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| 1 | 3D printing of bone tissue engineering scaffolds显示文摘Tissue engineering is promising in realizing successful treatments of human body tissue loss that current methods cannot treat well or achieve satisfactory clinical outcomes.In scaffold-based bone tissue engineering,a high performance scaffold underpins the success of a bone tissue engineering strategy and a major direction in the field is to produce bone tissue engineering scaffolds with desirable shape,structural,physical,chemical and biological features for enhanced biological performance and for regenerating complex bone tissues.Three-dimensional(3D)printing can produce customized scaffolds that are highly desirable for bone tissue engineering.The enormous interest in 3D printing and 3D printed objects by the science,engineering and medical communities has led to various developments of the 3D printing technology and wide investigations of 3D printed products in many industries,including biomedical engineering,over the past decade.It is now possible to create novel bone tissue engineering scaffolds with customized shape,architecture,favorable macro-micro structure,wettability,mechanical strength and cellular responses.This article provides a concise review of recent advances in the R&D of 3D printing of bone tissue engineering scaffolds.It also presents our philosophy and research in the designing and fabrication of bone tissue engineering scaffolds through 3D printing. | Chong Wang Wei Huang Yu Zhou Libing He Zhi He Ziling Chen Xiao He Shuo Tian Jiaming Liao Bingheng Lu Yen Wei Min Wang | 2020 | Bioactive Materials2020，5，1： | 20 |
| 2 | Materials Experiment on Tiangong-2 Space Laboratory显示文摘During the China's Tiangong-2(TG-2) flight mission, the experiments of 18 kinds of material samples were conducted in space by using a Multiple Materials Processing Furnace(MMPF) mounted in the orbital module of the TG-2 space laboratory. After the experiments of 12 kinds of samples of the first and second batches were completed successfully, astronauts packed and brought them back to the ground by ShenzhouII spacecraft. By studying processing and formation on semiconductor and optoelectronics materials, metal alloys and metastable materials, functional single-crystal, micro-and nano-composite materials encapsulated in sample ampoules both in space and on Earth, we expect to explore some physical and chemical processes and mechanism of the materials formation that are normally obscured and therefore are difficult to study quantitatively on the ground due to the gravity-induced convection, to obtain the processing and synthesis technology for preparing high quality materials, and lead to the improvement and development of materials processing techniques on Earth, and also develop the experiment device and comprehensive ability for materials experiment in microgravity environment. This report briefly introduces the main points of each research work and preliminary comparative analysis results of 12 samples carried out by scientists undertaking research task. | LI Xiangyang LU Ye MENG Xiangjian WANG Jianlu WANG Reng CHEN Lidong HUA Zile LI Xiaoya SHI Jianlin LIU Jinfeng XU Guisheng WEI Bingbo XIE Wenjun YIN Zhigang ZHANG Xingwang JIANG Hongxiang LI Hong LUO Xinghong ZHANG Haifeng ZHAO Jiuzhou WANG Binbin PAN Mingxiang | 2018 | 空间科学学报2018，38，5： | 4 |
| 3 | A novel steganography ap- proach for voice over IP 显示文摘 | Wei Ziling Zhao Baokang Liu Bo | 2014 | Journal of Ambient Intelligence and Humanized Computing2014，5，4： | 1 |
| 4 | Perovskite single-pixel detector for dual-color metasurface imaging recognition in complex environment显示文摘Highly efficient multi-dimensional data storage and extraction are two primary ends for the design and fabrication of emerging optical materials.Although metasurfaces show great potential in information storage due to their modulation for different degrees of freedom of light,a compact and efficient detector for relevant multi-dimensional data retrieval is still a challenge,especially in complex environments.Here,we demonstrate a multi-dimensional image storage and retrieval process by using a dual-color metasurface and a double-layer integrated perovskite single-pixel detector(DIP-SPD).Benefitting from the photoelectric response characteristics of the FAPbBr2.4l0.6 and FAPbl3 films and their stacked structure,our filter-free DIP-SPD can accurately reconstruct different colorful images stored in a metasurface within a single-round measurement,even in complex environments with scattering media or strong background noise.Our work not only provides a compact,filter-free,and noise-robust detector for colorful image extraction in a metasurface,but also paves the way for color imaging application of perovskite-like bandgap tunable materials. | Jiahao Xiong Zhi-Hong Zhang Zile Li Peixia Zheng Jiaxin Li Xuan Zhang Zihan Gao Zhipeng Wei Guoxing Zheng Shuang-Peng Wang Hong-Chao Liu | 2023 | Light(Science & Applications)2023，12，12： | 0 |
| 5 | Development of a bias power supply for Geiger mode avalanche photodiodes显示文摘Avalanche photodiodes(APDs)have high output and high stability requirements for bias power in Geiger mode.This paper designs an APD with high boost ratio,high precision,low temperature drift,small size,and low power.Bias power supply,this module uses switching chip IC and flyback transformer to achieve high step-up ratio,realizes precise output control through precision operational amplifier and T-type resistor feedback network,and designs appropriate compensation network to improve system stability.The size of the module is 2.5 cm×2.5 cm,the output voltage is adjustable from 0 to 450 V,and the maximum ripple does not exceed 5.4 mV.By changing the control voltage,any type of APD in Geiger mode can be biased,and the maximum deviation of the bias voltage does not exceed 0.5%. | MENG Yinjie WEI Zhengjun YAN Ziling WANG Jindong | 2023 | Optoelectronics Letters2023，19，11： | 0 |
