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Bioinspired sensing-memory-computing integrated vision systems: biomimetic mechanisms, design principles, and applications

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science China(Information sciences) 2024年第5期67卷 5-27页

作者： Yujie HUANG Yinlong TAN Yan KANG Yabo CHEN Yuhua TANG Tian JIANG institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology College of Advanced Interdisciplinary Studies National University of Defense Technology institute for Quantum science and technology College of ScienceNational University of Defense Technology

With the explosion of sensory data in the Internet of Things(Io T) era, conventional machine vision systems are becoming increasingly difficult to meet the requirements of high efficiency, low energy consumption, and low latency due to their inherent shortcomings of separate sensing, memory, and computing units. Inspired by the retina and neuromorphic computing, the sensing-memory-computing integrated vision system(SMCVS) that features low power consumption, low latency, and high parallelism has been considered a promising technology to surpass the von Neumann architecture and realize strong artificial ***, novel materials like two-dimensional semiconductors and quantum dots with novel optoelectronic performance provide hardware carriers for implementing integrated sensing-memory-computing architectures,attracting considerable attention. This paper reviews the recent research progress in bioinspired vision systems in terms of biomimetic mechanisms, design principles, computational architectures, and ***, the biomimetic mechanisms are illustrated to guide the design of high-performance artificial visual perception systems. Then the research progress of optoelectronic-synapse-based bioinspired vision systems in the device principles and applications including image filtering, color recognition, visual adaptation, and motion detection are summarized. Finally, the challenges and future developing directions of the SMCVS are provided regarding bionic application, architecture design, and device fabrication.

关键词： sensing-memory-computing architecture neuromorphic computing retinomorphic device image recognition visual system

Mechanism of reduction-diffusion reaction in Sm-Fe binary system at low temperature using molten salts

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Journal of Rare Earths 2024年第10期42卷 1889-1894页

作者： Jungryang Kim Shusuke Okada Kenta Takagi Kimihiro Ozaki Innovative Functional Materials Research institute National Institute of Advanced Industrial Science and Technology (AIST)

In this study,the mechanism of the reduction-diffusion reaction in a Sm-Fe binary system at low temperature was studied to investigate the possibility of synthesis of a Fe-rich TbCu7-type SmFex（x>9）by the low-temperature diffusion-reduction（LTRD） process using LiCl-KCl eutectic molten ***,the Sm-Fe phase transformation depending on the Sm-Fe composition,the LTRD temperature,and time was investigated,and it is found that the obtained metastable phase is only TbCu7-type SmFe～8.5,which is not a Fe-rich *** Fe content does not change even after an expended LTRD process,and the metastable TbCu7-type SmFe～8.5tends to transform to the stable *** addition,it is found that the Sm-Fe phase starts to synthesize from the Sm-rich phase in the order of SmFe2,SmFe3,and SmFe8.5as the LTRD temperature increases（when the time was 10 h） or the LTRD time increases（when the temperature was 550℃）.Core-shell-like particles are observed in the case of a short LTRD time,and the core and the shell are Fe and the Sm-rich Sm-Fe phase,respectively,indicating that the Sm-rich phase begins to produce on the surface of the Fe *** is difficult to synthesize a Fe-rich TbCu7-type SmFex（x>9） phase with the Sm-Fe binary system,suggesting that a different approach,such as addition of other elements,will be necessary.

关键词： Low-temperature synthesis Molten salts Rare earths Reduction-diffusion process Sm–Fe compounds Synthesis mechanism

Simulating a Chern Insulator with C = ±2 on Synthetic Floquet Lattice

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Chinese Physics Letters 2024年第9期41卷 4-11页

作者：雷凌霄王伟臣黄光耀胡顺曹希张鑫方邓明堂陈平形 institute for Quantum science and technology College of ScienceNational University of Defense Technology institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Greatwall Quantum Laboratory Hefei national Laboratory

The synthetic Floquet lattice, generated by multiple strong drives with mutually incommensurate frequencies,provides a powerful platform for quantum simulation of topological phenomena. In this study, we propose a 4-band tight-binding model of the Chern insulator with a Chern number C = ±2 by coupling two layers of the half Bernevig-Hughes-Zhang lattice and subsequently mapping it onto the Floquet lattice to simulate its topological properties.

