检索结果-南通市图书馆

Vector meson's spin alignments in high energy reactions

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 5-20页

作者： Jin-Hui Chen Zuo-Tang Liang Yu-Gang Ma Xin-Li Sheng Qun Wang key laboratory of Nuclear physics and Ion-beam Application (MoE) Institute of Modern PhysicsFudan University Institute of Frontier and Interdisciplinary Science Key Laboratory of Particle Physics and Particle Irradiation (MOE)Shandong University INFN-Firenze Department of Modern physics University of Science and Technology of China School of Mechanics and physics Anhui University of Science and Technology

The global spin alignment of vector mesons has been observed by the STAR collaboration at the Relativistic Heavy Ion Collider （RHIC） at Brookhaven National laboratory （BNL）.It provides a unique opportunity to probe the correlation between the polarized quark and antiquark in the strongly coupled quark-gluon plasma （sQGP） produced in relativistic heavy ion collisions,opening a new window to explore the properties of s *** addition,spin alignments of vector mesons have also been observed in other high-energy particle collisions such as e+e-annihilations at high energies where hadron production is dominated by quark fragmentation *** results obtained are quite different from those obtained in heavy ion collisions where quark coalescence/combination mechanism dominates suggesting strong dependence on hadronization *** comprehensive studies in different hadronization processes are *** this article,we present a brief review of theoretical and experimental advances in the study of vector meson’s spin alignments in a variety of high-energy particle collisions,with emphasis on hadronization mechanisms.

关键词： vector meson spin alignment global polarization relativistic heavy ion collisions fragmentation

Low-cost and fluoride-free synthesis of MFI zeolite nanosheets with enhanced stability for benzene alkylation with ethanol

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 458-468页

作者： Peng Zhu Cun Liu Yiren Yu Guoshu Gao Yumeng Zhao Xiongfu Zhang Guodong Liu Guohui Yang State key laboratory of Fine Chemicals School of Chemical Engineering Dalian University of Technology State key laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Zeolite nanosheets with a short b-axis thickness are highly desirable in lots of catalytic reactions due to their reduced diffusion resistance. Nevertheless, conventional synthesis methods usually require expensive structure-directing agents(SDAs), pricey raw materials, and eco-unfriendly fluorine-containing additives. Here, we contributed a cost-effective and fluoride-free synthesis method for synthesizing high-quality MFI zeolite nanosheets through a Silicalite-1(Sil-1) seed suspension and urea cooperative strategy, only with inexpensive colloidal silica as the Si source. Our approach was effective for synthesizing both Sil-1 and aluminum-containing ZSM-5 nanosheets. By optimizing key synthesis parameters,including seed aging time, seed quantity, and urea concentration, we achieved precise control over the crystal face aspect ratio and b-axis thickness. We also revealed a non-classical oriented nanosheet growth mechanism, where Sil-1 seeds induced the formation of quasi-ordered precursor particles, and the(010)crystal planes of these particles facilitated urea adsorption, thereby promoting c-axis-oriented *** obtained ZSM-5 nanosheets exhibited exceptional catalytic performance in the benzene alkylation with ethanol, maintaining stability for over 500 h, which is 5 times longer than traditional ZSM-5 catalysts. Furthermore, large-scale production of ZSM-5 nanosheets was successfully carried out in a 3 L highpressure autoclave, yielding samples consistent with those from laboratory-scale synthesis. This work marks a significant step forward in the sustainable and efficient production of MFI nanosheets using inexpensive and environmentally friendly raw materials, offering the broad applicability in catalysis.

关键词： Aspect ratio

Fabrication of carbon-supported Al2O3 nanoparticles via spontaneous cross-linking to enhance selective hydrogenation of furfural

