Henan University of Technology

About: Henan University of Technology is a education organization based out in Zhengzhou, China. It is known for research contribution in the topics: Catalysis & Chemistry. The organization has 7648 authors who have published 6503 publications receiving 73067 citations. The organization is also known as: Hénán Gōngyè Dàxué.

Super-stretchable and extreme temperature-tolerant supramolecular-polymer double-network eutectogels with ultrafast in situ adhesion and flexible electrochromic behaviour

Abstract: The current tough and stretchable gels with various integrated functions are mainly based on polymer hydrogels. By introducing a non-covalent supramolecular self-assembled network into a covalently cross-linked polymer network in the presence of eco-friendly and cost-effective deep eutectic solvents (DESs), we developed a new small molecule-based supramolecular-polymer double-network (SP-DN) eutectogel platform. This exciting material exhibits high stretchability and toughness (>18 000% areal strain), spontaneous self-healing ability, ultrafast (∼5 s) in situ underwater and low-temperature (−80 °C) adhesion, and unusual boiling water-resistance, as well as strong base-, strong acid- (even aqua regia), ultra-low-temperature- (liquid nitrogen, −196 °C), and high-temperature- (200 °C) resistance. All these outstanding properties strongly recommend the SP-DN eutectogels as a quasi-solid electrolyte for soft electrochromic devices, which exhibited exceptional flexibility and consistent electrochromic behaviours in harsh mechanical or temperature environments. The experimental and simulation results uncovered the assembly mechanism of the SP-DN eutectogels. Unlike polymer hydrogels, the obtained SP-DN eutectogels showed high molecular design freedom and structural versatility. The findings of this work offer a promising strategy for developing the next generation of mechanically robust and functionally integrated soft materials with high environmental adaptability.

A PSO-Based Classification Rule Mining Algorithm

Abstract: Classification rule mining is one of the important problems in the emerging field of data mining which is aimed at finding a small set of rules from the training data set with predetermined targets. To efficiently mine the classification rule from databases, a novel classification rule mining algorithm based on particle swarm optimization (PSO) was proposed. The experimental results show that the proposed algorithm achieved higher predictive accuracy and much smaller rule list than other classification algorithm.