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Thermally modulated photoelectronic synaptic behavior in HfS_(2)/VO_(2) heterostructure

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Rare Metals 2024年第8期43卷 3798-3809页

作者： Le Wang Lin Wang Xiao-Yun Ye Xiong-Hu xu Li-yan Shang ya-wei Li Jin-Zhong Zhang Liang-Qing Zhu Zhi-Gao Hu Technical Center for Multifunctional Magneto-Optical Spectroscopy(Shanghai) Engineering Research Center of Nanophotonics&Advanced Instrument(Ministry of Education)Department of PhysicsSchool of Physics and Electronic ScienceEast China Normal UniversityShanghai 200241China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China

Neuromorphic computing is known for its efficient computational speed,low latency,and reduced power consumption,which is considered a pivotal technology to overcome the von Neumann *** synapses are an indispensable component of neuromorphic computational artificial neural *** guarantee effective and precise processing of optical signals,it must have a high responsivity,detectivity,and the ability to adapt to various ***,a synaptic transistor based on the HfS_(2)/VO_(2) heterojunction with a responsivity of8.6×10^(3) A·W^(-1)and a detectivity of 1.26×10^(14)Jones at405 nm laser was ***,the typical synaptic behavior was successfully simulated,including postsynaptic currents(PSCs),the transition from shortterm plasticity(STP)to long-term plasticity(LTP).When VO_(2) converts from the semiconductor state to the metal state,the HfS_(2)/VO_(2) heterojunction transforms into a Schottky heterojunction from a TypeⅡheterojunction with ***'s important,the heterojunction still exhibits excellent responsivity and detectivity,as well as stability of synaptic *** addition,the classical Pavlovian conditioning experiment is simulated under different laser intensity to study the brain's associative learning *** results demonstrate that the HfS_(2)/VO_(2) heterojunction synapse exhibits significant responsivity and detectivity and is adaptable to high-temperature environments,showing great potential for neuromorphic computational applic ations.

关键词： HfS_(2) VO_(2) Phase transition Photoelectric synapse Heterojunction

Origin of condensate oil and natural gas in Bozhong 19-6 gas field,Bohai Bay Basin

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Energy Geoscience 2024年第1期5卷 54-62页

作者： Jianyong xu wei Li CNOOC Research Institute Co.Ltd. Beijing100028China

The discovery of the Bozhong 19-6 gas field has opened a new frontier for deep gas exploration in the Bohai Bay Basin,with a great potential for further gas ***,poor understanding of oil and gas origin has been limiting the exploration progress in this *** clarify the origin of condensate oil and gas in Bozhong 19-6 gas field,this study adequately utilized the organic geochemical analysis data to investigate the composition and geochemical characteristics of condensate oil and natural gas,and analyzed the relationship between condensate oil and the three sets of source rocks in the nearby *** show that the lighter components dominate the condensate oil,with a forward type *** parent material of crude oil was primarily deposited in a shallow,clay-rich,low-salinity,weakly reducing aquatic *** condensate and natural gas have similar parent source characteristics and maturity,with Ro ranging from 1.4%to 1.6%.Both are products of high maturity stage,indicating that they are hydrocarbon compounds produced by the same group of source rocks in the same ***-sources correlation shows that condensate oil and gas mainly originate from the source rocks of the third member of Shahejie Formation in the nearby subsags of the Bozhong 19-6 structural belt.

关键词： Bozhong Sag Natural gas Condensate oil Light hydrocarbon Gas-source correlation Oil-source correlation

Fast source mask co-optimization method for high-NA EUV lithography

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Opto-Electronic Advances 2024年第4期7卷 44-54页

作者： Ziqi Li Lisong Dong xu Ma yayi wei EDA Center Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029China Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China University of Chinese Academy of Sciences Beijing 100049China Guangdong Greater Bay Area Applied Research Institute of Integrated Circuit and Systems Guangzhou 510700China

Extreme ultraviolet(EUV)lithography with high numerical aperture(NA)is a future technology to manufacture the integrated circuit in sub-nanometer ***,source mask co-optimization(SMO)is an extensively used approach for advanced lithography process beyond 28 nm technology *** work proposes a novel SMO method to improve the image fidelity of high-NA EUV lithography system.A fast high-NA EUV lithography imaging model is established first,which includes the effects of mask three-dimensional structure and anamorphic ***,this paper develops an efficient SMO method that combines the gradient-based mask optimization algorithm and the compressivesensing-based source optimization algorithm.A mask rule check(MRC)process is further proposed to simplify the optimized mask *** illustrate that the proposed SMO method can significantly reduce the lithography patterning error,and maintain high computational efficiency.