关键词： Quantum computers

Facile synthesis of accordion-like porous carbon from waste PET bottles-based MIL-53(Al) and its application for high-performance Zn-ion capacitor

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Green Energy & Environment 2024年第7期9卷 1138-1150页

作者： Jiaxin Li Shuai Zhang Yumeng Hua Yichao Lin Xin Wen Ewa Mijowska Tao Tang Xuecheng Chen Rodney S.Ruoff Faculty of Chemical technology and Engineering West Pomeranian University of Technology Key State Key Laboratory of Polymer Physics and Chemistry Changchun Institute of Applied Chemistry Chinese Academy of Sciences School of Safety Engineering China University of Mining and Technology institute of Advanced Electrical Materials Qingdao University of Science and Technology institute for Basic science Center for Multiple Dimensional Carbon Materials Department of Chemistry Ulsan National Institute of Science and Technology (UNIST) Department of Materials science and Engineering Ulsan National Institute of Science and Technology (UNIST) School of Energy and Chemical Engineering Ulsan National Institute of Science and Technology (UNIST)

It is of great scientific and economic value to recycle waste poly（ethylene terephthalate）(PET) into high-value PET-based metal organic frameworks（MOFs） and further convert it into porous carbon for green energy storage applications. In the present study, a facile and costeffective hydrothermal process was developed to direct recycle waste PET bottles into MIL-53（Al） with a 100% conversation, then the MOFderived porous carbon was assembled into electrodes for high-performance supercapacitors. The results indicated that the as-synthesized carbon exhibited high SSA of 1712 m2g-1and unique accordion-like structure with hierarchical porosity. Benefit to these advantageous characters, the assembled three-electrode supercapacitor displayed high specific capacitances of 391 F g-1at the current density of 0.5 A g-1and good rate capability of 73.6% capacitance retention at 20 A g-1in 6 mol L-1KOH electrolyte. Furthermore, the assembled zinc ion capacitor still revealed outstanding capacitance of 335 F g-1at 0.1 A g-1, excellent cycling stability of 92.2% capacitance retention after 10 000 cycles and ultra-high energy density of 150.3 Wh kg-1at power density of 90 W kg-1in 3 mol L-1ZnSO4electrolyte. It is believed that the current work provides a facile and effective strategy to recycle PET waste into high-valuable MOF, and further expands the applications of MOF-derived carbons for high-performance energy storage devices, so it is conducive to both pollution alleviation and sustainable economic development.

关键词： PET Recycling Porous carbon Supercapacitor Energy storage

Highly sensitive CO_(2)-LITES sensor based on a self-designed low-frequency quartz tuning fork and fiber-coupled MPC

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Chinese Optics Letters 2024年第7期22卷 105-110页

作者： Jinfeng Hou Xiaonan Liu Yahui Liu Ying He Weijiang Zhao Yufei Ma national Key Laboratory of science and technology on Tunable Laser Harbin Institute of TechnologyHarbin 150001China

A highly sensitive carbon dioxide(CO_(2))sensor based on light-induced thermoelastic spectroscopy(LITES)utilizing a selfdesigned low-frequency quartz tuning fork(QTF)and a fiber-coupled multipass cell(MPC)is reported in this *** QTF with a low resonant frequency of 8675 Hz and a high Q factor of 11,675.64 was used to improve its energy accumulation time and the sensor’s signal *** MPC with the fiber-coupled structure and optical length of 40 m was adopted to significantly increase the gas absorbance and reduce the optical alignment difficulty as well as improve the robustness of the sensor system.A distributed feedback(DFB),near-infrared diode laser with an emission wavelength of 1.57μm was used as an excitation *** experimental results showed that this CO_(2)-LITES sensor had an excellent linear response to CO_(2) *** minimum detection limitation(MDL)of this CO_(2)-LITES sensor was obtained to be 445.91 ppm,and it could be improved to 47.70 ppm(parts per million)when the integration time of the system reached 500 *** improvement methods for the detection performance of such sensors were also discussed.

关键词： carbon dioxide quartz tuning fork multipass cell light-induced thermoelastic spectroscopy

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Autonomous multi-drone racing method based on deep reinforcement learning

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science China(Information sciences) 2024年第8期67卷 35-48页

作者： Yu KANG Jian DI Ming LI Yunbo ZHAO Yuhui WANG Department of Automation University of Science and Technology of China institute of Advanced technology University of Science and Technology of China institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Racing drones have attracted increasing attention due to their remarkable high speed and excellent maneuverability. However, autonomous multi-drone racing is quite difficult since it requires quick and agile flight in intricate surroundings and rich drone interaction. To address these issues, we propose a novel autonomous multi-drone racing method based on deep reinforcement learning. A new set of reward functions is proposed to make racing drones learn the racing skills of human experts. Unlike previous methods that required global information about tracks and track boundary constraints, the proposed method requires only limited localized track information within the range of its own onboard sensors. Further, the dynamic response characteristics of racing drones are incorporated into the training environment, so that the proposed method is more in line with the requirements of real drone racing scenarios. In addition, our method has a low computational cost and can meet the requirements of real-time racing. Finally, the effectiveness and superiority of the proposed method are verified by extensive comparison with the state-of-the-art methods in a series of simulations and real-world experiments.

