As a representative of non-evaporative getter,Zr-V-Fe has gained widespread attention due to its advantages including low activation temperatures andrapid hydrogen absorption *** this study,we investigated the impact...
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As a representative of non-evaporative getter,Zr-V-Fe has gained widespread attention due to its advantages including low activation temperatures andrapid hydrogen absorption *** this study,we investigated the impact of La and Ce doping on the thermodynamic,kinetic,and activation properties of Zr_(7)V_(5)Fe alloy.X-ray diffraction analysis shows that rare earth doping causes a decrease in the cell volume of both the ZrV_(2) andα-Zr phases of Zr_(7)V_(5)Fe alloy,which results in an increase in the plateau pressure of the *** kinetic curves illustrate that rare earth doping leads to a coarseα-Zr phases and a larger particle size after activation,resulting in a decrease in the hydrogen absorption kinetic *** for the activation process,the rare earth doped alloys exhibit excellent activation with shorter incubation periods.X-ray photoelectron spectroscopy investigations reveal that Zr and V are initially in a highly oxidized *** the heating temperature increases,they undergo a transition from oxidation state to metal *** content of metal Zr in rare earth doped alloys is higher than that in undoped alloys at 250℃,primarily due to rare earth elements'affinity for oxygen.
The integration of artificial intelligence(AI) anddigital twin(dT) technology has revolutionized the industrial Internet of Things(IIoT), enabling advanced automation and intelligent manufacturing [1]. Through sophis...
The integration of artificial intelligence(AI) anddigital twin(dT) technology has revolutionized the industrial Internet of Things(IIoT), enabling advanced automation and intelligent manufacturing [1]. Through sophisticated interactions between physical entities and their virtual counterparts,AI-driven dTs facilitate performance monitoring, analysis,simulation, and optimization of physical assets, enabling predictive maintenance and informeddecision-making [2].
Microstructure,texture,and mechanical properties of the extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy were investigated at different extrusion temperatures(260 and 320℃),extrusion ratios(10:1,15:1,and 30:1),and extrusi...
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Microstructure,texture,and mechanical properties of the extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy were investigated at different extrusion temperatures(260 and 320℃),extrusion ratios(10:1,15:1,and 30:1),and extrusion speeds(3 and 6 mm/s).The experimental results exhibited that the grain sizes after extrusion were much finer than that of the homogenized alloy,and the second phase showed streamline distribution along the extrusion direction(Ed).With extrusion temperature increased from 260 to 320℃,the microstructure,texture,and mechanical properties of alloys changed *** dynamic recrystallization(drX)degree and grain sizes enhanced as the extrusion ratio increased from 10:1 to 30:1,and the strength gradually decreased but elongation(EL)*** the extrusion speed increased from 3 to 6 mm/s,the grain sizes anddrX degree increased significantly,and the samples presented the typical<2111>-<1123>rare-earth(rE)*** alloy extruded at 260℃ with extrusion ratio of 10:1 and extrusion speed of 3 mm/s showed the tensile yield strength(TYS)of 213 MPa and EL of 30.6%.After quantitatively analyzing the contribution of strengthening mechanisms,it was found that the grain boundary strengthening anddislocation strengthening played majorroles among strengthening *** results provide some guidelines for enlarging the industrial application of extruded Mg-rE alloy.
Flexible adaptation to differentiated quality of service(QoS)is quite important for future 6G network with a variety of *** ad hoc networks(MANETs)are able to provide flexible communication services to users through s...
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Flexible adaptation to differentiated quality of service(QoS)is quite important for future 6G network with a variety of *** ad hoc networks(MANETs)are able to provide flexible communication services to users through self-configuration andrapid ***,the dynamic wireless environment,the limitedresources,and complex QoS requirements have presented great challenges for network routing *** by the development of artificial intelligence,a deep reinforcement learning-based collaborative routing(drLCr)algorithm is *** routing policy and subchannel allocation are considered jointly,aiming at minimizing the end-to-end(E2E)delay and improving the network *** sufficient training by the cluster head node,the Q-network can be synchronized to each member node to select the next hop based on local ***,we improve the performance of training by considering historical observations,which can improve the adaptability of routing policies to dynamic *** results show that the proposeddrLCr algorithm outperforms other algorithms in terms of resource utilization and E2E delay by optimizing network load to avoid *** addition,the effectiveness of the routing policy in a dynamic environment is verified.
The accurate characterization of anisotropy for additively manufactured materials is of vital importance for both highperformance structural design and printing processing *** avoid the repetitive andredundant tensil...
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The accurate characterization of anisotropy for additively manufactured materials is of vital importance for both highperformance structural design and printing processing *** avoid the repetitive andredundant tensile testing on specimens prepared along diverse directions,this study proposes an instrumented indentation-based inverse identification method for the efficient characterization of additively manufactured *** the present work,a 3d finite element model of indentation test is first established for the printed material,for which an anisotropic material constitutive model is *** have demonstrated that the indentation responses are information-rich,and material anisotropy along different directions can be interpreted by a single indentation ***,an inverse identification framework is built,in which an Euclidean error norm between simulated and experimental indentation responses is minimized via optimization algorithms such as the Globally Convergent Method of Moving Asymptotes(GCMMA).The developed method has been verified on diverse printed materials referring to either the indentation curve or the residual imprint,and the superiority of this latter over the former is confirmed by a better and faster convergence of inverse *** validations on 3d printed materials(including stainless steel 316L,aluminum alloy AlSi10Mg,and titanium alloy TC4)reveal that the developed method is both accurate andreliable when compared with material constitutive behaviors obtained from uni-axial tensile tests,regardless of the degree of anisotropy among different materials.
