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Overview of in-situ oxygen production technologies for lunar resources

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 233-255页

作者： Youpeng Xu Sheng Pang Liangwei Cong Guoyu Qian Dong Wang Laishi Li Yusheng Wu Zhi Wang College of Materials science and Engineering Shenyang University of TechnologyShenyang 110870China CAS Key Laboratory of Green Process and Engineering National Engineering Research Center for Green Recycling of Strategic Metal ResourcesInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China

The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial ***,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic *** oxygen and metal extraction can be achieved using existing metallurgical ***,the ample reserves of water ice on the Moon offer another means for oxygen *** paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental *** delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar *** two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the *** the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the *** review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.

关键词： lunar resources in-situ oxygen production space metallurgy molten lunar regolith electrolysis

Practical approach for detecting k-nonseparability of multipartite quantum states

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science china(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 32-48页

作者： Jie Guo Jinchuan Hou Xiaofei Qi Kan He College of Mathematics Taiyuan University of Technology School of Mathematics and Statistics Shanxi University Key Laboratory of Complex Systems and Data science of Ministry of Education Shanxi University

The instantaneous detection of entanglement in quantum states poses a significant challenge in the fields of quantum computation and quantum information, and there are no practical methods or tools to complete this task satisfactorily so far. We propose a sufficient and necessary criterion of k-nonseparability for any n-partite finite or infinite dimensional systems, 2 ≤ k ≤ n. This criterion serves as the foundation for a practical scheme designed to detect entanglement and k-nonseparability across multipartite finite-dimensional systems. To exemplify the application of our scheme, we have developed a software tool that facilitates swift and precise identification of entanglement, k-nonseparability, and genuine entanglement within n-qubit systems, specifically tailored for systems with 2 ≤ n ≤ 4.

关键词： multipartite systems entanglement states entanglement witnesses ${\bm~k}$-nonseparability

Influence of introducing Zr,Ti,Nb and Ce elements on externally solidified crystals and mechanical properties of high-pressure die-casting Al–Si alloy

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 147-153页

作者： Junjie Li Wenbo Yu Zhenyu Sun Weichen Zheng Liangwei Zhang Yanling Xue Wenning Liu Shoumei Xiong Center of Materials science and Engineering School of Mechanical and Electronic Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Traffic&Transportation Engineering Central South UniversityChangsha 410075China Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201204China School of Materials science and Engineering Tsinghua UniversityBeijing 100084China

High pressure die casting(HPDC)AlSi10Mn Mg alloy castings are widely used in the automobile *** can optimize the mechanical properties of castings through heat treatment,while the release of thermal stress arouses the deformation of large integrated ***,the development of non-heat treatment Al alloys is becoming the hot *** addition,HPDC contains externally solidified crystals(ESCs),which are detrimental to the mechanical properties of *** achieve high strength and toughness of non-heat treatment die-casting Al-Si alloy,we used AlSi9Mn alloy as matrix with the introduction of Zr,Ti,Nb,and *** influences on ESCs and mechanical properties were systematically investigated through three-dimensional reconstruction and thermodynamic *** results reveal that the addition of Ti increased ESCs'size and porosity,while the introduction of Nb refined ESCs and decreased ***,large-sized Al_3(Zr,Ti)phases formed and degraded the mechanical *** introduction of Ce resulted in the poisoning effect and reduced mechanical properties.

关键词： aluminium alloy high-pressure die-casting externally solidified crystals non-heat treatment

Targets capture by distributed active swarms via bio-inspired reinforcement learning

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science china(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

Interannual variability of boreal summer intraseasonal oscillation over the northwestern Pacific influenced by the Pacific Meridional Mode

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Atmospheric and Oceanic science Letters 2025年第1期18卷 6-11页

作者： Haoyu Zhou Pang-Chi Hsu Lin Chen Yitian Qian Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environmental Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjingChina

During the boreal summer,intraseasonal oscillations exhibit significant interannual variations in intensity over two key regions:the central-western equatorial Pacific(5°S-5°N,150°E-150°W)and the subtropical Northwestern Pacific(10°-20°N,130°E-175°W).The former is well-documented and considered to be influenced by the ENSO,while the latter has received comparatively less attention and is likely influenced by the Pacific Meridional Mode(PMM),as suggested by partial correlation analysis *** elucidate the physical processes responsible for the enhanced(weakened)intraseasonal convection over the subtropical northwestern Pacific during warm(cold)PMM years,the authors employed a moisture budget *** findings reveal that during warm PMM years,there is an increase in summer-mean moisture over the subtropical northwestern *** increase interacts with intensified vertical motion perturbations in the region,leading to greater vertical moisture advection in the lower troposphere and consequently resulting in convective *** a process is pivotal in amplifying intraseasonal convection *** observational findings were further verified by model experiments forced by PMM-like sea surface temperature patterns.