关键词： racing drone autonomous multi-drone racing sim-to-real deep reinforcement learning Markov game

Porous organic cages as a novel platform for second harmonic generation

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science China Chemistry 2024年第11期67卷 3669-3674页

作者： Feng Shui Yunqin Zhang Mao Yi Xiongli Liu Lin Li Shuo Zhang Yongshen Zheng Yongtao Yao Qiao Zhao Baiyan Li Xianhe Bu School of Materials science and Engineering National Institute for Advanced Materials TKL of Metal and Molecule-Based Material Chemistry Nankai University national Key Laboratory of science and technology on Advanced Composites in Special Environments Harbin Institute of Technology

Second harmonic generation(SHG) is one of the most extensively applied nonlinear optical phenomena. Compared to traditional inorganic SHG materials, organic SHG materials, including non-centrosymmetric small molecular crystals and organic polymers, have been extensively explored for SHG optics due to their advantageous properties, including high light-induced damage threshold, ultrafast response speed, high polarization ratio, wide transparency range, and elevated dielectric constant. However,in organic SHG materials, most small molecular crystals often show poor thermal stability(<200 °C) due to their low molecular weight, which is an important obstacle for practical application under high temperatures. On the other hand, the difficulty in the growth of large-size crystals as well as the disorderly array of chromospheres on polymer chains associated with organic polymers have hindered their widespread application in SHG due to the requirements of processability and ***, it is significantly necessary to develop novel organic SHG material with high thermal stability, large-size crystals,excellent processability, high homogeneity, and a well SHG effect. In the contribution, we developed herein porous organic cages(POCs) as a novel platform for SHG optics. Thanks to its inherent macromolecular composition and zero-dimensional discrete structures, POCs can not only solve the instability problem of small molecule crystals but also overcome the drawbacks in growing large-size crystals for organic polymer. The obtained two POCs with chiral asymmetric centers(CPOC-R-5 and CPOCS-7) display advantageous features for SHG optics including well SHG performance, large-size crystal(5 mm×3 mm×1 mm),high thermal stability(≥250 °C), wide transparency window(750–2,000 nm) and high polarization ratio(up to 94.5%). This work thus develops POCs as a new platform toward the construction of organic NLO materials with the potential application in sorts of SHG optics.

关键词： porous organic cages second harmonic generation novel SHG platform high thermal stability large-size single crystal

Memory-enhanced text style transfer with dynamic style learning and calibration

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science China(Information sciences) 2024年第4期67卷 181-196页

作者： Fuqiang LIN Yiping SONG Zhiliang TIAN Wangqun CHEN Diwen DONG Bo LIU College of Computer science and technology National University of Defense Technology Department of Computer science and Engineering The Hong Kong University of Science and Technology Strategic Assessments and Consultation institute Academy of Military Sciences

Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content. As a controllable text generation task, mainstream approaches use content-independent style embedding as control variables to guide stylistic generation. Nonetheless, stylistic properties are contextsensitive even under the same style. For example, “delicious” and “helpful” convey positive sentiments,although they are more likely to describe food and people, respectively. Therefore, desired style signals must vary with the content. To this end, we propose a memory-enhanced transfer method, which learns fine-grained style representation concerning content to assist transfer. Rather than employing static style embedding or latent variables, our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations. The style signal is dynamically retrieved from memory using the content as a query, providing a more expressive and flexible latent style space. To address the imbalance between quantity and quality in different content, we further introduce a calibration method to augment memory construction by modeling the relationship between candidate *** results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches. The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.

关键词： style transfer memory-enhanced method text generation deep learning text representation

Deep Guided Attention Network for Joint Denoising and Demosaicing in Real Image

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Chinese Journal of Electronics 2024年第1期33卷 303-312页

作者： Tao ZHANG Ying FU Jun ZHANG School of Computer science and technology Beijing Institute of Technology Advanced Reasearch institute of Multidisciplinary science Beijing Institute of Technology

Denoising(DN) and demosaicing(DM) are the first crucial stages in the image signal processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint manner, which is an extremely undetermined inverse problem. Existing deep learning methods learn the desired prior on synthetic dataset, which limits the generalization of learned network to the real world data. Moreover, existing methods mainly focus on the raw data property of high green information sampling rate for DM, but occasionally exploit the high intensity and signalto-noise(SNR) of green channel. In this work, a deep guided attention network(DGAN) is presented for real image joint DN and DM(JDD), which considers both high SNR and high sampling rate of green information for DN and DM, respectively. To ease the training and fully exploit the data property of green channel, we first train DN and DM sub-networks sequentially and then learn them jointly, which can alleviate the error accumulation. Besides, in order to support the real image JDD, we collect paired raw clean RGB and noisy mosaic images to conduct a realistic dataset. The experimental results on real JDD dataset show the presented approach performs better than the state-of-the-art methods, in terms of both quantitative metrics and qualitative visualization.

关键词： Training Visualization Inverse problems Green products Noise reduction Pipelines Signal processing