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Realization of one-dimensional 2^(n)-root topological states in photonic lattices

Science China(Technological Sciences) 2024年第1期67卷 98-104页

作者： WEI RuiShan ZHANG QingLong yang DanDan HUANG XiongJian PAN QiWen KANG Juan QIU JianRong yang zhongmin DONG GuoPing State Key Laboratory of Luminescent Materials and Devices and Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied TechniquesGuangdong Engineering Technology Research and Development Center of Special Optical Fiber Materials and DevicesSchool of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510640China School of Physics and Optoelectronics South China University of TechnologyGuangzhou 510640China State Key Laboratory of Modern Optical Instrumentation College of Optical Science and EngineeringZhejiang UniversityHangzhou 310027China

Square-root topological insulators recently discovered are intriguing topological phases.They possess topological properties inherited from the squared Hamiltonian and exhibit double-band structures.The mechanism of the square root was generalized to 2^(n)-root topological insulators,giving rise to more band gaps.In this study,we describe the experimental realization of onedimensional 2^(n)-root topological insulators in photonic waveguide arrays using the archetypical Su-Schrieffer-Heeger(SSH)model.Topological edge states with tunable numbers are clearly observed under visible light.In particular,we visualized the dynamic evolutions of the light propagation by varying the sample lengths,which further proved the localization and multiple numbers of edge states in 2^(n)-root topological systems.The experiment,which involves constructing 2^(n)-root topological photonic lattices in various geometric arrangements,provides a stable platform for studying topological states that exhibit a remarkable degree of flexibility and control.

关键词： 2^(n)-root topological insulators multiple edge states photonic waveguide arrays light dynamics

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Wearable ultrasensitive and rapid human physiological monitoring based on microfiber Sagnac interferometer

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Science China(Information Sciences) 2024年第3期67卷 281-290页

作者： Xin WANG Hongyou ZHOU Meihua CHEN Yongcheng HE Zhishen ZHANG Jiulin GAN zhongmin yang State Key Laboratory Luminescent Materials and Devices Institute of Optical Communication MaterialsSpecial Glass Fiber and Device Engineering Technology Research and Development Center of Guangdong ProvinceGuangdong Provincial Key Laboratory of Fiber Laser Materials and Applied TechniquesSouth China University of Technology Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology Foshan University

High-sensitive and fast-responding flexible strain sensors are essential for the smart wearable devices that precisely and dynamically perceive the weak deformations induced by human physiological signals. Here, a flexible strain sensor via polydimethylsiloxane(PDMS)-encapsulated microfiber Sagnac interferometer was designed and prepared for monitoring the human pulse signals and sound vibrations. The sensor achieved a record-breaking sensitivity(gauge factor, GF = 9977) and an extremely low detection limit(0.00025%) due to the strong polarization-dependent coupling effect in the microfiber coupler and the polarization-mixing effect in the Sagnac loop. The relative intensity demodulation method also enabled a fast response time of 10 μs. The wearable pulse measurements were implemented by attaching this flexible strain sensor directly to human skin at various locations and the waveform details were accurately captured. Taking advantage of the ultra-high sensitivity and fast response performance of the prepared sensor, the real-time dynamic acquisition of the underwater weak signal, such as the hydro-acoustic waves with a wide range of 20 Hz–16.86 k Hz, has been demonstrated. These initial results pave the way for a new and innovative category of underwater wearable devices with rapid detection of human physiological signals and weak environmental vibrations.

关键词： flexible strain sensor microfiber Sagnac interferometer underwater detection

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High performance photodegradation resistant PVA@TiO_(2)/carboxyl-PES self-healing reactive ultrafiltration membrane

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Chinese Journal of Chemical Engineering 2024年第2期66卷 31-39页

作者： Yu Liang Yuanfang Fan zhongmin Su Mingxin Huo Xia yang Hongliang Huo Chi Wang Zhi Geng College of Environment Engineering Research Center of Low-Carbon Treatment and Green Development of Polluted Water in Northeast ChinaMinistry of EducationNortheast Normal UniversityChangchun 130117China School of Science Hainan UniversityHaikou 570225China

