查看更多>>摘要：Since the superior mechanical,chemical and physical properties of high-entropy alloys(HEAs)were discovered,they have gradually become new emerging candidates for renewable energy applications.This review presents the novel applications of HEAs in thermoelectric energy conversion.Firstly,the basic concepts and structural properties of HEAs are introduced.Then,we discuss a number of promising thermoelectric materials based on HEAs.Finally,the conclusion and outlook are presented.This article presents an advanced understanding of the thermoelectric properties of HEAs,which provides new opportunities for promoting their applications in renewable energy.
查看更多>>摘要：Thermal transistor,the thermal analog of an electronic transistor,is one of the most important thermal devices for microscopic-scale heat manipulating.It is a three-terminal device,and the heat current flowing through two terminals can be largely controlled by the temperature of the third one.Dynamic response plays an important role in the application of electric devices and also thermal devices,which represents the devices'ability to treat fast varying inputs.In this paper,we systematically study two typical dynamic responses of a thermal transistor,i.e.,the response to a step-function input(a switching process)and the response to a square-wave input.The role of the length L of the control segment is carefully studied.It is revealed that when L is increased,the performance of the thermal transistor worsens badly.Both the relaxation time for the former process and the cutoff frequency for the latter one follow the power-law dependence on L quite well,which agrees with our analytical expectation.However,the detailed power exponents deviate from the expected values noticeably.This implies the violation of the conventional assumptions that we adopt.
查看更多>>摘要：Electromagnetic absorbing materials may convert electromagnetic energy into heat energy and dissipate it.However,in a high-power electromagnetic radiation environment,the temperature of the absorbing material rises significantly and even burns.It becomes critical to ensure electromagnetic absorption performance while minimizing temperature rise.Here,we systematically study the coupling mechanism between the electromagnetic field and the temperature field when the absorbing material is irradiated by electromagnetic waves.We find out the influence of the constitutive parameters of the absorbing materials(including uniform and non-uniform)on the temperature distribution.Finally,through a smart design,we achieve better absorption and lower temperature simultaneously.The accuracy of the model is affirmed as simulation results aligned with theoretical analysis.This work provides a new avenue to control the temperature distribution of absorbing materials.
查看更多>>摘要：With the rapid advancement of quantum computing,hybrid quantum-classical machine learning has shown numerous potential applications at the current stage,with expectations of being achievable in the noisy intermediate-scale quantum(NISQ)era.Quantum reinforcement learning,as an indispensable study,has recently demonstrated its ability to solve standard benchmark environments with formally provable theoretical advantages over classical counterparts.However,despite the progress of quantum processors and the emergence of quantum computing clouds,implementing quantum reinforcement learning algorithms utilizing parameterized quantum circuits(PQCs)on NISQ devices remains infrequent.In this work,we take the first step towards executing benchmark quantum reinforcement problems on real devices equipped with at most 136 qubits on the BAQIS Quafu quantum computing cloud.The experimental results demonstrate that the policy agents can successfully accomplish objectives under modified conditions in both the training and inference phases.Moreover,we design hardware-efficient PQC architectures in the quantum model using a multi-objective evolutionary algorithm and develop a learning algorithm that is adaptable to quantum devices.We hope that the Quafu-RL can be a guiding example to show how to realize machine learning tasks by taking advantage of quantum computers on the quantum cloud platform.
查看更多>>摘要：We report the physical properties of ThRu3Si2 featured with distorted Ru kagome lattice.The combined experiments of resistivity,magnetization and specific heat reveal bulk superconductivity with Te=3.8 K.The specific heat jump and calculated electron-phonon coupling indicate a moderate coupled BCS superconductor.In comparison with LaRu3Si2,the calculated electronic structure in ThRu3Si2 shows an electron-doping effect with electron filling lifted from 100 meV below flat bands to 300 meV above it.This explains the lower superconducting transition temperature and weaker electron correlations observed in ThRu3Si2.Our work suggests the Tc and electronic correlations in the kagome superconductor could have an intimate connection with the flat bands.
