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| 1 | The study on the mechanical properties of PU/MF double shell self-healing microcapsules显示文摘The self-healing microcapsules can be buried in the coating to improve the anticorrosive ability.In this paper,self-healing microcapsules of polyurea(PU)/melamine resin(MF)double shell were prepared by in-situ polymerization and interfacial polymerization with isocyanate as the core material.Scanning electron microscope was used to observe the microcapsule morphology.The structures of microcapsules prepared with different chain extenders were characterized by Fourier transform infrared spectroscopy.The micromanipulation system was used to loading–holding,loading–unloading and loading to rupture individual microcapsules,so as to explore the mechanical properties of microcapsules.The Young’s modulus corresponding to microcapsules was calculated by mathematical model fitting.The self-healing properties of microcapsule coating were characterized by optical microscope.The experimental results showed that the microcapsule shell prepared under optimized conditions had a complete morphology and good mechanical properties.The microcapsule was in the elastic deformation stage under small deformation,and the plastic deformation stage under large deformation.The Young’s modulus range of microcapsules was 9.29–14.51 MPa,and the corresponding Young’s modulus could be prepared by adjusting the process.The surface crack of the coating containing microcapsule could heal itself after48 h in a humid environment. | Guohao Du Jianfeng Hu Jianhui Zhou Guangwu Wang Shengli Guan Hailing Liu Man Geng Chuang Lv Yaoqiang Ming Jinqing Qu | 2020 | Chinese Journal of Chemical Engineering2020，28，5： | 4 |
| 2 | Effect of surfactant on zeta potential and rheology behavior of methylene bis (thiocyanate) suspension concentrate显示文摘Methylene bis(thiocyanate)(MBT) is insoluble in water, so suspension concentrate(SC) of MBT is extremely relied on surfactants. In this paper, SC of MBT was prepared with wet-grinding technology, and the effect of surfactants,such as Morwet D425(D425) and Morwet EFW(EFW)(two kinds of dispersant), on the Zeta potential and rheology behavior of MBT SC were investigated. The results showed that the Zeta potential absolute value of MBT SC increased with the increasing content of D425, and it decreased with the increasing content of EFW at acidic solution(pH = 4.5). In the combination system of D425 and EFW, Zeta potential of MBT SC decreased first and then increased with the increasing content of EFW. The relationship between shear rate(γ) and viscosity(η) was studied according to Herschel–Bulkley model: η = η0+ k/γ, and the relationship between shear rate(γ) and shear force(τ) was investigated according to:τ = τ0+Kγ~n. It was revealed that the mixed fluid belonged to Yield Pseudoplastic Fluid. | Jianfeng Hu Yan Cai Shan Lu Jiezhen Xu Zhongrun Yun Jianheng Huang Yuliang Wen Jinqing Qu | 2017 | Chinese Journal of Chemical Engineering2017，25，5： | 1 |
| 3 | Self-emulsiiying hydroxyl aerylic polymer dispersions for two component waterbm'ne polyurethane coatings 显示文摘 | Kong Xia Li Shaomao Qu Jinqing | 2010 | Journal of Maeromolecular Science2010，，47： | 1 |
| 4 | DNA-lipid complexes carrying azobenzene moieties: Preparation, characterization, and photoisomerization显示文摘 | Jinqing Qu Zhiming Qiu Huanqin Chen Naoya Ogata Toshio Masuda | 2009 | Polymer2009，，23： | 1 |
| 5 | Deep learning enhanced lithium-ion battery nonlinear fading prognosis显示文摘With the assistance of artificial intelligence,advanced health prognosis technique plays a critical role in the lithium-ion(Li-ion) batteries management system.However,conventional data-driven early aging prediction exhibited dramatic drawbacks,i.e.,volatile capacity nonlinear fading trajectories create obstacles to the accurate multistep ahead prediction due to the complex working conditions of batteries.Herein,a novel deep learning model is proposed to achieve a universal and accurate Li-ion battery aging prognosis.Two battery datasets with various electrode types and cycling conditions are developed to validate the proposed approaches.Knee-point probability(KPP),extracted from the capacity loss curve,is first proposed to detect knee points and improve state-of-health(SOH) predictive accuracy,especially during periods of rapid capacity decline.Using one-cycle data of partial raw voltage as the model input,the SOH and KPP can be simultaneously predicted at multistep ahead,whereas the conventional method showed worse accuracy.Furthermore,to explore the underlying characteristics among various degradation tendencies,an online model update strategy is developed by leveraging the adversarial adaptationinduced transfer learning technique.This work gains new sights into the comprehensive Li-ion battery management and prognosis framework through decomposing capacity degradation trajectories and adversarial learning on the unlabeled samples. | Shanling Ji Jianxiong Zhu Zhiyang Lyu Heze You Yifan Zhou Liudong Gu Jinqing Qu Zhijie Xia Zhisheng Zhang Haifeng Dai | 2023 | Journal of Energy Chemistry2023，，3： | 0 |
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