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Your search keyword '"Yueting Zhuang"' showing total 493 results
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493 results on '"Yueting Zhuang"'

1. Preparation and performance control of ultra-low near-infrared reflectivity coatings with super-hydrophobic and outstanding mechanical properties

Author

Weigang Zhang, Yueting Zhuang, Jialun Zhang, and Qianfeng Zhang

Subjects
Super-hydrophobic, Ultra-low near-infrared reflectivity, Composite coating, Mechanical property optimization, Medicine, Science
Abstract

Abstract The development of ultra-low near-infrared reflectivity coatings with outstanding engineering properties remains a challenge in laser stealth materials research. Herein, we reported a laser stealth coating with outstanding mechanical properties, super-hydrophobicity, and an ultra-low near-infrared reflectivity for 1.06 μm wavelength. The effects of the mass ratio of graphene to nano-SiO2, the proportion of total filler, the addition of KH560, the mass ratio of Polydimethylsiloxane (PDMS) to acrylic-modified polyurethane (APU), and the addition of dioctyl phthalate (DOP) on the coating properties were thoroughly discussed. The coating can achieve a low reflectivity of 9.3% at 1.06 μm and a high water contact angle of 152° at a mass ratio of 7:3 for PDMS to APU and 6:4 for graphene to nano-SiO2 with a total filler amount of 40 wt%. KH560 can play a bridging role between the blended resin matrix and nano-SiO2, which can significantly improve the impact strength of the coating. The DOP, which contains a polar ester group and a non-polar carbon chain structure, can be inserted between the molecular chains of the resin to weaken the intermolecular force of the resin, so that the flexibility of the coating can be significantly improved. Adding KH560 at 4 wt% and DOP at 1 wt%, resulted in a coating with ultra-low near-infrared reflectivity of 1.06 μm (9.3%), super-hydrophobic properties, outstanding adhesion strength (grade 2), flexibility (2 mm), and impact strength (50 kg cm). The above super-hydrophobic ultra-low near-infrared reflectivity coating has significant potential for use in the field of laser stealth equipment, and it can serve as a useful reference for optimizing the mechanical properties of super-hydrophobic functional coatings.

Published
2024
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2. Unfolding and modeling the recovery process after COVID lockdowns

Author

Xuan Yang, Yang Yang, Chenhao Tan, Yinghe Lin, Zhengzhe Fu, Fei Wu, and Yueting Zhuang

Subjects
Medicine, Science
Abstract

Abstract Lockdown is a common policy used to deter the spread of COVID-19. However, the question of how our society comes back to life after a lockdown remains an open one. Understanding how cities bounce back from lockdown is critical for promoting the global economy and preparing for future pandemics. Here, we propose a novel computational method based on electricity data to study the recovery process, and conduct a case study on the city of Hangzhou. With the designed Recovery Index, we find a variety of recovery patterns in main sectors. One of the main reasons for this difference is policy; therefore, we aim to answer the question of how policies can best facilitate the recovery of society. We first analyze how policy affects sectors and employ a change-point detection algorithm to provide a non-subjective approach to policy assessment. Furthermore, we design a model that can predict future recovery, allowing policies to be adjusted accordingly in advance. Specifically, we develop a deep neural network, TPG, to model recovery trends, which utilizes the graph structure learning to perceive influences between sectors. Simulation experiments using our model offer insights for policy-making: the government should prioritize supporting sectors that have greater influence on others and are influential on the whole economy.

Published
2023
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33. The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.

Author

Matej Kristan, Jirí Matas, Martin Danelljan, Michael Felsberg, Hyung Jin Chang, Luka Cehovin Zajc, Alan Lukezic, Ondrej Drbohlav, Zhongqun Zhang, Khanh-Tung Tran, Xuan-Son Vu, Johanna Björklund, Christoph Mayer 0007, Yushan Zhang, Lei Ke, Jie Zhao 0014, Gustavo Fernández, Noor Al-Shakarji, Dong An, Michael Arens, Stefan Becker, Goutam Bhat, Sebastian Bullinger, Antoni B. Chan, Shijie Chang, Hanyuan Chen, Xin Chen 0032, Yan Chen, Zhenyu Chen 0001, Yangming Cheng, Yutao Cui, Chunyuan Deng, Jiahua Dong 0001, Matteo Dunnhofer, Wei Feng 0005, Jianlong Fu, Jie Gao, Ruize Han, Zeqi Hao, Jun-Yan He, Keji He, Zhenyu He 0001, Xiantao Hu, Kaer Huang, Yuqing Huang, Yi Jiang 0004, Ben Kang, Jin-Peng Lan, Hyungjun Lee, Chenyang Li, Jiahao Li, Ning Li, Wangkai Li, Xiaodi Li, Xin Li 0034, Pengyu Liu, Yue Liu, Huchuan Lu, Bin Luo 0008, Ping Luo 0002, Yinchao Ma, Deshui Miao, Christian Micheloni, Kannappan Palaniappan, Hancheol Park, Matthieu Paul, Houwen Peng, Zekun Qian, Gani Rahmon, Norbert Scherer-Negenborn, Pengcheng Shao, Wooksu Shin, Elham Soltani Kazemi, Tianhui Song, Rainer Stiefelhagen, Rui Sun, Chuanming Tang, Zhangyong Tang, Imad Eddine Toubal, Jack Valmadre, Joost van de Weijer 0001, Luc Van Gool, Jash Vira, Stéphane Vujasinovic, Cheng Wan 0006, Jia Wan 0001, Dong Wang 0004, Fei Wang 0032, Feifan Wang, He Wang, Limin Wang 0002, Song Wang 0002, Yaowei Wang 0001, Zhepeng Wang 0002, Gangshan Wu, Jiannan Wu, Qiangqiang Wu, Xiaojun Wu 0001, Anqi Xiao, Jinxia Xie, Chenlong Xu, Min Xu 0001, Tianyang Xu, Yuanyou Xu, Bin Yan 0004, Dawei Yang, Ming-Hsuan Yang 0001, Tianyu Yang 0003, Yi Yang 0001, Zongxin Yang, Xuanwu Yin, Fisher Yu 0001, Hongyuan Yu, Qianjin Yu, Weichen Yu, Yongsheng Yuan, Zehuan Yuan, Jianlin Zhang 0001, Lu Zhang 0053, Tianzhu Zhang, Guodongfang Zhao, Shaochuan Zhao, Yaozong Zheng, Bineng Zhong, Jiawen Zhu, Xuefeng Zhu, Yueting Zhuang, ChengAo Zong, and Kunlong Zuo

Published
2023
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