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| 1 | Recent progress in interface modification for dye-sensitized solar cells显示文摘Interface modification on the TiO2/dye/electrolyte interface of dye-sensitized solar cells (DSCs) is one of the most effective approaches to suppress the charge recombination,improve electron injection and transportation,and thus ameliorate the conversion efficiency and stability of DSCs.Conventional research focusing on the photoanodes interface modification before sensitization in dye-sensitized solar cells has been carried out and reviewed.However,recent studies showed that post-modification after sensitization of the TiO2 electrode also plays a significant role on the TiO2/dye/electrolyte interface.This post-modification using the immersing method could deprotonate dye molecules,prohibit the dye aggregation and retard the recombination reaction.As a result,it has great influence on the devices' photovoltaic performance.This interface modification could also provide an approach to broaden the response of the solar spectrum by introducing an alternative assembling structure.An in-situ meaning of using a co-adsorbent is employed to modify the interface in the DSCs,which could retard the aggregation of the dye molecules and enhance the conversion efficiency.In addition,electrolyte additives can be used to modify the TiO2/dye/electrolyte interface through some unique mechanisms.Based on the background of interface modification of photoanodes before sensitization,this review introduces various interface modifications after sensitization of dye-sensitized solar cells and their mechanisms. | MA BeiBei,GAO Rui,WANG LiDuo,ZHU YiFeng,SHI YanTao,GENG Yi,DONG HaoPeng & QIU Yong Key Lab of Organic Optoelectronics & Molecular Engineering of Ministry of Education Department of Chemistry,Tsinghua University,Beijing 100084,China | 2010 | Science China Chemistry2010，53，8： | 4 |
| 2 | Refinement mechanism of cerium addition on solidification structure and sigma phase of super austenitic stainless steel S32654显示文摘The influence of Ce addition on the solidification structure and σphase of super austenitic stainless steel S32654 was systematically investigated via microstructural characterization and thermodynamic calcula- tion. The results indicate that a small addition of Ce could modify MgO and MnS into Ce-bearing inclu- sions Ce_(2)O_(3)and Ce_(2)O_(2)S. Ce addition led to noticeable refinement of both the dendrite structure and σphase. The refinement mechanism could be attributed to the combined actions of effective Ce-bearing inclusions and solute Ce. Effective Ce-bearing inclusions could serve as heterogeneous nucleation cores of austenite as well as σphase, which provided a favorable prerequisite for their refinement. Solute Ce significantly enhanced the undercooling degree of the system, further promoting dendrite structure re- finement. Meanwhile, solute Ce improved the eutectic precipitation conditions of σphase and further promoted its nucleation, while the dendrite refinement limited its growth space. Finally, more fine and dispersed σphase particles formed in S32654 with Ce addition. The refinement of dendrite structure and σ phase will reduce the temperature and time required for high-temperature homogenization, which is beneficial to the hot working of this steel. | Shucai Zhang Jiangtao Yu Huabing Li Zhouhua Jiang Yifeng Geng Hao Feng Binbin Zhang Hongchun Zhu | 2022 | Journal of Materials Science & Technology2022，，7： | 3 |
| 3 | Abnormal intra-network architecture in extra-striate cortices in amblyopia: a resting state fMRI study显示文摘Background:Amblyopia(lazy eye)is one of the most common causes of monocular visual impairment.Intensive investigation has shown that amblyopes suffer from a range of deficits not only in the primary visual cortex but also the extra-striate visual cortex.However,amblyopic brain processing deficits in large-scale information networks especially in the visual network remain unclear.Methods:Through resting state functional magnetic resonance imaging(rs-fMRI),we studied the functional connectivity and efficiency of the brain visual processing networks in 18 anisometropic amblyopic patients and 18 healthy controls(HCs).Results:We found a loss of functional correlation within the higher visual network(HVN)and the visuospatial network(VSN)in amblyopes.Additionally,compared with HCs,amblyopic patients exhibited disruptions in local efficiency in the V3v(third visual cortex,ventral part)and V4(fourth visual cortex)of the HVN,as well as in the PFt,hIP3(human intraparietal area 3),and BA7p(Brodmann area 7 posterior)of the VSN.No significant alterations were found in the primary visual network(PVN).Conclusion:Our results indicate that amblyopia results in an intrinsic decrease of both network functional correlations and local efficiencies in the extra-striate visual networks. | Zhuo Lu Yufeng Huang Qilin Lu Lixia Feng Benedictor Alexander Nguchu Yanming Wang Huijuan Wang Geng Li Yifeng Zhou Bensheng Qiu Jiawei Zhou Xiaoxiao Wang | 2019 | Eye and Vision2019，6，1： | 3 |
