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| 1 | Highly Selective Lithium Ion Adsorbents:Polymeric Porous Microsphere with Crown Ether Groups显示文摘In this study, we prepared and applied polymeric porous microsphere adsorbents with selectivity for Li^+ extraction from aqueous solution. We synthesized the adsorbents by suspension polymerization using methacryloyoxyme-12-crown-4(M12C4) as a functional monomer, which had been synthesized from 2-hyroxymethyl-12-crown-4 and methacryloyl chloride. We verified the chemical composition by solid nuclear magnetic resonance(13C-NMR) spectroscopy and observed the porous structure by scanning electron microscopy(SEM). We conducted adsorption isothermal and kinetic tests to determine the adsorption properties. It was found that the adsorbents showed high adsorption efficiency and an adsorption equilibrium time of 200 min. In addition, since the crown ether used in this work could form a stable complex with Li^+, we observed good selectivity for Li^+ in the prepared solution compared with other ions such as Na^+, K^+, Mg^(2+), and Ca^(2+). We reused the adsorbents five times with no significant decrease in adsorptive capacity. | Caideng Yuan Lei Zhang Haichao Li Ruiwei Guo Meng Zhao Lan Yang | 2019 | Transactions of Tianjin University2019，25，2： | 3 |
| 2 | Phase imaging with an untrained neural network显示文摘Most of the neural networks proposed so far for computational imaging(CI)in optics employ a supervised training strategy,and thus need a large training set to optimize their weights and biases.Setting aside the requirements of environmental and system stability during many hours of data acquisition,in many practical applications,it is unlikely to be possible to obtain sufficient numbers of ground-truth images for training.Here,we propose to overcome this limitation by incorporating into a conventional deep neural network a complete physical model that represents the process of image formation.The most significant advantage of the resulting physics-enhanced deep neural network(PhysenNet)is that it can be used without training beforehand,thus eliminating the need for tens of thousands of labeled data.We take single-beam phase imaging as an example for demonstration.We experimentally show that one needs only to feed PhysenNet a single diffraction pattern of a phase object,and it can automatically optimize the network and eventually produce the object phase through the interplay between the neural network and the physical model.This opens up a new paradigm of neural network design,in which the concept of incorporating a physical model into a neural network can be generalized to solve many other CI problems. | Fei Wang Yaoming Bian Haichao Wang Meng Lyu Giancarlo Pedrini Wolfgang Osten George Barbastathis Guohai Situ | 2020 | Light(Science & Applications)2020，9，1： | 3 |
| 3 | Monitoring the Modal Frequency and Velocity Variations of Bridges under Ambient Excitation显示文摘We conducted a long-term monitoring experiment on the Lutuanxilu Bridge located in Changping District of Beijing, employing our recently developed real-time bridge monitoring system based on the Guralp CMG-6TD broadband seismometer. We identified the modal parameters with the stochastic subspace identification( SSI) algorithm,and continuously monitored the temporal velocity variation with coda wave interferometry.The results show that:( 1) the highly sensitive Guralp CMG-6TD broadband seismometer,which records the three-component vibration signal within broad frequency range,is well suited for long-term bridge health monitoring.( 2) With the continuous vibration signal from ambient excitation,the stochastic subspace algorithm can robustly identify the low-order modal parameters and the coda wave interferometry can accurately monitor the tiny velocity variation.( 3) The elastic modulus of bridge materials changes significantly associated with varying temperature,leading to diurnal velocity variation with amplitude of approximately 1%. The velocity variation shows strong negative correlation with temperature fluctuation. Meanwhile,the modal frequencies remain quite stable,suggesting that the velocity variation may be a more sensitive quantitative damage index.( 4) While the modal frequencies reflect the integrated health status of the bridge,the velocity variation can be utilized to monitor the local elastic modulus. Therefore,it is crucial for bridge health monitoring to continuously monitor the two key damage indexes under ambient excitation. | Chen Haichao Ge Hongkui Meng Fanbao Wang Xiaoqiong Yang Wei | 2015 | Earthquake Research in China2015，29，4： | 1 |
| 4 | Global Well-Posedness of Solutions for the Sixth Order Convective Cahn-Hilliard Equation显示文摘In this paper,we consider the global well-posedness of smooth solutions for the Cauchy problem of a sixth order convective Cahn-Hilliard equation with small initial data.We first construct a local smooth solution,then by combining some a priori estimates,continuity argument,the local smooth solution is extended step by step to all t>0 provided that the L1 norm of initial data is suitably small and the smooth nonlinear functions f(u)and g(u)satisfy certain local growth conditions at some fixed point■. | Xiaopeng ZHAO Fengnan LIU Haichao MENG | 2021 | Journal of Mathematical Research with Applications2021，41，2： | 1 |
| 5 | Sustainability Intelligent Evaluation of Regional Microgrid Interconnection System Based on Combination Entropy Weight Rank Order-TOPSIS and NILA-KELM显示文摘Sustainability evaluation of regional microgrid interconnection system is conducive to a profound and comprehensive understanding of the impact of interconnection system projects.In order to realize the comprehensive and scientific intelligent evaluation of the system,this paper proposes an evaluation model based on combination entropy weight rank order-technique for order preference by similarity to an ideal solution(TOPSIS)and Niche Immune Lion Algorithm-Extreme Learning Machine with Kernel(NILAKELM).Firstly,the sustainability evaluation indicator system of the regional microgrid interconnection system is constructed fromfour aspects of economic,environmental,social,and technical characteristics,and the evaluation indicators are explained.Then,the classical evaluationmodel based on TOPSIS is constructed,and the entropy weight method and rank order method(RO)are coupled to obtain the indicator weight.The niche immune algorithm is used to improve the lion algorithm,and the improved lion algorithm is used to optimize the parameters of KELM,and the intelligent evaluation model based on NILA-KELM is obtained to realize fast real-time calculation.Finally,the scientificity and accuracy of themodel proposed in this paper are verified.The model proposed in this paper has the lowest RMSE,MAE and RE values,indicating that its intelligent evaluation results are the most accurate.This study is conducive to the horizontal comparison of the overall performance of regional microgrid interconnection system projects,helps investors to choose the most promising project scheme,and helps the government to find feasible project. | Haichao Wang Yingying Fan Weigao Meng Qiaoran Yang | 2022 | Energy Engineering2022，119，3： | 0 |
| 6 | HMGB1 increases radiosensitivity by interacting with HDAC1显示文摘 | He Xin Meng Qinghui Meng Aimin Liu Qiang Wang Haichao Fan Saijun HeXin MengQinghui MengAimin LiuQiang WangHaichao FanSaijun | 2015 | 中华放射医学与防护杂志2015，35，1： | 0 |
| 7 | Well-Posedness of Solutions for Sixth-Order Cahn-Hilliard Equation Arising in Oil-Water-Surfactant Mixtures显示文摘In this paper,by using the Lp-Lq-estimates,regularization property of the linear part of e^-t△3 and successive approximations,we consider the existence and uniqueness of global mild solutions to the sixth-order Cahn-Hilliard equation arising in oil-water-surfactant mixtures in suitable spaces,namely C^0([0,T];W^2,N(l-1)/2(Ω))when the norm||u0||W^2,N(l-1)/2(Ω)is sufficiently small. | MENG Haichao ZHAO Xiaopeng | 2020 | Journal of Partial Differential Equations2020，33，3： | 0 |
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