bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultralow-Temperature Heat Transport Evidence for Residual Density of States in the Superconducting State of CsV3Sb5
Authors: Zhao 赵 C. C. 成成 , Wang 王 L. S. 临舒 , Xia 夏 W. 威 , Yin 殷 Q. W. 蔷薇 , Deng 邓 H. B. 翰宾 , Liu 刘 G. W. 国威 , Liu 刘 J. J. 锦锦 , Zhang 张 X. 旭 , Ni 倪 J. M. 佳敏 , Huang 黄 Y. Y. 烨煜 , Tu 涂 C. P. 成鹏 , Tao 陶 Z. C. 咨成 , Tu 涂 Z. J. 志俊 , Gong 龚 C. S. 春生 , Wang 王 Z. W. 秩伟 , Lei 雷 H. C. 和畅 , Guo 郭 Y. F. 艳峰 , Yang 杨 X. F. 小帆 , Yin 殷 J. X. 嘉鑫 , Li 李 S. Y. 世燕 
Published: November 2024

Abstract
V-based kagome superconductors AV3Sb5 (A = K, Rb, and Cs) host a charge density wave (CDW) and a topological nontrivial band structure, thereby providing a great platform to study the interplay of superconductivity (SC), CDW, frustration, and topology. Here, we report ultralow-temperature thermal conductivity measurements of CsV3Sb5 and Ta-doped Cs(V0.86Ta0.14)3Sb5 and scanning tunneling microscopy (STM) measurements of CsV3Sb5. The finite residual linear term of thermal conductivity at zero magnetic field suggests the existence of a residual density of states (DOS) in the superconducting state of CsV3Sb5. This is supported by the observation of non-zero conductance at zero bias in STM spectrum at an electronic temperature of 90 mK. However, in Cs(V0.86Ta0.14)3Sb5, which does not have CDW order, there is no evidence for the residual DOS. These results show the importance of CDW order for the residual DOS, and that a nodal s-wave gap or residual Fermi arc may be the origin of the residual DOS in such an unusual multiband kagome superconductor, CsV3Sb5.
Helicity-Controlled Spin Hall Angle in 2D Altermagnets with Rashba Spin-Orbit Coupling
Authors: Chen Weiwei , Zeng Longhai , Zhu W. 
Published: November 2024

Abstract
We investigated the efficiency of charge-to-spin conversion in two-dimensional Rashba altermagnets, a class of materials that combines the characteristics of both ferromagnets and antiferromagnets. Using quantum linear response theory, we quantified the longitudinal and spin Hall conductivities in this system and demonstrated a substantial enhancement in the spin Hall angle below the band crossing point through the dual effects of relativistic spin–orbit interaction and nonrelativistic altermagnetic exchange interaction. Additionally, the results showed that the skew scattering and intrinsic mechanisms arising from Fermi sea states are almost negligible in this system, in contrast to conventional ferromagnetic Rashba systems. Our findings not only elucidate the spin dynamics in Rashba altermagnets but also pave the way for developing novel strategies for manipulating charge-to-spin conversion via sophisticated control of noncollinear and collinear out-of-plane spin textures.
New sources of ghost fields in k-essence theories for black-bounce solutions
Authors: Pereira Carlos F S , Rodrigues Denis C , Martins Ébano L , Fabris Júlio C , Rodrigues Manuel E 
Published: November 2024

Abstract
In the present study, we generalize the possible ghost field configurations within the framework of k-essence theory to the Simpson–Visser metric area function

Σ
2

=

x
2

+

a
2

. Our analysis encompasses field configurations for the region-defined metric function

A
±

as well as the general solution that asymptotically behaves as Schwarzschild-de Sitter for

x
→
−
∞

. Specifically, we investigate two scalar field configurations and define the associated potential for each one. Through rigorous calculations, we verify that all equations of motion are satisfied. Notably, our findings indicate that even when proposing new configurations of ghost scalar fields, the energy conditions remain unchanged. This result serves to validate the wormhole solutions obtained in previous studies.
Influence of Sn2+ doping to improve the charge transport and light-emitting properties of CsPbCl3 perovskites
Authors: Sharma Deenbandhu , Sharma S K 
Published: November 2024