查看更多>>摘要：We report on the magnetization and anomalous Hall effect(AHE)in the high-quality single crystals of the kagome magnet YbMn6Sn6,where the spins of the Mn atoms in the kagome lattice order ferromagnetically and the intermediate-valence Yb atoms are nonmagnetic.The intrinsic mechanism plays a crucial role in the AHE,leading to an enhanced anomalous Hall conductivity(AHC)compared with the other rare-earth RMn6Sn6 compounds.Our band structure calcu-lation reveals a strong hybridization between the 4f electrons of Yb and conduction electrons.
查看更多>>摘要：By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,respectively.From this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,and Γ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network models.Detailed analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and BiLSTM.The MAE peak of BiGRU+GRU reaches 0.00037.We have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent datasets.The ResNet has the worst performance among all the seven network models.The datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://doi.org/10.57760/sciencedb.j00113.00192.
查看更多>>摘要：We have theoretically and experimentally studied the dispersive signal of the Rydberg atomic electromagnetically-induced transparency(EIT)Autler-Townes(AT)splitting spectra obtained using amplitude modulation of the microwave(MW)electric field.In addition to the two zero-crossing points interval △fzeros,the dispersion signal has two positive maxima with an interval defined as the shoulder interval △fsho,which is theoretically expected to be used to measure a much weaker MW electric field.The relationship of the MW field strength EMW and △fsho is experimentally studied at the MW frequencies of 31.6 GHz and 9.2 GHz respectively.The results show that △fsho can be used to characterize the much weaker EMW than that of △fzeros and the traditional EIT-AT splitting interval △fm;the minimum EMW measured by△fsho is about 30 times smaller than that by △fm.As an example,the minimum EMW at 9.2 GHz that can be characterized by △fsho is 0.056 mV/cm,which is the minimum value characterized by the frequency interval using a vapor cell without adding any auxiliary fields.The proposed method can improve the weak limit and sensitivity of EMW measured by the spectral frequency interval,which is important in the direct measurement of weak EMW.
查看更多>>摘要：Atom tracking technology enhanced with innovative algorithms has been implemented in this study,utilizing a comprehensive suite of controllers and software independently developed domestically.Leveraging an on-board field-programmable gate array(FPGA)with a core frequency of 100 MHz,our system facilitates reading and writing opera-tions across 16 channels,performing discrete incremental proportional-integral-derivative(PID)calculations within 3.4 mi-croseconds.Building upon this foundation,gradient and extremum algorithms are further integrated,incorporating circular and spiral scanning modes with a horizontal movement accuracy of 0.38 pm.This integration enhances the real-time performance and significantly increases the accuracy of atom tracking.Atom tracking achieves an equivalent precision of at least 142 pm on a highly oriented pyrolytic graphite(HOPG)surface under room temperature atmospheric condi-tions.Through applying computer vision and image processing algorithms,atom tracking can be used when scanning a large area.The techniques primarily consist of two algorithms:the region of interest(ROI)-based feature matching algo-rithm,which achieves 97.92％accuracy,and the feature description-based matching algorithm,with an impressive 99.99％accuracy.Both implementation approaches have been tested for scanner drift measurements,and these technologies are scalable and applicable in various domains of scanning probe microscopy with broad application prospects in the field of nanoengineering.
查看更多>>摘要：The haloscope based on the TM010 mode cavity is a well-established technique for detecting QCD axions.How-ever,the method has limitations in detecting high-mass axion due to significant volume loss in the high-frequency cavity.Utilizing a higher-order mode cavity can effectively reduce the volume loss of the high-frequency cavity.The rotatable dielectric pieces as a tuning mechanism can compensate for the degradation of the form factor of the higher-order mode.Nevertheless,the introduction of dielectric causes additional volume loss.To address these issues,this paper proposes a novel design scheme by adding a central metal rod to the higher-order mode cavity tuned by dielectrics,which improves the performance of the haloscope due to the increased effective volume of the cavity detector.The superiority of the novel design is demonstrated by comparing its simulated performance with previous designs.Moreover,the feasibility of the scheme is verified by the full-wave simulation results of the mechanical design model.
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