Facile generation of highly durable thiol-functionalized polyhedral oligomeric silsesquioxane based superhydrophobic melamine foam

In this study, a durable superhydrophobic/superoleophilic melamine foam was fabricated by a facile and rapid one-step thiol-ene click chemistry and Michael addition reaction, which demonstrated excellent robustness in oil/water separation. First, 1H, 1H, 2H-perfluoro-1-hexene reacted with thiol-functionalized polyhedral oligomeric silsesquioxane via the thiol-ene click chemistry to obtain a fluorinated thiol-functionalized polyhedral oligomeric silsesquioxane solution. Subsequently, the melamine foam was immersed to the solution system to form nanoaggregates on the melamine foam surface by the Michael addition reaction in the presence of ultraviolet light. The micro/nano rough structure and low surface energy of the nanoaggregates layer endowed the pristine melamine foam with superhydrophobicity; the water contact angle was greater than 150°. More importantly, the as-prepared melamine foam could withstand harsh conditions, such as a corrosive solution environment, strong ultraviolet light, mechanical compression, high and low temperature exposure, and ultrasonic washing. Driven by gravity, the as-prepared melamine foam could efficiently separate the oil/water mixtures and maintain 98% separation efficiency at high and low temperatures. In addition, it maintained the desirable absorption capability in different oil/organic solvents even after 15 absorption cycles. Accordingly, this facile, low-cost, and robust one-step method provides important support for the superhydrophobic oil/water separation field.     

基于非线性规划理论的凸多面体最小平移距离算法

凸多面体的最小平移距离问题一直以来都成为计算机图形学的一个研究热点.目前已有的距离算法在稳定性、可实现性、精确度和实现效率这几方面或多或少都存在一定的缺陷.为此,从最小平移距离定义出发,引入广义分离平面概念,提出一种用非线性规划求解距离问题的新算法.算法先定义一对最优广义分离平面以确定凸多面体最小平移距离;然后,将最优广义分离平面对的搜索问题等效变换为非线性规划问题;最后,用非线性优化工具软件对非线性规划问题进行求解,从而确定最小平移距离.实验结果表明：该算法能提供一个准确的距离值和实现向量,其性能优于其他同类算法;迭代次数与多面体的顶点数呈线性关系.此外,该算法只需提供顶点信息即可实现,求解过程中避免了死循环,故实现简单、可靠.因此,此算法是一种快速而有效的距离算法.     

Fast model predictive control for linear periodic systems with state and control constraints

The design of stabilizing model predictive control laws for discrete‐time linear periodic systems with state and control constraints is considered. Two algorithms are presented. The first one is based on interpolation between several unconstrained periodic controllers. Among them, one controller is chosen for the performance while the rest are used to extend the domain of attraction. The second algorithm aims to improve the performance by combining model predictive control and interpolating control. The proposed approaches not only guarantee recursive feasibility and asymptotic stability but also are optimal for states near the origin. Copyright © 2017 John Wiley & Sons, Ltd.