The occurrence of ultrafiltration(UF)membrane fouling frequently hampers the sustainable advancement of UF technology.Reactive self-cleaning UF membranes can effectively alleviate the problem of membrane fouling.Nevertheless,the self-cleaning process may accelerate membrane aging.Addressing these concerns,we present an innovative design concept for composite self-healing materials based on self-cleaning UF membranes.To begin,TiO_(2)nanoparticles were incorporated into the polymer molecular structure via molecular design,resulting in the synthesis of TiO_(2)/carboxyl-polyether sulfone(PES)hybrid materials.Subsequently,the nonsolvent-induced phase inversion technique was employed to prepare a novel of UF membrane.Lastly,a polyvinyl alcohol(PVA)hydrogel coating was applied to the hybrid UF membrane surface to create PVA@TiO_(2)/carboxyl-PES self-healing reactive UF membranes.By establishing a covalent bond,the TiO_(2)nanoparticles were effectively and uniformly dispersed within the UF membrane,leading to exceptional self-cleaning properties.Furthermore,the water-absorbing and swelling properties of PVA hydrogel,along with its capacity to form hydrogen bonds with water molecules,resulted in UF membranes with improved hydrophilicity and active self-healing abilities.The results demonstrated that the water contact angle of PVA@5%TiO_(2)/carboxyl-PES UF membrane was 43.1°.Following a 1-h exposure to simulated solar exposure,the water flux recovery ratio increased from 48.16%to 81.03%.Moreover,even after undergoing five cycles of 12-h simulated sunlight exposure,the UF membranes exhibited a consistent retention rate of over 97%,thus fully demonstrating their exceptional self-cleaning,antifouling,and selfhealing capabilities.We anticipate that the self-healing reactive UF membrane system will serve as a pioneering and comprehensive solution for the self-cleaning antifouling challenges encountered in UF membranes while also effectively mitigating the aging effects of reactive UF membranes.

关键词： Ultrafiltration membrane Self-cleaning Self-healing Poly(aryl ether sulfone)

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IoV environment exploring coordination:A federated learning approach

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Digital Communications and Networks 2024年第1期10卷 135-141页

作者： Tong Ding Lei Liu Yi Zhu Lizhen Cui zhongmin Yan School of Software Shandong UniversityJinan250101China

Exploring open fields with coordinated unmanned vehicles is popular in academia and industries.One of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration tasks.However,the coordination of acquiring information from multi-vehicles may risk data privacy.To this end,sharing high-quality experiences instead of raw data has become an urgent demand.This paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more efficiently.Moreover,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'privacy.The numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental methods.The experiments also suggest that the proposed method could support agents without full information to achieve the tasks.

关键词： Internet of vehicle Deep reinforcement learning Federated learning Data privacy

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Small-sized Ni-Co/Mo_(2)C/Co_(6)Mo_(6)C_(2)@C for efficient alkaline and acidic hydrogen evolution reaction by an anchoring calcination strategy

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Frontiers of Chemical Science and Engineering 2024年第5期18卷 95-103页

作者： Jianxia Gu Ying Zhu Haiyan Zheng Chunyi Sun zhongmin Su Department of Chemistry Xinzhou Normal UniversityXinzhou 034000China School of Chemistry Northeast Normal UniversityChangchun 130024China

A novel,cheap and highly efficient Ni-Co/Mo_(2)C/Co_(6)Mo_(6)C_(2)@C nanocomposite has been successfully constructed through simple one-step carbonization method in a nitrogen atmosphere.Polyethyleneimine in the precursor can effectively anchor molybdenum-based Keggin-type polyoxometallate and NiCo-layered double hydroxide through electrostatic and coordination interactions,which avoids the aggregation of catalyst particles during the pyrolysis process.After optimization,the obtained Ni-Co/Mo_(2)C/Co_(6)Mo_(6)C_(2)@C possesses small size(3-8 nm),large specific surface area and hierarchical pore structure.More importantly,Ni-Co/Mo_(2)C/Co_(6)Mo_(6)C_(2)@C presents remarkable hydrogen evolution reaction activity with low overpotentials in 0.5 mol·L^(-1)H_(2)SO_(4)(102.3 mV)and 1 mol·L^(-1)KOH(95 mV)to afford the current density of 10 mA·cm^(-2),as well as small Tafel slopes of 82.49 and 99.92 mV·dec^(-1),respectively.Simultaneously,this catalyst also shows outstanding stability for 12 h without a significant change in current density.The excellent catalytic performance of Ni-Co/Mo_(2)C/Co_(6)Mo_(6)C_(2)@C can put down to the synergistic effect between multiple components and the small size of the catalyst.This work provides unique insights into the preparation of efficient transition metal-based catalysts for HER.

