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Plasmonic nanolaser with tunable emitting wavelength near 1 µm

Optics Letters 2025年第10期50卷 3305-3308页

作者： Yuhua Wang Shudi Lu Jingteng Ma Runkang Lin Peiling Wang Yipeng Xu Shizhong Yue Zhijie Wang Shengchun Qu Le Huang Kong Liu Huafeng Dong Guangdong Provincial Key Laboratory of Sensing Physics and System Integration Applications School of Physics and Optoelectronic Engineering Guangdong University of Technology Guangzhou 510006 China Laboratory of Solid-State Optoelectronics Information Technology Beijing Key Laboratory of Low Dimensional Semiconductor Materials and Devices Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China College of Physical Science and Technology Hebei Normal University of Science & Technology Qinhuangdao 066004 China huangle@*** liukong@***

Surface plasmon polaritons (SPPs) can produce a confined electromagnetic field near the metal–dielectric interface, allowing energy to be compressed into a scale smaller than the optical diffraction limit. The characteristic enables the fabrication of sub-wavelength-sized, ultra-low-threshold, ultrafast, specific polarization, room-temperature lasing nanolasers, which is especially meaningful for the lasers emitting long wavelength light. In this work, we developed a Cs 0.1 MA 0.9 SnI 3 perovskite plasmonic laser based on a metal–insulator–semiconductor (MIS) structure, demonstrating a low threshold of 281 μJ cm −2 , a tunable emitting wavelength from 973 to 1023 nm, strong mode confinement at the cutoff height of 90 nm, and a rapid response lifetime of 29.43 ps. Our study represents the first, to the best of our knowledge, theoretical design and experimental production of perovskite plasmonic nanolaser with a tunable emitting wavelength near 1 μm, filling a significant research gap and paving the way for the application of perovskite nanolasers in optoelectronic integration and information technology.

关键词： Diffraction limit Effective refractive index Laser arrays Optical limiting Scanning electron microscopy Tunable lasers

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Model-Driven Channel Estimation Network for Orthogonal Time-Frequency Space systems

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IEEE Transactions on Vehicular technology 2025年

作者： Wang, Qian Chen, Xingke Tao, Qin Qian, Li Ping Kam, Pooi-Yuen Wu, Yuan Zhejiang University of Technology Institute of Cyberspace Security Hangzhou310023 China Hangzhou Normal University School of Information Science and Technology Hangzhou311121 China School of Science and Engineering Shenzhen518172 China Center for Advanced Microelectronic Devices Suzhou215123 China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science China

Orthogonal time-frequency space (OTFS) modulation has garnered significant attention in wireless communications, particularly in high-mobility scenarios, due to its exceptional resilience to Doppler shifts. While the delay- Doppler domain channel estimation is mostly considered for reliable communication, it is often hindered by fractional Doppler shifts in complex channel conditions. To overcome this challenge, this paper proposes a model-driven channel estimation network (CENet) for accurate channel estimation in the delay-time (DT) domain, with the initial least-squares (LS) solutions as prior information for training. Specifically, a LS-driven CENet with parallel structure is proposed to efficiently handle the high-dimensional DT domain channel matrix, which enables the row- wise training and estimation with fast convergence. Simulation results demonstrate that our proposed CENet significantly outperforms the conventional LS and deep neural network-based methods. © 1967-2012 IEEE.