Atomic nonlinear interferometry has wide applications in quantum metrology and quantum information *** we propose a nonlinear time-reversal interferometry scheme with high robustness and metrological gain based on the...
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Atomic nonlinear interferometry has wide applications in quantum metrology and quantum information *** we propose a nonlinear time-reversal interferometry scheme with high robustness and metrological gain based on the spin squeezing generated by arbitrary quadratic collective-spin interaction,which could be described by the Lipkin–Meshkov–Glick(LMG)*** optimize the squeezing process,encoding process,and anti-squeezing process,finding that the two particular cases of the LMG model,one-axis twisting and two-axis twisting outperform in robustness and precision,***,we propose a Floquet driving method to realize equivalent time reverse in the atomic system,which leads to high performance in precision,robustness,and *** study sets a benchmark for achieving high precision and high robustness in atomic nonlinear interferometry.
dear Editor,Tracking control in networked environment is a very challenging problem due to the contradiction of rapidresponse to the time-varying signal and the inevitable delay introduced by networks. This letter ha...
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dear Editor,Tracking control in networked environment is a very challenging problem due to the contradiction of rapidresponse to the time-varying signal and the inevitable delay introduced by networks. This letter has proposed several fuzzy-inverse-model-based network tracking control frameworks which are helpful in handling the system with nonlineardynamics and uncertainties.
作者:
Zhiming ChenLSEC
Institute of Computational MathematicsAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China School of Mathematical Science
University of Chinese Academy of SciencesBeijing100049China
In this paper,we prove the H^(2)regularity of the solution to the time-harmonic Maxwell equations with impedance boundary conditions on domains with a C^(2)boundary under minimum regularity assumptions on the source a...
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In this paper,we prove the H^(2)regularity of the solution to the time-harmonic Maxwell equations with impedance boundary conditions on domains with a C^(2)boundary under minimum regularity assumptions on the source and boundary functions.
The infinite-layer cuprate ACu O_(2)(A=Ca,Sr,Ba)possesses the simplest crystal structure among numerous cuprate superconductors and can serve as a prototypical system to explore the unconventional *** on the first-pri...
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The infinite-layer cuprate ACu O_(2)(A=Ca,Sr,Ba)possesses the simplest crystal structure among numerous cuprate superconductors and can serve as a prototypical system to explore the unconventional *** on the first-principles electronic structure calculations,we have studied the electronic and magnetic properties of the infinite-layer cuprate SrCuO_(2)from a phonon *** find that interesting fluctuations of charges,electrical dipoles,and local magnetic moments can be induced by the atomic displacements of phonon modes in SrCuO_(2)upon the hole *** all optical phonon modes of SrCuO_(2)in the antiferromagnetic Néel state,only the A_(1g)mode that involves the full-breathing O vibrations along the Cu-O bonds can cause significant fluctuations of local magnetic moments on O atoms anddramatic charge redistributions between Cu and O ***,due to the atomic displacements of the A_(1g)mode,both the charge fluctuations on Cu and the electrical dipoles on O show a dome-like evolution with increasing hole doping,quite similar to the experimentally observed behavior of the superconducting T_(c);in comparison,the fluctuations of local magnetic moments on O display a monotonic enhancement along with the hole *** analyses indicate that around the optimal doping,there exists a large softening in the frequency of the A_(1g)phonon mode and a van Hove singularity in the electronic structure close to the Fermi level,suggesting potential electron-phonon *** work reveals the important role of the full-breathing O phonon mode playing in the infinite-layer SrCuO_(2),which may provide new insights in understanding the cuprate superconductivity.
Sentiment analysis depends on individuals’comments and opinions on *** from social media platforms like Twitter,Quora,or Facebook poses challenges due to informal language,including acronyms,misspellings,and ambiguou...
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Sentiment analysis depends on individuals’comments and opinions on *** from social media platforms like Twitter,Quora,or Facebook poses challenges due to informal language,including acronyms,misspellings,and ambiguous ***,hyperparameters in machine learning models significantly impact *** address these issues,we propose advanced feature engineering techniques in Natural Language Processing(NLP)and hyperparameter optimization to enhance prediction accuracy and generalization *** study employs Naïve Bayes,Logistic regression(Lr),Multi-layer Perceptron(MLP),and Support Vector Machine(SVM)to classify sentiments in tweets about Elon Musk’s potential acquisition of *** dataset,consisting of 100,000 tweets,is fetched using the Twitterrepresentational state transfer application programming interface(rEST API).We outline a sentiment analysis procedure to classify unstructured Twitterdata,identify influential keywords,and categorize sentiments as Positive,Negative,or *** a hybrid Lexicon NLP approach,we extract contextually significant emotionally charged words and assign sentiment *** optimization via automated search methods ensures alignment with classifier performance *** achieved an impressive accuracy rate of 97%.Cross-validation minimizes random variations,providing a reliable assessment of the model’s generalization capabilities,anddemonstrating the method’s accuracy in predicting sentiments with larger new unseen standarddatasets,and varying sentiment.
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