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 612-620页

作者： Weiwei Yu Xinbao Zhang Hongyu Chen Yanan Wang Shaoguo Li Fucun Chen Zhenni Liu Xiujie Li Xiangxue Zhu State key laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Selective hydrogenation of furfural to furfuryl alcohol is a great challenge in the hydrogenation field due to thermodynamic preference for hydrogenation of C=C over C=***,a novel Al2O3/C-u hybrid catalyst,composed of N-modified dendritic carbon networks supporting Al2O3nanoparticles,was successfully prepared via carbonizing the freeze-dried gel from spontaneous cross-linking of alginate,Al3+and *** obtained carbon-supported Al2O3hybrid catalyst has a high ratio （31%） of Al species in pentahedral-coordinated *** introduction of urea enhances the surface N content,the ratio of pyrrolic N,and specific surface area of catalyst,leading to improved adsorption capacity of C=O and the accessibility of active *** the furfural hydrogenation reaction with isopropyl alcohol as hydrogen donor,Al2O3/C-u catalyst achieved a 90%conversion of furfural with 98.0% selectivity to furfuryl alcohol,outperforming that of commercial γ-***,Al2O3/C-u demonstrates excellent catalytic stability in the recycling tests attributed to the synergistic effect of abundant weak Lewis acid sites and the anchoring effect of the carbon network on *** work provides an innovative and facile strategy for fabrication of carbon-supported Al2O3hybrid catalysts with rich AlVspecies,serving as a high selective hydrogenation catalyst through MPV reaction route.

关键词： Selective hydrogenation Furfural Furfuryl alcohol Cross-linking Carbon supported Al 2 O 3 MPV route

Local-contrastive-learning machine with both generalization and adversarial robustness: A statistical physics analysis

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 109-123页

作者： Mingshan Xie Yuchen Wang Haiping Huang PMI Lab School of Physics Sun Yat-sen University Guangdong Provincial key laboratory of Magnetoelectric physics and Devices Sun Yat-sen University

Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples. To design a semantically meaningful representation learning, we discard backpropagation, and instead, propose a local contrastive learning, where the representations for the inputs bearing the same label shrink(akin to boson) in hidden layers,while those of different labels repel(akin to fermion). This layer-wise learning is local in nature, being biologically plausible.A statistical mechanics analysis shows that the target fermion-pair-distance is a key parameter. Moreover, the application of this local contrastive learning to MNIST benchmark dataset demonstrates that the adversarial vulnerability of standard perceptron can be greatly mitigated by tuning the target distance, i.e., controlling the geometric separation of prototype manifolds.

关键词： machine learning statistical mechanics adversarial robustness neural networks

Boosting bidirectional sulfur conversion enabled by introducing boron-doped atoms and phosphorus vacancies in Ni2P for lithium-sulfur batteries

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 760-769页

作者： Lin Peng Yu Bai Hang Li Meixiu Qu Zhenhua Wang Kening Sun Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing key laboratory of Chemical Power source and Green Catalysis School of Chemistry and Chemical Engineering Beijing Institute of Technology

Lithium-sulfur （Li-S） batteries have gained great attention due to the high theoretical energy density and low cost,yet their further commercialization has been obstructed by the notorious shuttle effect and sluggish redox ***,we supply a strategy to optimize the electron structure of Ni2P by concurrently introducing B-doped atoms and P vacancies in Ni2P （Vp-B-Ni2P）,thereby enhancing the bidirectional sulfur *** study indicates that the simultaneous introduction of B-doped atoms and P vacancies in Ni2P causes the redistribution of electron around Ni atoms,bringing about the upward shift of d-band center of Ni atoms and effective d-p orbital hybridization between Ni atoms and sulfur species,thus strengthening the chemical anchoring for lithium polysulfides （LiPSs） as well as expediting the bidirectional conversion kinetics of sulfur ***,theoretical calculations reveal that the incorporation of B-doped atoms and P vacancies in Ni2P selectively promotes Li2S dissolution and nucleation ***,the Li-S batteries with Vp-B-Ni2P-separators present outstanding rate ability of 777 m A h g-1at 5 C and high areal capacity of 8.03 mA h cm-2under E/S of 5μL mg-1and sulfur loading of 7.20 mg *** work elucidates that introducing heteroatom and vacancy in metal phosphide collaboratively regulates the electron structure to accelerate bidirectional sulfur conversion.