关键词： Least squares approximations

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Enhanced Pyroelectric Response in Quenched BNT-Based Lead-Free Ferroelectrics for Uncooled Infrared Detection

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Advanced Functional Materials 2025年

作者： Shen, Meng Zhang, Xian Cen, Fangjie Zhang, Qingfeng Zhang, Haibo Zhang, Guangzu Jiang, Shenglin Chen, Yong Hu, Yongming Yao, Kui Hubei Key Laboratory of Micro-Nanoelectronic Materials and Devices Key Laboratory of Intelligent Sensing System and Security of Ministry of Education and School of Microelectronics Hubei University Wuhan430062 China School of Integrated Circuits Engineering Research Center for Functional Ceramics MOE and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Ministry of Education Key Laboratory of Green Preparation and Application for Functional Materials Hubei Key Laboratory of Micro-Nanoelectronic Materials and Devices Hubei Key Laboratory of Polymer Materials School of Materials Science & Engineering Hubei University Wuhan430062 China School of Materials Science and Engineering State Key Laboratory of Material Processing and Die & Mould Technology Huazhong University of Science and Technology Wuhan430074 China Singapore138634 Singapore

Excellent pyroelectric performance in environmentally friendly lead-free ferroelectrics is highly demanded for uncooled infrared detector. However, the trade-off between room temperature pyroelectric coefficient (proom) and depolarization temperature (Td) remains a major challenge of lead-free ferroelectrics for their device applications. Herein, a superior proom of 13.8 × 10−4 C m−2 K−1 with high Td of 155 °C is achieved in quenched BNT-Fe/Mn-NBT sample. Oxygen vacancy engineering is proposed to solve the constraint between proom and Td in BNT-based ceramics. The local A/B site displacement and oxygen vacancies are constructed in the BNT-Fe/Mn-NBT perovskite structure by quenching treatment, resulting in larger lattice distortion and superior proom. Meanwhile, defect-induced inhomogeneous random field compensates the ferroelectric depolarization field and down-shifts the free energy well, maintaining high Td. The resulting pyroelectric infrared detector made from the high-performance quenched BNT-Fe/Mn-NBT generates the voltage responsivity of 5906 V W−1 and specific detection rate of 1.8 × 108 cm Hz1/2 W−1, which is comparable to the commercial RD-624 type PZT-based pyroelectric infrared detector. © 2025 Wiley-VCH GmbH.

关键词： Perovskite

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Stacking-, strain-engineering induced altermagnetism, multipiezo effect, and topological state in two-dimensional materials

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Applied Physics Letters 2025年第16期126卷

作者： Xun, Wei Liu, Xin Zhang, Youdong Wu, Yin-Zhong Li, Ping School of Electronic Engineering Jiangsu Vocational College of Electronics and Information Huaian223003 China School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China State Key Laboratory for Mechanical Behavior of Materials Center for Spintronics and Quantum System School of Materials Science and Engineering Xi'an Jiaotong University Shaanxi Xi'an710049 China State Key Laboratory for Surface Physics Department of Physics Fudan University Shanghai200433 China State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University Hangzhou310027 China

Altermagnetism, a recently identified form of unconventional antiferromagnetism (AFM), enables the removal of spin degeneracy in the absence of net magnetization that provides a platform for the low power consumption and ultra-fast device applications. However, a little attention has been paid to the relationship between stacking, strain, and altermagnet, the multipiezo effect, and the topological state. Here, we propose a mechanism to realize the altermagnet, the multipiezo effect, and the topological state in two-dimensional (2D) materials by the stacking and strain engineering. Based on the analysis of symmetry, we find that the spin splitting feature related to the Ut, PTt, M z U t , or M z PTt symmetries in altermagnet multilayers. In addition, we find that the stacking engineering can effectively realize the transform from antiferromagnetism to altermagnetism and semiconductor to metal for the Janus bilayer V2SeTeO. More interestingly, the strain not only induces an intriguing multipiezo effect, encompassing the piezovalley, piezomagnetism, and piezoelectric, but also achieves the abundant topological phase. Our findings offer a generalized direction for manipulating the spin splitting, valley polarization, and topological states, promoting practical application of valleytronic and spintronic devices based on two-dimensional altermagnets. © 2025 Author(s).