| 4 | Learning to focus: cascaded feature matching network for few-shot image recognition显示文摘Generally, deep networks learn to recognize a category of objects by training on a large number of annotated images accurately. However, a meta-learning problem known as a low-shot image recognition task occurs when a few images with annotations are available for learning a recognition model for a single category. Consequently, the objects in testing/query and training/support image datasets are likely to vary in terms of size, location, style, and so on. In this paper, we propose a method, cascaded feature matching network(CFMN), to solve this problem. We train the meta-learner to learn a more fine-grained and adaptive deep distance metric using feature matching block, which aligns associated features together and naturally ignores non-discriminative features. By applying the proposed feature matching block in different layers of the network, multi-scale information among the compared images is incorporated into the final cascaded matching feature, which boosts the recognition performance and generalizes better by learning on relationships. Moreover, the experiments for few-shot learning(FSL) using two standard datasets:miniImageNet and Omniglot, confirm the effectiveness of our proposed method. Besides, the multi-label fewshot task is first studied on a new data split of the COCO dataset, which further shows the superiority of the proposed feature matching network when performing the FSL in complex images. | Mengting CHEN Xinggang WANG Heng LUO Yifeng GENG Wenyu LIU | 2021 | Science China(Information Sciences)2021，64，9： | 2 |
| 5 | Enhanced oxygen reduction kinetics by a porous heterostructured cathode for intermediate temperature solid oxide fuel cells显示文摘A novel porous heterostructured Nd_(0.8)Sr_(1.2)CoO_(4)±/Nd_(0.5)Sr_(0.5)CoO_(3-δ)(NSC_(214/113))cathode for intermediate tem-perature solid oxide fuel cells(IT-SOFCs)is developed to significantly enhance oxygen reduction reaction(ORR)kinetics.Compared to single-phase materials,the fabricated porous heterostructured NSC 214/113 shows optimized electrochemical properties,including a better conductivity,20 times faster surface oxygen exchange kinetics,and a comparatively lower area-specific resistance(0.065Ωcm^(2) at 800℃).The single cell with Ni-YSZ|YSZ-GDC|NSC_(214/113) configuration exhibits a high peak power density of 1.10 W cm^(−2) at 800℃,superior to other cells reported in literature with similar heterostructured cathodes.Moreover,the underlying mechanism of the ORR performance enhancement is further investigated,revealing that the formation of heterojunction can lead to a narrowed energy bandgap and a decrease of Co oxidation state,which further induce better conductivity,more available electrons and oxygen vacancies to enhance the ORR process.Taken together,our research also provides new insights into potential application of artificial intelligence(AI)method involved in materials in-telligent identification,cell state estimation,system diagnostic and optimization.The revolutionary force of AI,especially in the field of new electrode material development is now advancing in its full swing.More and greater breakthroughs are still expected. | Yun Zheng Chenhuan Zhao Tong Wu Yifeng Li Wenqiang Zhang Jianxin Zhu Ga Geng Jing Chen Jianchen Wang Bo Yu Jiujun Zhang | 2020 | Energy and AI2020，2，2： | 0 |
| 6 | SwiftArray: Accelerating Queries on Multidimensional Arrays显示文摘Scientific instruments and simulation programs are generating large amounts of multidimensional array data.Queries with value and dimension subsetting conditions are commonly used by scientists to find useful information from big array data,and data storage and indexing methods play an important role in supporting queries on multidimensional array data efficiently.In this paper,we propose SwiftArray,a new storage layout with indexing techniques to accelerate queries with value and dimension subsetting conditions.In SwiftArray,the multidimensional array is divided into blocks and each block stores sorted values.Blocks are placed in the order of a Hilbert space-filling curve to improve data locality for dimension subsetting queries.We propose a 2-D-Bin method to build an index for the blocks’value ranges,which is an efficient way to avoid accessing unnecessary blocks for value subsetting queries.Our evaluations show that SwiftArray surpasses the NetCDF-4 format and FastBit indexing technique for queries on multidimensional arrays. | Yifeng Geng Xiaomeng Huang Guangwen Yang | 2014 | Tsinghua Science and Technology2014，19，5： | 0 |
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