|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Effect of surface area and heteroatom of porous carbon materials on electrochemical capacitance in aqueous and organic electrolytes显示文摘A series of porous carbon materials with wide range of specific surface areas and different heteroatom contents had been prepared using polyaniline as carbon precursor and KOH as an activating agent. Effect of surface area and heteroatom of porous carbon materials on specific capacitance was investigated thoroughly in two typical aqueous KOH and organic 1-butyl-3- methylimidazolium tetrafluoroborate/acetonitirle electrolytes. The different trends of capacitance performance were observed in these two electrolytes. Electrochemical analyses suggested that the presence of faradaic interactions on heteroatom-enriched carbon materials in organic environment is less significant than that observed in aqueous electrolytes. Thus, in aqueous electrolyte, a balance between surface area and heteroatom content of activated porous carbon would be found to develop a supercapacitor with high energy density. In organic electrolyte, the capacitance performance of porous carbon is strongly dependent on the surface area. The results may be useful for the design of porous carbon-based supercapacitor with the desired capacitive performance in aqueous and organic electrolytes. | WANG RuTao LANG JunWei YAN XingBin | 2014 | Science China Chemistry2014，57，11： | 4 |
| 2 | Effect of carboxylic acid groups on the supercapacitive performance of functional carbon frameworks derived from bacterial cellulose显示文摘Three-dimensional(3D) carbonaceous materials derived from bacterial cellulose(BC) has been introduced as electrode for supercapacitors in recent. Here, we report a simple strategy for the synthesis of functional carbon frameworks through 2,2,6,6-tetramethylpilperidine 1-oxyl radical(TEMPO)-mediated oxidation of bacterial cellulose(BC) followed by carbonization. TEMPO-mediated oxidation can efficiently convert the hydroxyls on the surface of BC to carboxylate groups to improve electrochemical activity. Because of its high porosity, good hydrophilicity, rich oxygen groups, and continuous ion transport in-between sheet-like porous network, the TEMPO-oxidized BC delivers a much higher gravimetric capacitance(137.3 F/g) at low annealing temperature of 500℃ than that of pyrolysis BC(31 F/g) at the same annealing temperature. The pyrolysis modified BC obtained at 900℃ shows specific capacitance(160.2 F/g), large current stability and long-term stability(84.2% of its initial capacitance retention after 10,000 cycles). | Tianyun Zhang Junwei Lang Li Liu Lingyang Liu Hongxia Li Yipeng Gu Xingbin Yan Xin Ding | 2017 | Chinese Chemical Letters2017，28，12： | 2 |
| 3 | The roles of graphene in advanced Li-ion hybrid supercapacitors显示文摘Lithium-ion hybrid supercapacitors(LIHSs), also called Li-ion capacitors, are electrochemical energy storage devices that combining the advantages of high power density of supercapacitor and high energy density of Li-ion battery. However, high power density and long cycle life are still challenges for the current LIHSs due to the imbalance of charge-storage capacity and electrode kinetics between capacitor-type cathode and battery-type anode. Therefore, great efforts have been made on designing novel cathode materials with high storage capacity and anode material with enhanced kinetic behavior for LIHSs. With unique two-dimensional form and numerous appealing properties, for the past several years, the rational designed graphene and its composites materials exhibit greatly improved electrochemical performance as cathode or anode for LIHSs. Here, we summarized and discussed the latest advances of the stateof-art graphene-based materials for LIHSs applications. The major roles of graphene are highlighted as(1) a superior active material,(2) ultrathin 2D flexible support to remedy the sluggish reaction of the metal compound anode, and(3) good 2D building blocks for constructing macroscopic 3D porous carbon/graphene hybrids. In addition, some high performance aqueous LIHSs using graphene as electrode were also summarized. Finally, the perspectives and challenges are also proposed for further development of more advanced graphene-based LIHSs. | Junwei Lang Xu Zhang Bao Liu RutaoWang Jiangtao Chen Xingbin Yan | 2018 | Journal of Energy Chemistry2018，27，1： | 2 |
| 4 | Influence of nitric acid modification of ordered mesoporous carbon materials on their capacitive performances in different aqueous electrolytes 显示文摘 | LANG Junwei YAN Xingbin LIU Wenwen | 2012 | J Power Sources2012，204，： | 1 |
| 5 | Facile approach to prepare loose-packed NiO nano-flakes materials for supereapaeitors 显示文摘 | Lang Junwei Kong Lingbin Wu Weijin | 2008 | Chemical Communications2008，，35： | 1 |
| 6 | Facile ap-proaeh to prepare loose-packed NiO nano-flakes materials for supereapacitors 显示文摘 | Lang Junwei Kong Ling bin Wu Weijin | 2008 | Chem Commun2008，35，： | 1 |
| 7 | Porous cobalt hydroxide film electrodeposited on nickel foam with exeeUent electrochemical capacitive behavior 显示文摘 | Kong Lingbin Liu Maocheng Lang Junwei | 2011 | J Solid State Electrochem2011，15，： | 1 |
| 8 | Flexible and conductive nanocomposite electrode based on graphenesheets and cotton cloth for supercapacitor 显示文摘 | Wenwen Liu Xingbin Yan Junwei Lang | 2012 | Journal of Materials Chemistry2012，22，17： | 1 |