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Joint Optimization of Compression, Transmission and Computation for Cooperative Perception Aided Intelligent Vehicular Networks

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IEEE Transactions on Vehicular technology 2025年

作者： Lu, Binbin Huang, Xumin Wu, Yuan Qian, Liping Zhou, Sheng Niyato, Dusit University of Macau State Key Laboratory of Internet of Things for Smart City The Department of Computer and Information Science Macau China Guangdong University of Technology School of Automation Guangzhou510006 China University of Macau State Key Lab of Internet of Things for Smart City Macau China University of Macau State Key Laboratory of Internet of Things for Smart City The Department of Computer Information Science Macau China Zhuhai UM Science and Technology AQ2 Research Institute Zhuhai519301 China Zhejiang University of Technology Institute of Cyberspace Security Hangzhou310023 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Nanyang Technological University School of Computer Science and Engineering Singapore

Cooperative perception is a promising paradigm to tackle the perception limitations of a single intelligent vehicle (IV) to enhance the driving safety and efficiency in intelligent vehicular networks. However, the real-time transmission and computation-intensive fusion of raw sensing data raise new challenges for satisfying the stringent delay requirement of delay-sensitive applications. In this paper, we formulate a joint optimization problem of the cooperative IV selection, compression ratio selection, transmit power control, task offloading decision and computation allocation to minimize the end-to-end delay consisting of compression, transmission and computation. In particular, to meet the perception probability requirement, the quality and quantity-aware matching algorithm is proposed to optimize the cooperative IV selection. To guarantee the queue stability of offloading tasks, we develop the Lyapunov optimization algorithm to determine the upper bound of the offloading tasks and the corresponding optimal computation allocation. The Lyapunov aided deep reinforcement learning algorithm is further proposed to dynamically adjust the task offloading decision and compression ratio selection to minimize the end-to-end delay with the transmit power control being optimized by the successive convex approximation algorithm. Simulation results demonstrate that, compared to several benchmark algorithms, our proposed algorithm achieves the lowest end-to-end delay while guaranteeing the requirements on perception probability and queue stability effectively. © 1967-2012 IEEE.

关键词： Deep reinforcement learning

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A Triangular Stable Node Network based on Self-supervised Learning for personalized prediction

A Triangular Stable Node Network based on Self-supervised Le...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qing Liu Qian Gao Jun Fan Zhiqiang Zhang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China China Telecom Digital Intelligence Techonology Co Ltd Jinan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In recent years, research has illuminated the potency of implicit data processing in enhancing user preferences. Nevertheless, barriers remain in breaking through the constraints of implicit information. This study aims to bridge this gap by firstly constructing a triangular stable node network model, tailored to manage implicit information with precision. Recognizing the challenge of pinpointing novel structures within large-scale graphs, we propose SLTSNN— a triangular stable node network based on self-supervised learning for personalized prediction. SLTSNN innovates by maximizing mutual information between graph-level and patch-level representations, while augmenting graph representations through extended enhanced representations. Additionally, it incorporates triangular data associations and introduces a triangular allocation attention network, which emphasizes strongly correlated preference features among similar users. Furthermore, SLTSNN employs contrastive learning to maximize mutual information between graph vectors and hidden representations, distinguishing between high-order global and local representations. The model’s effectiveness in enhancing user preferences and capturing new graph structures is evidenced by its performance on hit rate and normalized discounted cumulative gain metrics across three datasets.

关键词： Measurement Bridges Contrastive learning Signal processing Data processing Vectors Space exploration Resource management Speech processing Mutual information

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Unveiling and advancing grassland degradation research using a BERTopic modelling approach

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Journal of Integrative Agriculture 2025年第3期24卷 949-965页