关键词： Boreal summer intraseasonal oscillation Interannual variability Pacific Meridional Mode Moisture budget analysis

MoS_(2)Lubricate‑Toughened MXene/ANF Composites for Multifunctional Electromagnetic Interference Shielding

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Nano-Micro Letters 2025年第2期17卷 358-371页

作者： Jiaen Wang Wei Ming Longfu Chen Tianliang Song Moxi Yele Hao Zhang Long Yang Gegen Sarula Benliang Liang Luting Yan Guangsheng Wang School of Physical science and Engineering Beijing Jiaotong UniversityBeijing 100044People’s Republic of China Key Laboratory of Bio‑Inspired Smart Interfacial science and Technology of Ministry of Education School of ChemistryBeihang UniversityBeijing 100191People’s Republic of China

The design and fabrication of high toughness electromagnetic interference(EMI)shielding composite films with diminished reflection are an imperative task to solve electromagnetic pollution *** MXene/ANF(aramid nanofibers)–MoS_(2)composite films with nacre-like layered structure here are fabricated after the introduction of MoS_(2)into binary MXene/ANF composite *** introduction of MoS_(2)fulfills an impressive“kill three birds with one stone”improvement effect:lubrication toughening mechanical performance,reduction in secondary reflection pollution of electromagnetic wave,and improvement in the performance of photothermal *** the introduction of MoS_(2)into binary MXene/ANF(mass ratio of 50:50),the strain to failure and tensile strength increase from 22.1±1.7%and 105.7±6.4 MPa and to 25.8±0.7%and 167.3±9.1 MPa,*** toughness elevates from 13.0±4.1 to 26.3±0.8 MJ m^(−3)(~102.3%)*** the reflection shielding effectiveness(SE_(R))of MXene/ANF(mass ratio of 50:50)decreases~10.8%.EMI shielding effectiveness(EMI SE)elevates to 41.0 dB(8.2–12.4 GHz);After the introduction of MoS_(2)into binary MXene/ANF(mass ratio of 60:40),the strain to failure increases from 18.3±1.9%to 28.1±0.7%(~53.5%),the SE_(R)decreases~22.2%,and the corresponding EMI SE is 43.9 *** MoS_(2)also leads to a more efficient photothermal conversion performance(~45 to~55℃).Additionally,MXene/ANF–MoS_(2)composite films exhibit excellent electric heating performance,quick temperature elevation(15 s),excellent cycle stability(2,2.5,and 3 V),and long-term stability(2520 s).Combining with excellent mechanical performance with high MXene content,electric heating performance,and photothermal conversion performance,EMI shielding ternary MXene/ANF–MoS_(2)composite films could be applied in many industrial *** work broadens how to achieve a balance between mechanical properties and versatility of composites in the case of high-function fillers.

关键词： MXene-MoS_(2) Lubrication toughening EMI shielding Photothermal conversion Electric heating performance

Rock fracture mechanism of buffer blasting with cushion layer at the borehole bottom

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 325-334页

作者： Xinguang Zhu Chenxi Ding Zhe Sui Hong Su Xu Guo School of Civil and Resources Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Mechanics and Civil Engineering China University of Mining and Technology(Beijing)Beijing 100083China School of Chemical and Blasting Engineering Anhui University of Science and TechnologyHuainan 232001China

This study primarily investigates the rock fracture mechanism of bottom cushion layer blasting and explores the effects of the bottom cushion layer on rock *** involves analyses of the evolution patterns of blasting stress,characteristics of crack distribution,and rock fracture features in the ***,blasting model experiments were carried out using the dynamic caustics principle to investigate the influence of bottom cushion layers and initiation methods on the integrity of the bottom rock *** experimental results indicate that the combined use of bottom cushion layers and inverse initiation effectively protects the integrity of the bottom rock ***,the process of stress wave propagation and dynamic crack propagation in rocks was simulated using the continuum-discontinuum element method(CDEM)and the Landau explosion source model,with varying thicknesses of bottom cushion *** numerical simulation results indicate that with increasing cushion thickness,the absorption of energy generated by the explosion becomes more pronounced,resulting in fewer cracks in the bottom rock *** illustrates the positive role of the cushion layer in protecting the integrity of the bottom rock mass.

关键词： bottom cushion layer blasting crack propagation continuum-discontinuum element method dynamic stress intensity factor

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

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science china(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He Wang Minghui Du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,china

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Atmospheric and Oceanic science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina china Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia