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Microstructure and mechanical performance study of CrMnFeCoNi high-entropy alloys after cryogenic treatment

Materials Science and engineering: A 2025年 942卷

作者： Yulin Qin Liufei Huang Changgui Wu Xiaochong Liang Ling Wang Shilei Li Qungang Kong Xiaoyi Wang Jinfeng Li Longqing Chen Jun Zhu Ming Yin College of Physics Sichuan University Chengdu Sichuan 610065 China Institute of Materials China Academy of Engineering Physics Mianyang 621907 China School of Mechanical Engineering Sichuan University Chengdu 610064 China Southwest Minzu University State Ethnic Affairs Commission Chengdu 610041 China Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu 610064 China

In recent years, significant progress has been made in the development of high-entropy alloys (HEAs) that possess both high strength and high ductility. The application of the metastable engineering strategy to enhance the strength and ductility of materials has also gradually been employed, and cryogenic treatment is one of the important techniques in this regard. Through cryogenic liquid nitrogen treatment, this study significantly enhanced the strength and ductility of (CrMnFeCoNi) 45 Fe 55 and (CrMnFeCoNi) 40 Fe 60 HEAs prepared by laser melting deposition (LMD). Compared to the initial samples, the fracture strength of (CrMnFeCoNi) 45 Fe 55 increased from 480 MPa (at room temperature) to 980 MPa (after cryogenic treatment), and the fracture elongation alloy increased from 60 % (at room temperature) to 62 % (after cryogenic treatment). The fracture strength of (CrMnFeCoNi) 40 Fe 60 alloy increased from 550 MPa (at room temperature) to 1150 MPa (after cryogenic treatment), and the fracture elongation decreased from 55 % (at room temperature) to 45 % (after cryogenic treatment). The reduction in stacking fault energy (SFE) through cryogenic liquid nitrogen treatment enables the formation of stacking faults in the alloy system. These stacking faults act as nucleation sites for phase transformations, encouraging the shift of the matrix from a face-centered cubic (FCC) phase to a body-centered cubic (BCC) phase or other phases. This triggers phase transformation-induced plasticity effects (TRIP). The occurrence of phase transformation was confirmed using in-situ cryo-TEM. Simultaneously, the coexistence of two phases mechanism achieves an advantageous balance between strength and ductility. Our study offers novel insights and methodologies for acquiring high-entropy alloys with exceptional comprehensive mechanical properties.

关键词： Additive manufacturing Cryogenic treatment High-entropy alloys Mechanical properties Microstructure

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Monotone decreasing LKF method for synchronization of heterogeneous nonlinear switched time-delay multi-agent systems with an uncertain target

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Communications in Nonlinear Science and Numerical Simulation 2025年 151卷

作者： Qiao Tong Xinsong Yang Changjun Gu Yaping Sun Housheng Su College of Electronics and Information Engineering Sichuan University Chengdu 610065 China College of Automation Chongqing University of Posts and Telecommunications Chongqing 400065 China Key Laboratory of Imaging Processing and Intelligence Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

This paper investigates the synchronization problem of heterogeneous nonlinear switched time-delay multi-agent systems (MASs) with an uncertain target. Due to the heterogeneous, nonlinear, and switching features, considering different time-delays among agents and unknown inputs on the target poses a huge challenge in achieving synchronization. To solve this challenging issue, a new protocol that incorporates distributed observers, distributed controllers, and a time-varying positive-definite matrix function is designed to estimate the states of the target and compensate for errors among agents. Moreover, by proposing a novel Lyapunov–Krasovskii functional (LKF), this paper not only obtains synchronization criteria but also has an interesting characteristic: the LKF is monotonically decreasing at any time, even at any switching instants. Finally, as some applications, heterogeneous switched Chua’s circuits and flexible-joint robots are given to demonstrate the effectiveness of the proposed new protocol and LKF.

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A Comparative Study on High-Temperature Air and Steam Oxidation of Cr-Coated Zr-4 Alloy Prepared by Multi-Arc Ion Plating

SSRN

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SSRN 2022年

作者： Xiao, Weiwei Liu, Shihong Huang, Jinghao Zou, Shuliang Yu, Hongxing Zhang, Lin Zhang, Kun Huang, Yongchao School of Mechanical Engineering University of South China Hunan Hengyang421001 China Hunan Provincial Key Laboratory of Emergency Safety Technology and Equipment for Nuclear Facilities University of South China Hunan Hengyang421001 China Nuclear Power Institute of China Sichuan Chengdu610213 China Hunan Technical College of Railway High-Speed Hunan Hengyang421001 China

The high-temperature oxidation behavior of Cr-coated Zr-4 alloy in air and steam atmosphere are comparatively studied. The results demonstrate that Cr-coated Zr-4 alloy experiences more severe oxidation in steam atmosphere. This can be attributed to the cyclic redox reactions between Cr and H2O(g), Cr2O3 and H2. Due to the co-reduction effect of H2 and Zr next to the coating, the thickness of Cr2O3 does not increase monotonically with the increase of oxidation time in steam atmosphere. In addition, the reduction reaction of Zr next to the coating caused its own oxidation under prolonged exposure to high temperature steam. © 2022, The Authors. All rights reserved.

关键词： Ion implantation

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Propylammonium Chloride Passivation for Efficient Carbon-Electrode FA 0.1MA 0.9Pbi 3 Solar Cells

SSRN

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SSRN 2024年

作者： Tang, Shaowen Cheng, Nian Huang, Baoting Hang, Fengling Sun, Chuan Zhong, Jun Chen, Mengran Zong, Peng-An Liu, Zhenguo College of Materials Science and Engineering Nanjing Tech University Nanjing211800 China Key laboratory of Flexible Electronics of Zhejiang Provience Ningbo Institute of Northwestern Polytechnical University Ningbo315103 China School of Physics and Optoelectronic Engineering Yangtze University Jingzhou434023 China National Innovation Institute of Defense Technology Academy of Military Sciences of the People’ s Liberation Army of China Beijing100089 China Nuclear Power Institute of China Chengdu610213 China Frontiers Science Center for Flexible Electronics Institute of Flexible Electronics Northwestern Polytechnical University Xi’an710072 China

Carbon-based perovskite solar cells (C-PSCs) are garnering considerable attention in the photovoltaic realm due to their cost-effectiveness, simplified fabrication processes, and improved long-term durability. Nonetheless, their efficiency often suffers from notable non-radiative recombination at the interface of the carbon electrode and the perovskite layer, as well as inherent film defects. This investigation adopts additive engineering to address these challenges by introducing propylammonium chloride (PACl) into FA0.1MA0.9PbI3 perovskite films. The resultant films exhibit larger grain sizes and smoother surface morphology, mitigating grain boundary defects and enhancing interface quality. Additionally, PACl-treated films demonstrate heightened photoluminescence intensity and prolonged carrier lifetimes, effectively suppressing non-radiative recombination. Comparative analysis with control devices showcases a noteworthy efficiency boost in PACl-treated devices, rising from 14.74% to 16.57%, alongside minimal hysteresis effects and exemplary long-term stability. This study presents a simple yet highly efficient approach to enhance film morphology and rectify defects in perovskite films, leading to superior efficiency and stability in HTL-free C-PSCs. © 2024, The Authors. All rights reserved.

关键词： Passivation

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Optimization Control for Flapping Load Mitigation and Output Power Levelling of Wind Turbine

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IFAC-PapersOnLine 2020年第2期53卷 12121-12126页

作者： Chao Peng Jianzou Zou Yan Li Hua Geng Zhenzhen Zhang School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Automation Tsinghua University Beijing 100084 China College of Electrical & Information Engineering Southwest Minzu University Chengdu 610041 China

Fatigue load affects the secure and stability of wind turbine operation. Flapping load is the main source of fatigue load endured by wind turbine operating above the rated wind speed. In this paper, a novel optimization control method for wind turbine flapping load mitigation and output power leveling is proposed. At first, wind turbine flapping load is analyzed and its calculation model is presented. Secondly, principle of the proposed control method is presented. Considering on coupling between flapping load and output power, a multi-objective optimization model and differential evolution based flapping load optimization controller are then designed. Additional PID-based output power leveling controller is employed to keep the output power leveling around the rated power. Finally, the effectiveness of the proposed control method is demonstrated by NREL 5MW wind turbine simulations.

关键词： wind turbine pitch angle flapping load calculation model output power leveling differential evolution algorithm

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Vibration Modelling and the Difference Between Different Vibration Models for a Fewer-DOF Parallel Robot

Research Square

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Research Square 2020年

作者： Fan, Shuai Fan, Shouwen Zhang, Xin Song, Guangkui Lan, Weibin The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan Chengdu610059 China Center for Robotics University of Electronic Science and Technology of China Sichuan Chengdu611731 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China College of Mechanical Engineering Baoji University of Arts and Sciences Shaanxi Baoji721016 China

The accuracy of the vibration model used in the design process directly affects the vibration performance of a parallel robot in practice, which determines the machining accuracy and the surface finish of the manufactured products. Considering a drilling parallel robot with a passive branch and few degrees of freedom as the implementation object, a vibration modelling method is proposed in which Kane’s equation is utilized, and various commonly ignored factors, such as the passive branch, the joint clearances and gravity, are considered. To explore the effects of the passive branch, which was considered ideal in previous studies, two dynamic models are derived in which the passive branch is rigid or flexible. To explore the effects of the joint clearances, which were ignored in previous studies, two stiffness models of branches are derived, in which the joint clearances are considered or ignored. Finally, numerical examples are presented for analysing the effects of these commonly ignored factors on the vibration performance of the drilling parallel robot. Regarding to the effects of these commonly ignored factors, the findings of this paper can serve as a reference for designers in simplifying the vibration model in the design process of parallel robot. © 2020, CC BY.

关键词： Numerical methods

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Determining impact parameters of heavy-ion collisions at low-intermediate incident energies using deep learning with convolutional neural networks

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Physical Review C 2022年第3期105卷 034611-034611页

作者： X. Zhang (张鑫) X. Liu (刘星泉) Y. Huang (黄宇) W. Lin (林炜平) H. Zheng (郑华) R. Wada A. Bonasera Z. Chen (陈志强) L. Chen (陈蕾) J. Han (韩纪锋) R. Han (韩瑞) M. Huang (黄美容) Q. Hu (胡强) Q. Leng (冷强钟) C. W. Ma (马春旺) G. Qu (曲国峰) P. Ren (任培培) G. Tian (田国玉) Z. Xu (徐子虚) Z. Yang (杨振雷) L. Zhang (张丽娜) Key Laboratory of Radiation Physics and Technology of the Ministry of Education Sichuan University Chengdu 610064 China School of Physics and Information Technology Shaanxi Normal University Xi'an 710119 China Cyclotron Institute Texas A&M University College Station Texas 77843 USA Laboratori Nazionali del Sud INFN via Santa Sofia 62 95123 Catania Italy Institute of Modern Physics Chinese Academy of Sciences Lanzhou 730000 China College of Physics and Electronics information Inner Mongolia University for Nationalities Tongliao 028000 China School of Physics Henan Normal University Xinxiang 453007 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu 610213 China School of Information Sciences and Engineering Lanzhou University Lanzhou 730000 China

A deep learning based method with the convolutional neural network (CNN) algorithm for determining the impact parameters is developed by using constrained molecular-dynamics model simulations, focusing on the heavy-ion collisions at the low-intermediate incident energies from several tens to one hundred MeV/nucleon in which the emissions of heavy fragments with the charge numbers larger than three become crucial. To make the CNN applicable in the task of the impact-parameter determination at the present energy range, specific improvements are made in the input selection, the CNN construction, and the CNN training. It is demonstrated from the comparisons of the deep CNN method and the conventional methods with the impact-parameter-sensitive observables that the deep CNN method shows better performance for determining the impact parameters, especially leading to the capability of providing better recognition of the central collision events. With a proper consideration of the experimental filter effect in both training and testing processes to keep consistency with the actual experiments, the good performance of the deep CNN method holds and performs significantly better in terms of predicting the impact parameters and recognizing the central collision events compared with conventional methods, demonstrating the superiority of the present deep CNN method. The deep CNN method with the consideration of the filter effect is applied in the deduction of nuclear stopping power. Higher accuracy for the stopping power deduction is achieved benefitting from the better impact-parameter determination using the deep CNN method, compared with using conventional methods. This result reveals the importance of selecting a reliable impact-parameter-determination method in the experimental deduction of the nuclear stopping power as well as other observables.