关键词： Lithium sulfur batteries

Construction of 3D porous Cu_(1.81)S/nitrogen-doped carbon frameworks for ultrafast and long-cycle life sodium-ion storage

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 191-200页

作者： Chen Chen Hongyu Xue Qilin Hu Mengfan Wang Pan Shang Ziyan Liu Tao Peng Deyang Zhang Yongsong Luo key laboratory of Microelectronics and Energy of Henan Province Henan Joint International Research Laboratory of New Energy Storage TechnologyCollege of Physics and Electronic EngineeringXinyang Normal UniversityXinyang 464000China School of physics and Electronic Engineering Nanyang Normal UniversityNanyang 473061China

Transition metal sulfides have great potential as anode mterials for sodium-ion batteries(SIBs)due to their high theoretical specific ***,the inferior intrinsic conductivity and large volume variation during sodiation-desodiation processes seriously affect its high-rate and long-cyde performance,unbeneficial for the application as fast-charging and long-cycling SIBs ***,the three-dimensional porous Cu_(1.81)S/nitrogen-doped carbon frameworks(Cu_(1.81)S/NC)are synthesized by the simple and facile sol-gel and annealing processes,which can accommodate the volumetric expansion of Cu_(1.81)S nanoparticles and accelerate the transmission of ions and electrons during Na^(+)insertion/extraction processes,exhibiting the excellent rate capability(250.6 mA·g^(-1)at 20.0 A·g^(-1))and outstanding cycling stability(70% capacity retention for 6000 cycles at 10.0 A·g^(-1))for ***,the Na-ion full cells coupled with Na_(3)V_(2)(PO_(4))_(3)/C cathode also demonstrate the satisfactory reversible specific capacity of 330.5 mAh·g^(-1)at 5.0 A·g^(-1)and long-cycle performance with the 86.9% capacity retention at 2.0 A·g^(-1)after 750 *** work proposes a promising way for the conversionbased metal sulfides for the applications as fast-charging sodium-ion battery anode.

关键词： copper sulfide nanoparticles porous carbon framework fast charging long-cycle performance sodium-ion full batteries

维普期刊数据库

Quantum public-key crypto via EPR pairs

在线全文

学校读者我要写书评

暂无评论

Science China(physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 58-63页

作者： Xiang-Qun Fu Hong-Wei Li Jian-Hong Shi Tan Li Wan-Su Bao Henan key laboratory of Quantum Information and Cryptography Information Engineering University Synergetic Innovation Center of Quantum Information and Quantum physics University of Science and Technology of China

With the development of quantum computing technology, quantum public-key cryptography is gradually becoming an alternative to the existing classical public-key cryptography. This paper designs a quantum trapdoor one-way function via EPR pairs and quantum measurements. Based on this, a new quantum public-key cryptosystem is presented, which offers forward security,and can resist the chosen-plaintext attack and chosen-ciphertext attack. Compared with the existing quantum public-key cryptos,eavesdropping can be automatically detected in this new quantum public-key cryptosystem under a necessary condition, which is also detailed in the paper.

关键词： quantum public-key crypto trapdoor one-way function EPR pairs

Boosting hydrocarbon conversion via Cu-doping induced oxygen vacancies on CeO2 in CO2 electroreduction

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第1期100卷 66-76页

作者： Lei Xue Tong Shi Chenhui Han Heng Zhang Fenrong Liu Haorun Li Yan Wang Xiaojun Gu Shanghong Zeng Inner Mongolia key laboratory of Chemistry and physics of Rare Earth Materials School of Chemistry and Chemical Engineering Inner Mongolia University State key laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Institute of Catalysis Department of Chemistry Zhejiang University National key laboratory of Baiyunobo Rare Earth Resource Research and Comprehensive Utilization Baotou Research Institute of Rare Earths

Conversion of CO2back to hydrocarbons is the most direct way of closing the“carbon cycle”,and its significance is further enlarged if this process is driven by renewable energies such as ***,precisely controlling the product selectivity towards hydrocarbons against the competitive hydrogen evolution remains challenging,especially for Cu-based ***,we report a novel defect engineering strategy,by which Cu-doping-induced oxygen vacancies on CeO2nanorods were effectively created,with adjustable vacancy/Cu *** resulting optimum catalyst shows up to 79% catalytic current density to hydrocarbons （excluding CO）,with 49% faradaic efficiency to *** and density functional theory unveil that the ratio between oxygen vacancy and Cu affects significantly the formation of*CHO and activation of H2O,which leads to the following deep hydrogenation to *** findings may spur new insights for designing and developing more controllable chemical process relevant to CO2utilization.

关键词： Nanorods

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

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

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