. There is a wide spectrum of catalytic systems such as metal oxides, ionic liquids, organic bases, nanoparticles, porous materials and microwave-assisted rapid depolymerization methods have been developed toward the yield enhancement of the depolymerized products. Ideologically, the present review would benefit the researchers in familiarizing themselves with the latest developments in this field.     

针对理论-实验教学相融合的微助教辅助实验教学实践——以滴定分析实验教学为例

研究生助教培养是高校化学本科生实验教学的重要组成部分,对提高实验课程的教学水平具有重要的推动作用。为解决助教培训时间仓促、定位不清、内容不连续、工具性倾向明显,以及在助教聘用、考核、激励、教学质量评估等方面规范性和系统性不足等问题,仪器分析实验室以《GB/T 19028–2018质量管理人员参与和能力指南》为理论依据,探索提高研究生助教深度参与实验教学的方法。连续三年追踪助教培养改进效果反馈数据表明,实验室采取的一系列改进措施有效提升了研究生助教的教学能力,促进了教学质量的提高,实现助教管理的改革创新与“过程增值”。     

Machine learning as an online diagnostic tool for proton exchange membrane fuel cells

Proton exchange membrane fuel cells are considered a promising power supply system with high efficiency and zero emissions. They typically work within a relatively narrow range of temperature and humidity to achieve optimal performance; however, this makes the system difficult to control, leading to faults and accelerated degradation. Two main approaches can be used for diagnosis, limited data input which provides an unintrusive, rapid but limited analysis, or advanced characterisation that provides a more accurate diagnosis but often requires invasive or slow measurements. To provide an accurate diagnosis with rapid data acquisition, machine learning methods have shown great potential. However, there is a broad approach to the diagnostic algorithms and signals used in the field. This article provides a critical view of the current approaches and suggests recommendations for future methodologies of machine learning in fuel cell diagnostic applications.     

Coating Cellulosic Material with Ag Nanowires to Fabricate Wearable IR-Reflective Device for Personal Thermal Management: The Role of Coating Method and Loading Level

Textiles coated with silver nanowires (AgNWs) are effective at suppressing radiative heat loss without sacrificing breathability. Many reports present the applicability of AgNWs as IR-reflective wearable textiles, where such studies partially evaluate the parameters for practical usage for large-scale production. In this study, the effect of the two industrial coating methods and the loading value of AgNWs on the performance of AgNWs-coated fabric (AgNWs-CF) is reported. The AgNWs were synthesized by the polyol process and applied onto the surface of cotton fabric using either dip- or spray-coating methods with variable loading levels of AgNWs. X-ray diffraction, scanning electron microscopy (SEM), infrared (IR) reflectance, water vapor permeability (WVP), and electrical resistance properties were characterized. The results report the successful synthesis of AgNWs with a 30 μm length. The results also show that the spray coating method has a better performance for reflecting the IR radiation to the body, which increases with a greater loading level of the AgNWs. The antibacterial results show a good inhibition zone for cotton fabric coated by both methods, where the spray-coated fabric has a better performance overall. The results also show the coated fabric with AgNWs maintains the level of fabric breathability similar to control samples. AgNWs-CFs have potential utility for cold weather protective clothing in which heat dissipation is attenuated, along with applications such as wound dressing materials that provide antibacterial protection.     

高校实验室安全教育在线资源调查研究*

对国内高校实验室安全教育在线资源现状进行调研。调查结果表明:在线资源主要有慕课、虚拟仿真实验及安全教育考试系统。因此,在安全教育过程中,可充分利用现有线上资源,弥补线下教学因时间有限、容量有限导致的不足,从而提高安全教育实效。线上、线下安全教育如何有机结合从而最大限度地发挥其在高校安全教育中的作用,仍需不断探索。     

”Illusion of control” in Time-Horizon Minority and Parrondo Games

Human beings like to believe they are in control of their destiny. This ubiquitous trait seems to increase motivation and persistence, and is probably evolutionarily adaptive [J.D. Taylor, S.E. Brown, Psych. Bull. 103, 193 (1988); A. Bandura, Self-efficacy: the exercise of control (WH Freeman, New York, 1997)]. But how good really is our ability to control? How successful is our track record in these areas? There is little understanding of when and under what circumstances we may over-estimate [E. Langer, J. Pers. Soc. Psych. 7, 185 (1975)] or even lose our ability to control and optimize outcomes, especially when they are the result of aggregations of individual optimization processes. Here, we demonstrate analytically using the theory of Markov Chains and by numerical simulations in two classes of games, the Time-Horizon Minority Game [M.L. Hart, P. Jefferies, N.F. Johnson, Phys. A 311, 275 (2002)] and the Parrondo Game [J.M.R. Parrondo, G.P. Harmer, D. Abbott, Phys. Rev. Lett. 85, 5226 (2000); J.M.R. Parrondo, How to cheat a bad mathematician (ISI, Italy, 1996)], that agents who optimize their strategy based on past information may actually perform worse than non-optimizing agents. In other words, low-entropy (more informative) strategies under-perform high-entropy (or random) strategies. This provides a precise definition of the “illusion of control” in certain set-ups a priori defined to emphasize the importance of optimization. An erratum to this article is available at .     

美军F-35战斗机PHM体系结构分析

为借鉴国外状态预测与健康管理(PHM)技术的发展经验,促进大型平台实现从状态监控向健康管理过渡,本文回顾了美军PHM技术的发展概况,分析了F-35战斗机PHM的体系结构组成以及各模块的主要功能,总结了F-35战斗机PHM的工作流程,介绍了F-35战斗机PHM系统的发展现状及存在的主要问题,提出了对发展PHM技术的认识,为从事PHM技术工作者提供了参考。