关键词： computational lithography high-NA EUV lithography source-mask co-optimization lithography imaging model

Gas–solid reactor optimization based on EMMS-DPM simulation and machine learning

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Particuology 2024年第6期89卷 131-143页

作者： Haolei Zhang Aiqi Zhu Ji xu wei Ge State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China

Design,scaling-up,and optimization of industrial reactors mainly depend on step-by-step experiments and engineering experience,which is usually time-consuming,high cost,and high *** numerical simulation can reproduce high resolution details of hydrodynamics,thermal transfer,and reaction process in reactors,it is still challenging for industrial reactors due to huge computational *** this study,by combining the numerical simulation and artificial intelligence(AI)technology of machine learning(ML),a method is proposed to efficiently predict and optimize the performance of industrial reactors.A gas–solid fluidization reactor for the methanol to olefins process is taken as an example.1500 cases under different conditions are simulated by the coarse-grain discrete particle method based on the Energy-Minimization Multi-Scale model,and thus,the reactor performance data set is *** develop an efficient reactor performance prediction model influenced by multiple factors,the ML method is established including the ensemble learning strategy and automatic hyperparameter optimization technique,which has better performance than the methods based on the artificial neural ***,the operating conditions for highest yield of ethylene and propylene or lowest pressure drop are searched with the particle swarm optimization algorithm due to its strength to solve non-linear optimization *** show that decreasing the methanol inflow rate and increasing the catalyst inventory can maximize the yield,while decreasing methanol the inflow rate and reducing the catalyst inventory can minimize the pressure *** two objectives are thus conflicting,and the practical operations need to be compromised under different circumstance.

关键词： Discrete particle method Artificial intelligence Machine learning Particle swarm optimization Industrial reactor optimization

Performance analysis and multi-objective optimization based on a modified irreversible Stirling cycle

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Science China(Technological Sciences) 2024年第6期67卷 1668-1684页

作者： xu Lei YU MinJie LIU ZhiChun LIU wei School of Energy and Power Engineering Huazhong University of Science and TechnologyWuhan430074China

The efficiency of the actual Stirling engine is much lower than the ideal Carnot cycle *** obtain more precise efficiency for Stirling engines,this paper proposes a modified Stirling cycle with a more accurate heat transfer process in Stirling engines based on a thermodynamic function called available *** finite-time thermodynamic method is used to analyze the model performance under constant heat source temperature,finite temperature difference heat transfer,and incomplete regenerative processes.A new polytropic process is introduced to model the heat transfer between the working fluid and external heat sources in which only heat above ambient temperature is converted into technical *** regenerator is divided into numerous smaller heat reservoirs with individual temperature to analyze the incomplete regenerative *** expressions of the output power and thermal efficiency are obtained based on the modified irreversible Stirling cycle,and the effects of irreversible losses are analyzed to evaluate the performance of the proposed *** indicate that the efficiency of the modified cycle is much lower than that of the ideal Stirling cycle with an isothermal *** the increase of the average heat transfer temperature difference,there exists an optimum value for the power of the irreversible *** optimum power of the model was obtained for varying thermodynamic parameters by optimizing the average heat transfer temperature difference between the hot and cold *** optimize the irreversible model,the multi-objective optimization analysis is carried out based on NSGA-Ⅱ,which results in an optimized output power of 40.87 kW and an optimized thermal efficiency of 44%.