关键词： polyoxometallates layered double hydroxide transition metal-based electrocatalysts hydrogen evolution reaction

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A hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process

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Frontiers of Chemical Science and Engineering 2024年第4期18卷 73-85页

作者： Jibin Zhou Xue Li Duiping Liu Feng Wang Tao Zhang Mao Ye zhongmin Liu National Engineering Research Center of Lower-Carbon Catalysis Technology Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China Yulin Innovation Institute for Clean Energy Clean Energy Innovation Institute of Chinese Academy of SciencesYulin 719053China Xuelang Industrial Intelligence Technology Co. Ltd.Wuxi 214000China

Methanol-to-olefins,as a promising non-oil pathway for the synthesis of light olefins,has been successfully industrialized.The accurate prediction of process variables can yield significant benefits for advanced process control and optimization.The challenge of this task is underscored by the failure of traditional methods in capturing the complex characteristics of industrial processes,such as high nonlinearities,dynamics,and data distribution shift caused by diverse operating conditions.In this paper,we propose a novel hybrid spatial-temporal deep learning prediction model to address these issues.Firstly,a unique data normalization technique called reversible instance normalization is employed to solve the problem of different data distributions.Subsequently,convolutional neural network integrated with the self-attention mechanism are utilized to extract the temporal patterns.Meanwhile,a multi-graph convolutional network is leveraged to model the spatial interactions.Afterward,the extracted temporal and spatial features are fused as input into a fully connected neural network to complete the prediction.Finally,the outputs are denormalized to obtain the ultimate results.The monitoring results of the dynamic trends of process variables in an actual industrial methanol-to-olefins process demonstrate that our model not only achieves superior prediction performance but also can reveal complex spatial-temporal relationships using the learned attention matrices and adjacency matrices,making the model more interpretable.Lastly,this model is deployed onto an end-to-end Industrial Internet Platform,which achieves effective practical results.

关键词： methanol-to-olefins process variables prediction spatial-temporal self-attention mechanism graph convolutional network

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Schottky infrared detectors with optically tunable barriers beyond the internal photoemission limit

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The Innovation 2024年第3期5卷 69-76页

作者： Jintao Fu zhongmin Guo Changbin Nie Feiying Sun Genglin Li Shuanglong Feng Xingzhan Wei Chongqing Institute of Green and Intelligent Technology Chinese Academy of SciencesChongqing 400714China University of Chinese Academy of Sciences Beijing 100049China Chongqing School University of Chinese Academy of SciencesChongqing 400714China

Internal photoemission is a prominent branch of the photoelectric effect and has emerged as a viable method for detecting photons with energies below the semiconductor bandgap.This breakthrough has played a significant role in accelerating the development of infrared imaging in one chip with state-of-the-art silicon techniques.However,the performance of these Schottky infrared detectors is currently hindered by the limit of internal photoemission;specifically,a low Schottky barrier height is inevitable for the detection of low-energy infrared photons.Herein,a distinct paradigm of Schottky infrared detectors is proposed to overcome the internal photoemission limit by introducing an optically tunable barrier.This device uses an infrared absorbing material-sensitized Schottky diode,assisted by the highly adjustable Fermi level of graphene,which subtly decouples the photon energy from the Schottky barrier height.Correspondingly,a broadband photoresponse spanning from ultraviolet to mid-wave infrared is achieved,with a high specific detectivity of 9.83×1010 cm Hz1/2 W−1 at 2,700 nm and an excellent specific detectivity of 7.2×109 cm Hz1/2 W−1 at room temperature under blackbody radiation.These results address a key challenge in internal photoemission and hold great promise for the development of the Schottky infrared detector with high sensitivity and room temperature operation.

关键词： Schottky tunable beyond

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Remote sensing and its applications using GNSS reflected signals:advances and prospects

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Satellite Navigation 2024年第1期5卷 10-51页

作者： Shuanggen Jin Adriano Camps Yan Jia Feng Wang Manuel Martin-Neira Feixiong Huang Qingyun Yan Shuangcheng Zhang Zhongyu Li Komi Edokossi Dongkai yang Zhiyu Xiao zhongmin Ma Weihua Bai Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai200030China School of Surveying and Land Information Engineering Henan Polytechnic UniversityJiaozuo454003China Department of Signal Theory and Communications Technical University of CataloniaBarcelona08034Spain Department of Surveying and Geoinformatics Nanjing University of Posts and TelecommunicationsNanjing210023China School of Electronics and Information Engineering Beihang UniversityBeijing100191China European Space Research and Technology Centre(ESTEC) European Space Agency2200-AGNoordwijkThe Netherlands National Space Science Center Chinese Academy of SciencesBeijing100190China School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and TechnologyNanjing210044China College of Geological Engineering and Geomatics Chang’an UniversityXi’an710054China University of Electronic Science and Technology of China Chengdu611731China