作者： Tong Li Lizhen Cui Yu Wu Rajiv Pandey Hongdou Liu Junfu Dong Weijin Wang Zhihong Xu Xiufang Song Yanbin Hao Xiaoyong Cui Jianqing Du Xuefu Zhang Yanfen Wang School of Agriculture and Food Sustainability The University of QueenslandSt Lucia 4072Australia College of Life Sciences University of Chinese Academy of SciencesBeijing 100049China Agricultural Information Institute Chinese Academy of Agricultural SciencesBeijing 100081China Indian Council of Forestry Research&Education Dehradun 248006India Centre for Planetary Health and Food Security School of Environment and ScienceGriffith UniversityNathanBrisbane 4111Australia Institute of Marine Science and Technology Shandong UniversityQingdao 264209China National Science Library Chinese Academy of SciencesBeijing 100190China Department of Information Resources Management School of Economics and ManagementUniversity of Chinese Academy of SciencesBeijing 100190China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Tibetan Plateau Earth System Science(LATPES) Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China

Grassland degradation presents overwhelming challenges to biodiversity,ecosystem services,and the socioeconomic sustainability of dependent ***,a comprehensive synthesis of global knowledge on the frontiers and key areas of grassland degradation research has not been achieved due to the limitations of traditional scientometrics *** present synthesis of information employed BERTopic,an advanced natural language processing tool,to analyze the extensive ecological literature on grassland *** compiled a dataset of 4,504 publications from the Web of science core collection database and used it to evaluate the geographic distribution and temporal evolution of different grassland types and available knowledge on the *** analysis identified key topics in the global grassland degradation research domain,including the effects of grassland degradation on ecosystem functions,grassland ecological restoration and biodiversity conservation,erosion processes and hydrological models in grasslands,and *** BERTopic analysis significantly outperforms traditional methods in identifying complex and evolving topics in large datasets of *** to traditional scientometrics analysis,BERTopic provides a more comprehensive perspective on the research areas,revealing not only popular topics but also emerging research areas that traditional methods may overlook,although scientometrics offers more specificity and ***,we argue for the simultaneous use of both approaches to achieve more systematic and comprehensive assessments of specific research *** study represents an emerging application of BERTopic algorithms in ecological research,particularly in the critical research focused on global grassland *** also highlights the need for integrating advanced computational methods in ecological research in this era of data *** like the BERTopic algorithm are essential for enhancing our understandin

关键词： natural language processing grassland degradation knowledge synthesis scientometrics systematic review

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Characteristics of boreal summer compound hot-drought events in the Yangtze River Valley and relationships with Indian Ocean Sea surface temperature

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Climate Dynamics 2025年第5期63卷 1-17页

作者： Zhang, Yifang An, Xuehua Sun, Shanlei Ma, Qianrong Yan, Pengcheng Zhou, Botao State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing 210044 China State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China College of Physical Science and Technology Yangzhou University Yangzhou 225012 China Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province/Key Laboratory of Arid Climatic Change and Reducing Disaster of China Meteorological Administration Institute of Arid Meteorology of China Meteorological Administration Lanzhou 730030 China

Compound hot-drought events (CHDEs) have drawn widespread attention for their severe impacts on ecosystems and human livelihoods. This study investigated the characteristics and driving mechanisms of boreal summer CHDEs in the Yangtze River Valley (YRV) during 1961–2022. Results showed that the most intense events were concentrated in Sichuan Province, with both the affected area and event severity exhibiting significant upward trends during the study period. A strong relationship was identified between CHDEs in the YRV and sea surface temperature (SST) anomalies in the Indian Ocean, independent of El Niño-Southern Oscillation (ENSO) influences. Cold SST anomalies cooled the tropical troposphere, triggering easterly winds over East Asia subtropical regions. Concurrently, increased precipitation over north-central India induced an upper-tropospheric anticyclone over the northwestern Tibetan Plateau. In turn, the propagated Rossby waves promoted anticyclonic conditions over East Asia and maintained a meridional dipole circulation pattern. Anomalous high-pressure systems over the North Atlantic and Europe-West Siberia amplified these patterns, which further altered surface radiation budgets, drying the land and enhancing sensible heat flux. The resulting land-atmosphere interaction sustained anticyclonic circulation, intensifying CHDEs in the YRV. Projections under the different warming scenarios suggested that the frequency of these atmospheric circulation patterns was likely to increase, exacerbating CHDEs in the YRV and posing heightened risks to the environment and society. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Atmospheric circulation Compound hot-drought events Flow analog Indian Ocean Yangtze River Valley