关键词： stirling cycle regenerative processes isopotential processes multi-objective optimization finite time thermodynamics

3D coarse-grained DPM simulation of the MIP reaction-regeneration loop

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Particuology 2024年第6期89卷 57-66页

作者： yanhao Ye Shuai Zhang Ji xu wei Ge State Key Laboratory of Mesoscience and Engineering(formerly State Key Laboratory of Multiphase Complex Systems) Institute of Process EngineeringChinese Academy of SciencesBeijing100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing100049China

The reactor-regenerator loop is the core facility of the maximizing iso-paraffin(MIP)*** the discrete particle method(DPM)simulation can provide detailed information at the particle scale,it has been unable to simulate such a complex loop system due to limitations of coarse-grained(CG)models,computing software,and *** this study,a newly proposed soft-shell CG-DPM model with a CG ratio of up to 800 is used to simulate a 3.5 Mt/a industrial-scale MIP reactor-regenerator *** solid fraction distribution obtained is found to agree well with in-situ *** properties including the distribution of solid fraction,gas and solid velocity,standard derivation of solid fraction with time,temporal distribution of the flow field,and particle residence time distribution are measured in the simulation,which are meaningful to better design and operate such systems in the future.

关键词： Discrete particle method Coarse-grain Maximizing iso-paraffins Full-loop Reaction-regeneration system

Robust Interval State Estimation for Distribution Systems Considering Pseudo-measurement Interval Prediction

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 179-188页

作者： xu Zhang wei yan Meiqing Huo Hui Li the School of Electrical Engineering Chongqing UniversityChongqing 400044China

Interval state estimation(ISE)can estimate state intervals of power systems according to confidence intervals of predicted pseudo-measurements,thereby analyzing the impact of uncertain pseudo-measurements on ***,predicted pseudo-measurements have prediction errors,and their confidence intervals do not necessarily contain the truth values,leading to estimation biases of the *** solve this problem,this paper proposes a pseudo-measurement interval prediction framework based on the Gaussian process regression(GPR)model,thereby improving the prediction accuracy of pseudo-measurement confidence ***,a weight assignment strategy for improving the robustness of weighted least squares(WLS)ISE is *** strategy quantifies the deviation between the pseudo-measurement intervals and their estimated intervals and assigns smaller weights to the pseudo-measurement intervals with larger deviations,thereby improving the estimation accuracy and robustness of the *** paper adopts the data from the supervisory control and data acquisition(SCADA)system of the New York Independent System Operator(NYISO).It verifies the advantages of the GPR method for pseudo-measurement interval prediction by comparing it with the quantile regression and neural network *** addition,this paper demonstrates the effectiveness of the proposed weight assignment strategy through the IEEE 14-bus ***,the differences in the estimation accuracy and the bad data identification between the robust interval state estimation and deterministic state estimation are discussed.

关键词： Interval state estimation interval analysis pseudo-measurement Gaussian process regression(GPR)

Neural network based adaptive nonsingular practical predefined-time fault-tolerant control for hypersonic morphing aircraft

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Chinese Journal of Aeronautics 2024年第4期37卷 421-435页

作者： Shihao xu Changzhu wei Litao ZHANG Rongjun MU School of Astronautics Harbin Institute of TechnologyHarbin 150001China Beijing Institute of Control&Electronics Technology Beijing 100038China

This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of practical predefined-time stability is established. Following the proposed criterion, a tangent function based nonsingular predefined-time sliding manifold and the control strategy are developed. Secondly, the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncertainties. Thirdly, rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time, while all signals in the closed-loop system remain bounded. Finally, numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.

关键词： Hypersonic morphing aircraft(HMA) Neural network(NN) Adaptive control Practical predefined-time control Fault-tolerant control

CO2-Induced Modulation of Si-O Bonds for Low Temperature Plastic Deformation of Amorphous Silica Nanoparticles with Enhanced Photoluminescence

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Energy & Environmental Materials 2024年第4期7卷 404-412页

作者： Kang Huang Wenzhuo Wu Song xu Pengfei yan Zhongming wei Qun xu Henan Institute of Advanced Technology Zhengzhou University College of Materials Science and Engineering Zhengzhou University State Key Laboratory of Superlattices and Microstructures Institute of Semiconductors Chinese Academy of Sciences

Modulation of Si-O bonds under mild conditions has been a challenging issue in the field of material science,which is critical to manufacture highperformance silica-based optical and photonic ***,we introduce a nondestructive technique to achieve Si-O bond rearrangement,leading to plastic deformation and photoluminescence enhancement of amorphous silica nanoparticles using supercritical carbon dioxides in EtOH/H2O solution under mild temperature.

关键词： amorphous silica anisotropic stress photoluminescence plastic deformation supercritical CO2