The Global Navigation Satellite Systems(GNSS),including the US’s GPS,China’s BDS,the European Union’s Galileo,and Russia’s GLONASS,offer real-time,all-weather,any-time,anywhere and high precision observations by transmitting L band signals continuously,which have been widely used for positioning,navigation and timing.With the development of GNSS technology,it has been found that GNSS-reflected signals can be used to detect Earth’s surface characteristics together with other signals of opportunity.In this paper,the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry(GNSS-R)in theory,methods,techniques and observations.New developments and progresses in GNSS-R instruments,theoretical modeling,and signal processing,ground and space-/air-borne experiments,parameters retrieval(e.***.wind speed,sea surface height,soil moisture,ice thickness),sea surface altimetry and applications in the atmosphere,oceans,land,vegetation,and cryosphere are given and reviewed in details.Meanwhile,the challenges in the GNSS-R development of each field are also given.Finally,the future applications and prospects of GNSS-R are discussed,including multi-GNSS reflectometry,new GNSS-R receivers,GNSS-R missions,and emerging applications,such as mesoscale ocean eddies,ocean phytoplankton blooms,microplastics detection,target recognition,river flow,desert studies,natural hazards and landslides monitoring.

关键词： GNSS Reflectometry Remote sensing Environmental change

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Transparent nanocrystal-in-glass composite fibers for multifunctional temperature and pressure sensing

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Fundamental Research 2024年第3期4卷 624-634页

作者： Qinpeng Chen Qiwen Pan Shiliang Kang Zhenlu Cai Shengda Ye Puxian Xiong zhongmin yang Jianrong Qiu Guoping Donga State Key Laboratory of Luminescent Materials and Devices and Guangdong Provincial Key Laboratory of Fiber Laser Materials and Applied TechniquesSchool of Materials Science and EngineeringSchool of Physics and OptoelectronicsSouth China University of TechnologyWushan Road 381Tianhe DistrictGuangzhou 510640China Laboratory of Infrared Materials and Devices the Research Institute of Advanced TechnologiesNingbo UniversityFenghua Road 818NingboJiangbei 315211China College of Optical Science and Engineering State Key Laboratory of Modern Optical InstrumentationZhejiang UniversityHangzhou 310027China

The pursuit of compact and integrated devices has stimulated a growing demand for multifunctional sensors with rapid and accurate responses to various physical parameters,either separately or simultaneously.Fluorescent fiber sensors have the advantages of robust stability,light weight,and compact geometry,enabling real-time and noninvasive signal detection by monitoring the fluorescence parameters.Despite substantial progress in fluorescence sensors,achieving multifunctional sensing in a single optical fiber remains challenging.To solve this problem,in this study,we present a bottom-up strategy to design and fabricate thermally drawn multifunctional fiber sensors by incorporating functional nanocrystals with temperature and pressure fluorescence responses into a transparent glass matrix.To generate the desired nanocrystal-in-glass composite(NGC)fiber,the fluorescent activators,incorporated nanocrystals,glassy core materials,and cladding matrix are rationally designed.Utilizing the fluorescence intensity ratio technique,a self-calibrated fiber sensor is demonstrated,with a bi-functional response to temperature and pressure.For temperature sensing,the NGC fiber exhibits temperature-dependent near-infrared emission at temperatures up to 573 K with a maximum absolute sensitivity of 0.019 K−1.A pressure-dependent upconversion emission is also realized in the visible spectral region,with a linear slope of-0.065.The successful demonstration of multifunctional NGC fiber sensors provides an efficient pathway for new paradigms of multifunctional sensors as well as a versatile strategy for future hybrid fibers with novel combinations of magnetic,optical,and mechanical properties.

关键词： Fiber Nanocrystal-in-glass composite Nanocrystals Fluorescence detection Temperature-pressuresensing

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Four decades of full-scale nitrous oxide emission inventory in China

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National Science Review 2024年第3期11卷 137-149页

作者： Minqi Liang Zheyan Zhou Peiyang Ren Han Xiao Xu-Ri zhongmin Hu Shilong Piao Hanqin Tian Qing Tong Feng Zhou Jing Wei Wenping Yuan School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University State Key Laboratory of Tibetan Plateau Earth System Resources and Environment Institute of Tibetan Plateau Research Chinese Academy of Sciences Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province Hainan University Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking University Schiller Institute for Integrated Science and Society Department of Earth and Environmental Sciences Boston College Institute of Energy Environment and Economy Tsinghua University Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)

China is among the top nitrous oxide（N2O）-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade（1980–2020） of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4（1774.8–2799.9） Gg N2O yr-1in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry,energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020,respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture,industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3（290.3–344.1） Gg N2O yr-1in 1980 to 376.2（335.5–407.2） Gg N2O yr-1in 2020. Our study produces a Full-scale Annual N2O dataset in China（FAN2020）, providing emergent counting to refine the current national N2O inventories.

关键词： nitrous oxide four decades anthropogenic sources natural sources

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