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The chiral 2 × 2 charge order has been reported and confirmed in the kagome superconductor RbV3Sb5, while its interplay with superconductivity remains elusive owing to its lowest superconducting transition temperature T C of about 0.85 K in the AV3Sb5 family (A = K, Rb, Cs) that severely challenges electronic spectroscopic probes. Here, utilizing dilution-refrigerator-based scanning tunneling microscopy down to 30 mK, we observe chiral 2 × 2 pair density waves with residual Fermi arcs in RbV3Sb5. We find a superconducting gap of 150 μeV with substantial residual in-gap states. The spatial distribution of this gap exhibits chiral 2 × 2 modulations, signaling a chiral pair density wave (PDW). Our quasi-particle interference imaging of the zero-energy residual states further reveals arc-like patterns. We discuss the relation of the gap modulations with the residual Fermi arcs under the space-momentum correspondence between PDW and Bogoliubov Fermi states. [ABSTRACT FROM AUTHOR]

The study of the rheological characteristics of cement paste backfill(CPB) is of great significance for the rational arrangement of filling pipelines and efficient filling operations in mines. Purpose: The purpose of this study is to combine the complex and multifactorial paste rheological parameter measurement tests with advanced machine learning regression prediction models to achieve accurate predictions of paste rheological parameters. Method:The research method involves using 128 sets of paste rheological characteristic test data under different material mix conditions as the model dataset. The Extreme Gradient Boosting Regression Tree(XGBoost) model was selected,and Bayesian Optimization(BO)was used for hyperparameter tuning to establish a multi-objective parameter regression prediction model. Result; The results show that the BO-XGBoost model, optimized by the Bayesian algorithm, significantly improves performance compared to the XGBoost model, with the coefficient of determination R2 increasing by 6 %. The relative error between the actual and predicted values of the BO-XGBoost model is maintained at the 0. 02 level in the yield stress dataset and at the 0. 1 level in the viscosity dataset. Conclusion: The study concludes that the BO-XGBoost model can efficiently and accurately predict the rheological parameters of paste, using an innovative multi-objective regression model, providing a reference for the design of mine filling operations with practical engineering application significance. [ABSTRACT FROM AUTHOR]

Purpose:Taking the tailings discharged from a tin ore beneficiation plant in Yunnan as the object, this study analyzes the influencing factors of tailings slurry pipeline transportation mode and sand transportation efficiency through experimental research and numerical simulation. Method: The distribution pattern of tailings gradation was measured through water screen test, and the rheological characteristics of slurry were measured through slurry rheological test. Combined with ANSYS-FLUENT, the slurry pipeline transportation model was simulated and calculated. Conclusion: By comparing and analyzing the shortcomings criteria of Wasp et al.,a new criterion for pipeline transportation mode based on particle size distribution was proposed. The sand transportation efficiency was calculated by combining the distribution model and rheological parameters. The absolute error between the results and the measured values was within 5%,indicating that the new criterion is reasonable. At the same time, a new model for calculating sand transportation efficiency was constructed. Significance: The research provides a new criterion for the pipeline transportation mode of tailings slurry, which can provide a certain reference value for the application of similar situations in mine tailings slurry pipeline transportation. [ABSTRACT FROM AUTHOR]

In recent years,high voltage cross linked polyethylen (XLPE) cable buffer layer ablation defects occur frequently,which has a serious impact on the safe operation of the cable. It is extremely urgent to study how to reduce the impact of the buffer layer defects. Therefore,how to reduce the severity of the buffer layer ablation defects by improving the aluminum sheath structure is studied in this paper. Firstly,the reason of ablative defect of buffer layer is analyzed theoretically. Secondly,the buffer layer voltage calculation model is established. Finally,a defect cable is taken as the simulation object to calculate the suspension potential and the electric field intensity of the buffer layer after reducing the minimum inner diameter and the curvature at the trough of the aluminum sheath respectively with the white spot defect of the buffer layer. Taking the defective cable as an example,the simulation quantitative analysis shows that when the minimum inner diameter decreases,the suspension potential of insulation shielding decreases by 30%,and the electric field intensity between buffer layers decreases by 30.9%. When the curvature at the trough of the aluminum sheath decreases,the suspension potential of insulating shield decreases by 13.7%,and the electric field intensity between buffer layers decreases by 13.3%. When the buffer layer white spot appears,the decrease of the minimum inner diameter and the curvature at the trough of the aluminum sheath lead to the suspension potential of the insulating shield layer and the electric field intensity between the buffer layer decrease,thus reducing the possibility of partial discharge and the impact caused by the buffer layer defect.

C20H16N6, monoclinic, P21/c (no. 14), a = 7.6623(4) Å, b = 11.8206(5) Å, c = 8.8960(4) Å, β = 91.825(2)°,V = 805.33(7) Å3, Z = 2, R gt(F) = 0.0577, wR ref(F 2) = 0.1588, T = 200(2) K.

This study proposes a high-resolution rotation-measuring system for miniaturized MEMS ultrasonic motors using tunneling magnetoresistance (TMR) sensors for the first time. Initially, the architecture and principle of the rotation-measuring system are described in detail. Then, the finite element simulation is implemented to determine the miniaturized permanent magnet's residual magnetization, dimensions, and TMR sensor position. Finally, the experiments are implemented to evaluate the performance. Using calibration based on a high-precision servo motor, it is found that the relationship between the output and rotational angle is highly linear and immune to the rotor's out-of-plane movement. Meanwhile, the angle-detecting resolution is higher than 0.1°. After the calibration, the continuous rotation of the MEMS ultrasonic motor is tested. It is found that the angle testing result varies with a period close to 360°, which indicates that the rotation-measuring system has successfully detected the motor's rotation. [ABSTRACT FROM AUTHOR]

The theme of this study is to find a method that can more accurately classify the spatiotemporal distribution characteristics of power system voltage dynamics. As more and more new energy power generation devices are added to the power network, the accuracy of traditional methods for classifying the spatiotemporal distribution characteristics of power system voltage dynamics has gradually decreased. It is significant to reduce the power loss caused by error in identifying voltage dynamic spatiotemporal distribution characteristics. Hence it is necessary to design methods that can more accurately classify power system voltage dynamic spatiotemporal distribution characteristics data. This study proposes a method for studying the spatiotemporal distribution characteristics of power system voltage dynamics based on an improved random forest algorithm. The information entropy calculation method of decision tree in random forest algorithm is improved. According to the experimental results, the classification accuracy of the method for voltage dynamic spatiotemporal distribution characteristics is 99.55%. It can effectively achieve the dynamic spatiotemporal distribution of power system voltage. [ABSTRACT FROM AUTHOR]