| 9 | Task-wise attention guided part complementary learning for few-shot image classification显示文摘A general framework to tackle the problem of few-shot learning is meta-learning,which aims to train a well-generalized meta-learner(or backbone network)to learn a base-learner for each future task with small training data.Although a lot of work has produced relatively good results,there are still some challenges for few-shot image classification.First,meta-learning is a learning problem over a collection of tasks and the meta-learner is usually shared among all tasks.To achieve image classification of novel classes in different tasks,it is needed to learn a base-learner for each task.Under the circumstances,how to make the base-learner specialized,and thus respond to different inputs in an extremely task-wise manner for different tasks is a big challenge at present.Second,classification network usually inclines to identify local regions from the most discriminative object parts rather than the whole objects for recognition,thereby resulting in incomplete feature representations.To address the first challenge,we propose a task-wise attention(TWA)module to guide the base-learner to extract task-specific image features.To address the second challenge,under the guidance of TWA,we propose a part complementary learning(PCL)module to extract and fuse the features of multiple complementary parts of target objects,and thus we can obtain more specific and complete information.In addition,the proposed TWA module and PCL module can be embedded into a unified network for end-to-end training.Extensive experiments on two commonly-used benchmark datasets and comparison with state-of-the-art methods demonstrate the effectiveness of our proposed method. | Gong CHENG Ruimin LI Chunbo LANG Junwei HAN | 2021 | Science China(Information Sciences)2021，64，2： | 1 |
| 10 | Influence of nitric acid modification of ordered mesoporous carbon materials on their capacitive performances in different aqueous electrolytes显示文摘 | Lang Junwei Yan Xingbin Liu Wenwen | 2012 | Jour- nal of Power Sources2012，204，： | 1 |
| 11 | High performance supercapacitor electrode based on graphene paper via flame-induced reduction of graphene oxide paper显示文摘 | Sun Dongfei Yan Xingbin Lang Junwei | 2013 | J Power Sources2013，222，： | 1 |
| 12 | JOURNAL OF POWER SOURCES显示文摘 | Sun Dongfei Yan Xingbin Lang Junwei | 2012 | 2222012，5255，： | 1 |
| 13 | High performance supercapacitor electrode based on graphene paper via flame-induced reduction of graphene oxide paper显示文摘 | Dongfei Sun Xingbin Yan Junwei Lang Qunji Xue | 2013 | Journal of Power Sources2013，，： | 1 |
| 14 | Synthesis of a water soluble, monosubstituted C60 polymeric derivative and its photoconductive properties 显示文摘 | Junwei Y Lang L Changchun W | 2003 | Macromolecules2003，36，： | 1 |
| 15 | Nitrogen-doped carbon nanotubes by multistep pyrolysis process as a promising anode material for lithium ion hybrid capacitors显示文摘Lithium-ion hybrid capacitors(LIHCs) is a promising electrochemical energy storage devices which combines the advantages of lithium-ion batteries and capacitors.Herein,we developed a facile multistep pyrolysis method,prepared an amorphous structure and a high-level N-doping carbon nanotubes(NCNTs),and by removing the Co catalyst,opening the port of NCNTs,and using NCNTs as anode material.It is shows good performance due to the electrolyte ions enter into the electrode materials and facilitate the charge transfer.Furthermore,we employ the porous carbon material(APDC) as the cathode to couple with anodes of NCNTs,building a LIHCs,it shows a high energy density of 173 Wh/kg at 200 W/kg and still retains 53 Wh/kg at a high power density of 10 kW/kg within the voltage window of 0-4.0 V,as well as outstanding cyclic life keep 80% capacity after 5000 cycles.This work provides an opportunity for the preparation of NCNTs,that is as a promising high-performance anode for LIHCs. | Juan Yang Dan Xu Ruilin Hou Junwei Lang Zhaoli Wang Zhengping Dong Jiantai Ma | 2020 | Chinese Chemical Letters2020，31，9： | 0 |
| 16 | Feature Enhancement Network for Object Detection in Optical Remote Sensing Images显示文摘Automatic and robust object detection in remote sensing images is of vital significance in real-world applications such as land resource management and disaster rescue.However,poor performance arises when the state-of-the-art natural image detection algorithms are directly applied to remote sensing images,which largely results from the variations in object scale,aspect ratio,indistinguishable object appearances,and complex background scenario.In this paper,we propose a novel Feature Enhancement Network(FENet)for object detection in optical remote sensing images,which consists of a Dual Attention Feature Enhancement(DAFE)module and a Context Feature Enhancement(CFE)module.Specifically,the DAFE module is introduced to highlight the network to focus on the distinctive features of the objects of interest and suppress useless ones by jointly recalibrating the spatial and channel feature responses.The CFE module is designed to capture global context cues and selectively strengthen class-aware features by leveraging image-level contextual information that indicates the presence or absence of the object classes.To this end,we employ a context encoding loss to regularize the model training which promotes the object detector to understand the scene better and narrows the probable object categories in prediction.We achieve our proposed FENet by unifying DAFE and CFE into the framework of Faster R-CNN.In the experiments,we evaluate our proposed method on two large-scale remote sensing image object detection datasets including DIOR and DOTA and demonstrate its effectiveness compared with the baseline methods. | Gong Cheng Chunbo Lang Maoxiong Wu Xingxing Xie Xiwen Yao Junwei Han | 2021 | Journal of Remote Sensing2021，，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员