关键词： Low & intermediate energy heavy-ion reactions Convolutional neural networks Machine learning nuclear data analysis & compilation

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Searching for neutrino emission from the Cygnus region 38

Searching for neutrino emission from the Cygnus region

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38th International Cosmic Ray Conference, ICRC 2023

作者： Li, Wenlian Huang, Tian-Qi Xu, Donglian He, Huihai Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai201210 China Key Laboratory of Particle Astrophysics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai200240 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China Tianfu Cosmic Ray Research Center Sichuan Chengdu610000 China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Sun Ya

The Cygnus region, which contains massive molecular and atomic clouds and young stars, is a promising Galactic neutrino source candidate. Cosmic rays transport in the region can produce neutrinos and γ-rays. Using ten years of track events detected by the IceCube Neutrino Observatory, we conduct searches for neutrino signals from the Cygnus region with a template method. Four templates, including the CO template, HI template, uniform template, and 2D Gaussian template, are used in this study. No significant emissions are found. We set upper limits for each template, with the resulting upper limit for the CO template being dν/dEν = 6.25 × 10−17(Eν/100TeV)−3TeV−1cm−2s−1 © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Fault diagnosis study for nuclear power plants under imbalanced fault sample datasets based on deep learning

引用

Annals of nuclear Energy 2025年 223卷

作者： Zhanguo Ma Jing Cui Jing Zhang Liang Zhang Wenhao Jia Long Tian School of Automation Harbin University of Science and Technology 150080 Harbin Heilongjiang China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory College of Nuclear Science and Technology Harbin Engineering University 150001 Harbin Heilongjiang China CNNC China Nuclear Power Engineering Co. Ltd 100840 Beijing China NO.703 Research Institute of China State Shipbuilding Company Limited 150078 Harbin Heilongjiang China

The safety of nuclear power plants is crucial, and the situation awareness of the power plant is significantly important for the plant operation during which the fault diagnosis technology plays a key role for the plant state monitoring. Operation of the nuclear power plant is predominantly in a normal state, resulting in a scarcity of fault data. This scarcity leads to imbalanced training data, posing a challenge to the accuracy of fault diagnosis models. This study proposed a fault diagnosis framework that integrates Self-Attention Time-Series Generative Adversarial Networks (SATimeGAN) to augment the training datasets and Convolutional Neural Network-Bidirectional Long Short-Term Memory networks (CNN-BiLSTM) to diagnose the faults, aimed at addressing the data imbalance issue and improving the diagnostic accuracy. Experimental results demonstrate preferable performance of the model in nuclear power plant fault diagnosis, especially in handling imbalance sample fault datasets, compared to traditional CNN, LSTM, and BiLSTM models.

关键词： Convolutional neural network-bidirectional long short-term memory networks Fault diagnosis Self-attention mechanism Time-series generative adversarial networks

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Searching for neutrino signals correlated with LHAASO diffuse Galactic emission 38

Searching for neutrino signals correlated with LHAASO diffus...

引用

38th International Cosmic Ray Conference, ICRC 2023

The diffuse Galactic γ-ray emission is produced from the interaction of cosmic rays and interstellar medium or radiation fields in the Galaxy, where neutrino production is also expected. Recently, the Large High Altitude Air Shower Observatory (LHAASO) reported the measurements of the diffuse γ-ray from the Galactic plane with energies above 10 TeV. In this study, we construct the neutrino emission template based on LHAASO’s observation and search for diffuse neutrinos accompanying the LHAASO diffuse Galactic γ-ray emission using ten-year IceCube track events. No significant signals are found. We set 90% confidence level upper limits, resulting in the neutrino flux of dν/dEν = 1.27 × 10−14(Eν/25TeV)−2.99TeV−1cm−2s−1 for the diffuse γ-ray flux map with a 1.5σ significance cut. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Gamma rays

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