| 6 | Technology trends in large-scale high-efficiency network computing显示文摘Network technology is the basis for large-scale high-efficiency network computing, such as supercomputing, cloud computing, big data processing, and artificial intelligence computing. The network technologies of network computing systems in different fields not only learn from each other but also have targeted design and optimization. Considering it comprehensively,three development trends, i.e., integration, differentiation, and optimization, are summarized in this paper for network technologies in different fields. Integration reflects that there are no clear boundaries for network technologies in different fields, differentiation reflects that there are some unique solutions in different application fields or innovative solutions under new application requirements,and optimization reflects that there are some optimizations for specific scenarios. This paper can help academic researchers consider what should be done in the future and industry personnel consider how to build efficient practical network systems. | Jinshu SU Baokang ZHAO Yi DAI Jijun CAO Ziling WEI Na ZHAO Congxi SONG Yujing LIU Yusheng XIA | 2022 | Frontiers of Information Technology & Electronic Engineering2022，23，12： | 0 |
| 7 | Machine learning-based spectral and spatial analysis of hyper-and multi-spectral leaf images for Dutch elm disease detection and resistance screening显示文摘Diseases caused by invasive pathogens are an increasing threat to forest health,and early and accurate disease detection is essential for timely and precision forest management.The recent technological advancements in spectral imaging and artificial intelligence have opened up new possibilities for plant disease detection in both crops and trees.In this study,Dutch elm disease(DED;caused by Ophiostoma novo-ulmi,)and American elm(Ulmus americana)was used as example pathosystem to evaluate the accuracy of two in-house developed high-precision portable hyper-and multi-spectral leaf imagers combined with machine learning as new tools for forest disease detection.Hyper-and multi-spectral images were collected from leaves of American elm geno-types with varied disease susceptibilities after mock-inoculation and inoculation with O.novo-ulmi under green-house conditions.Both traditional machine learning and state-of-art deep learning models were built upon derived spectra and directly upon spectral image cubes.Deep learning models that incorporate both spectral and spatial features of high-resolution spectral leaf images have better performance than traditional machine learning models built upon spectral features alone in detecting DED.Edges and symptomatic spots on the leaves were highlighted in the deep learning model as important spatial features to distinguish leaves from inoculated and mock-inoculated trees.In addition,spectral and spatial feature patterns identified in the machine learning-based models were found relative to the DED susceptibility of elm genotypes.Though further studies are needed to assess applications in other pathosystems,hyper-and multi-spectral leaf imagers combined with machine learning show potential as new tools for disease phenotyping in trees. | Xing Wei Jinnuo Zhang Anna O.Conrad Charles E.Flower Cornelia C.Pinchot Nancy Hayes-Plazolles Ziling Chen Zhihang Song Songlin Fei Jian Jin | 2023 | Artificial Intelligence in Agriculture2023，，4： | 0 |
| 8 | Mitigation of the Instability of Ultrafast Li-Ion Conductor Li_(6.6)Si_(0.6)Sb_(0.4)S_(5)I Enables High-Performance All-Solid-State Batteries显示文摘Solid-state batteries with excellent safety and high energy density display great potential as next-generation energy storage devices.However,few solid electrolytes simultaneously possess high ionic conductivity and good chemical and electrochemical stability.Herein,pure argyrodite Li_(6.6)Si_(0.6)Sb_(0.4)S_(5)I electrolyte with high Li-ion conductivity(9.0 mS cm−1)and poor stability is successfully synthesized via the typical mechanochemical route.Interfacial instability of this electrolyte with different electrode materials is investigated.A highly conductive Li_(3)InCl_(6)electrolyte,with a wide voltage window and excellent chemical and electrochemical stability,active material,and conductive carbon are introduced in the battery configuration,resulting in superior electrochemical performances with the bare LiNi_(0.7)Mn_(0.2)Co_(0.1)O_(2)cathode.The corresponding battery delivers a discharge capacity of 162.1 mAh g^(−1)at 0.5C and maintains 83.8%of the capacity after 200 cycles at room temperature.Moreover,this battery with a cathode mass loading of 6.37 mg cm−2 displays discharge capacities of 197.5 and 73.4 mAh g^(−1)at the beginning when cycled at 0.5C and 0.1C under the operating temperature of 60 and−20℃,respectively.The battery also achieved superior stablecycling performances at both temperatures.Due to the fast ionic conductivity from Li_(6.6)Si_(0.6)Sb_(0.4)S_(5)I and high electronic conductivity from carbon in the cathode,the thick-electrode configurations with huge mass loadings of 50.96 and 76.43 mg cm^(−2)also exhibit good capacities and highly reversible cyclability.This work provides a guideline for enabling superior conducting sulfide electrolytes with poor stability in thick-electrode configuration solid-state batteries. | Cong Liao Chuang Yu Shaoqing Chen Chaochao Wei Zhongkai Wu Shuai Chen Ziling Jiang Shijie Cheng Jia Xie | 2023 | Renewables2023，1，2： | 0 |
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