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28 results on '"Ji, Dongchao"'

6. Nanodiamond reinforced self-healing and transparent poly(urethane–urea) protective coating for scratch resistance.

Author

Wang, Zhuochao, Cao, Wenxin, Sun, Chunqiang, Ji, Dongchao, Zhao, Kunlong, Gao, Gang, Xu, Xingchun, Liu, Yingqi, Zhang, Tianyu, Zhu, Jiaqi, and Han, Jiecai

Subjects
PROTECTIVE coatings, PHASE separation, SILANE coupling agents, ATOMIC force microscopy, FLEXIBLE electronics, SCANNING electron microscopy, POLYURETHANE elastomers, UREA derivatives
Abstract

With increasing demand for scratch-resistant flexible electronics, the development of transparent coatings with good scratch resistance and self-healing properties has emerged as a key research topic. In this study, a high-strength self-healing poly(urethane – urea) (PUU)-based nanocomposite coating was prepared by introducing functionalized nanodiamond (ND) into a PUU matrix via solution blending. The PUU matrix had hard-segment repeating units and was constructed using isophorone diamine and isophorone isocyanate. The ND particles were modified using a silane coupling agent, 3-aminopropyltriethoxysilane, to obtain well-dispersed KH-ND nanoparticles. KH-ND promoted microphase separation in the PU matrix, inducing the formation of dense and homogeneous hard domains that dissipated stress, prevented further crack development, and improved the mechanical properties and scratch resistance of the coating. In addition, the coating exhibited excellent self-healing properties. Fourier-transform infrared spectroscopy, scanning electron microscopy, and atomic force microscopy were used to characterize the self-healing and hardening mechanisms of the coating. The environmentally friendly PUU/KH-ND coating is easy to prepare and has broad application prospects in transparent and anti-scratch coatings for flexible electronics, automobiles, and home appliances. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Self‐Healable and Transparent Elastomers Based on Dual Reversible Networks

Author

Lei Yang, Liangge Xu, Sun Mingqi, Peng Wang, Jiaqi Zhu, Gang Gao, Zhenhuai Yang, Wenxin Cao, Shuai Guo, and Ji Dongchao

Subjects
chemistry.chemical_compound, Silicone, Materials science, Polymers and Plastics, chemistry, General Chemical Engineering, Self-healing, Organic Chemistry, Materials Chemistry, Dual network, Nanotechnology, DUAL (cognitive architecture), Elastomer
Published
2020

27. An Improved KNN Algorithm of Intelligent Built-in Test

Author

Ji Dongchao, Han Fei, and Song Bifeng

Subjects
Artificial neural network, business.industry, Computer science, Volume (computing), Pattern recognition, Sample (statistics), computer.software_genre, Test (assessment), k-nearest neighbors algorithm, ComputingMethodologies_PATTERNRECOGNITION, Built-in self-test, Feature (machine learning), Artificial intelligence, Data mining, Cluster analysis, business, computer
Abstract

Aimed at the faults of K-nearest neighbor (KNN) algorithm in complex equipment's built-in test (BIT), an improved KNN (IKNN) algorithm is proposed to solve the problem from two aspects. Firstly, the weight of each input feature is learned using neural network to make important features contribute more in the classifications; this improves the precision of classification. Secondly, clustering each sample of the training set to reduce the data volume of training set, this improves the running speed of the algorithm. Simulation experiments prove the effectiveness of the IKNN algorithm with higher precision and less calculation.

Published
2008

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