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Geometry-Based Stochastic MIMO Channel Model for Near-Field and Far-Field Scenarios of Integrated Sensing and Communications

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IEEE Transactions on Vehicular technology 2025年

作者： Jin, Yunwei He, Ruisi Ai, Bo Yuan, Yuan Niu, Yong Zhang, Haoxiang Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation School of Electronics and Information Engineering Frontiers Science Center for Smart High-speed Railway System Beijing100044 China Ministry of Industry and Information Technology China Academy of Industrial Internet Beijing100804 China

Integrated sensing and communication (ISAC) has become a promising technology in current sixth-generation (6G) wireless communications due to its ability to support both communication and sensing. Existing works regarding ISAC channels mainly focus on far-field propagation conditions based on plane wave assumption. However, with the deployment of ultra-massive multiple-input multiple-output (MIMO), the far-field assumption may no longer hold, as the communication and sensing propagation distances distances may be comparable to the array aperture size. To address this issue, we propose a three-dimensional MIMO channel model that simultaneously considers near-field and far-field propagation conditions in ISAC environments. Additionally, we distinguish the communication and sensing propagation environments by employing different effective scatterer distributions. In the model, the sensing channel is divided into target sensing and environmental sensing components, whereas the communication channel is divided into line-of-sight and non-line-of-sight components. The weighted sum of each component in communication and sensing channels results in accurate channel representations. Based on the proposed model, we derive and thoroughly investigate space-time-frequency correlation function, normalized absolute error function, and channel capacity. A key observation is that the channel correlation strongly depends on scatterer distribution. In certain conditions, the sensing channel can effectively capture the behavior of the communication channel. Error function results indicate that the proposed channel model achieves fairly high accuracy in ultra-massive MIMO scenarios. These findings provide essential support for the development of ISAC systems in future 6G wireless communications. © 1967-2012 IEEE.

关键词： Stochastic systems

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Privacy-Preserving IoT Image Transmission: Multi-Stage SVD Data Embedding and Heatmap Alignment

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IEEE Internet of Things Journal 2025年

作者： Du, Kaixin Ma, Bin Yang, Meihong Wang, Xiaoyu Li, Xiaolong Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250101 China Beijing Jiaotong University School of Computer and Information Technology Beijing100044 China

The images transmitted by IoT devices, particularly those used for surveillance or sensor data, are vulnerable to malicious screenshots and unauthorized access, leading to potential privacy breaches. To address this, we propose a multi-stage Singular Value Decomposition (SVD)-based robust data-hiding scheme for JPEG images aimed at mitigating screenshot attacks. The method exploits the decorrelation properties of the Discrete Cosine Transform (DCT) to preprocess the carrier image, facilitating the selection of specific frequency coefficients. These coefficients undergo a dual-stage SVD transformation, where dimensionality reduction reduces the impact of noise from non-critical image regions. Additionally, we optimize Grad-CAM heatmap generation to better align with human visual perception, enabling the identification of stable and reliable feature regions for embedding secret information. This approach ensures that the visual integrity of the carrier image is maintained while preserving the legibility of the embedded information, even under *** method enhances both the visual fidelity of the carrier image and the robustness of the embedded information. Experimental results demonstrate that the proposed scheme outperforms existing methods, achieving at least a 5% improvement in confidential information extraction accuracy and a data extraction rate exceeding 95% across screenshot angles ranging from -40∘ to 40∘. Extensive evaluations confirm the superior performance, efficiency, and security of our method in mitigating screenshot attacks, showcasing its broad applicability to various image formats and resilience to distortions. © 2014 IEEE.

关键词： Discrete cosine transforms

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