Abstract
Doping B-site with metal ions is an emerging strategy to reduce lead toxicity and enhance the optoelectronic performance of lead halide perovskites. Also, the concentration of metal dopants plays an important role in achieving the desired electrical and optical properties of these halide perovskites. This work presents a simple chemical approach to synthesize pure and Sn2+ doped CsPbCl3 perovskites at room temperature. The dopant concentration was varied from 1 to 9 mol%. The structural, morphological, optical, thermal, and electrical properties of prepared perovskites are studied in order to check the optimal doping concentration along with to know the improvement in the optoelectronic properties required for LEDs and photovoltaic cells. It was observed that CsPbCl3 perovskites exhibit high photoluminescence intensity, blue/violet emission, and high charge carrier mobility (up to 56.3 cm2 V s−1) with a reduction in bandgap (up to 2.865 eV) after Sn2+ doping.
Research on avalanche tolerance test method for power devices based on avalanche energy equivalence
Authors: Zou Shenglei , Yang Yuan , Wen Yang , Du Xingfeng , Wang Yaxin , Guo Sunyu , Li Yan 
Published: November 2024

Abstract
A general avalanche tester that utilizes an unclamped inductive switching (UIS) test is essential for measuring the maximum energy that a power device can withstand before failure. This procedure is critical for evaluating the reliability and robustness of power devices. Avalanche testers typically require high-precision hollow inductors with broad adjustable ranges and fine increments to accommodate the varying test conditions of different devices. However, this often results in large, heavy, and expensive inductor modules. In this study, we propose and experimentally demonstrate a novel method for testing avalanche tolerance based on avalanche energy equivalence. This method employs the magnetic core inductance as an alternative to the traditionally used bulky air-core inductance in avalanche testers, producing results comparable to those obtained from conventional UIS tests. To verify the equivalence of the avalanche energy, we designed a UIS experimental platform that includes a 1.3 mH magnetic core inductor connected in series with an adjustable air-core inductor. This configuration enables the evaluation of the maximum avalanche current consistency and degree of core inductor attenuation during the UIS test for two commercial P-channel and N-channel power MOSFET devices. The experimental results indicate that the difference between the avalanche energy and maximum avalanche current in the UIS test under both inductor conditions is approximately 1

%

. Consequently, the magnetic core inductor can replace the air-core inductor. The method proposed in this study offers a promising direction for optimizing avalanche testers to meet the demands of modern devices for miniaturization and high efficiency, thereby reducing material consumption, production costs, and transportation expenses. This enhances product market competitiveness and holds practical value in engineering applications.
Optimizing coupled fault diagnosis in liquid rocket engines via distributed robust multi-model Kalman filter
Authors: Zhang Zhenzhen , Zhang Xiaoguang , Chen Hui , Li Yixuan , Chen Zhenyi 
Published: November 2024

Abstract
This paper concerns a novel fault diagnosis method for decoupling and diagnosing liquid rocket engine (LRE) system and sensor failures. LRE faults significantly affect the launch reliability. Many traditional methods applied in system-level fault diagnosis of LRE struggled with robustness when dealing with sensor and system coupling faults. The distributed robust multi-model Kalman filter (DRMM-KF) based fault diagnosis method is proposed for the LRE sensor-system concurrent fault diagnosis problem to solve the aforementioned issues. Firstly, improvements are made to the multi-model Kalman filter (MM-KF) method to enhance the robustness of the hypothetical model conditional probability calculation to obtain the robust MM-KF (RMM-KF). Then, based on the RMM-KF and local sensor fault hypothesis models, the local robust MM-KFs (LRMM-KFs) are established to describe the local sensor faults of the LRE subsystems, and then, the DRMM-KFs are established by integrating each LRMM-KF to realize the adaptive description of the LRE sensor faults. Finally, by fusing the results of the LRMM-KFs, the index fusion weighted sum-squared residual (FWSSR) is established for LRE system and sensor faults decoupling and diagnosis. After that, three hot-test cases are given to illustrate the effectiveness of the proposed method in practice. The contribution of this study is to propose the novel DRMM-KF algorithm to achieve real-time LRE system and sensor faults decoupling fault diagnosis, showing the capacity of distinguishing between system and sensor faults with alarm timely.
Performance analysis of LEO augmented GNSS precise point positioning from in-orbit CENTISPACETM satellites
Authors: Gao Weiguang , Xie Xin , Meng Yinan , Li Qiang , Chen Hanlin , Yang Long , Geng Tao , Zhao Qile 
Published: November 2024

Abstract
Low Earth orbit (LEO) satellites can be used to augment global navigation satellite system (GNSS) precise point positioning (PPP) for rapid convergence, which has been demonstrated by an abundance of simulation studies. In this contribution, we analyze the performance of LEO augmented GNSS PPP using real data from two in-orbit CENTISPACETM experimental satellites launched by Beijing Future Navigation Tech Co., Ltd. The onboard GNSS observations are used to determine the precise orbits and the initial clock offsets of LEO satellites, and the clock corrections are estimated using the observations from a ground network. The RMS values of measurement residuals for dual-frequency ionosphere-free combination of LEO downlink pseudorange and phase observations are about 0.8 m and 2 cm. We select three ground tracking stations for the PPP experiment and the performance of GPS, BeiDou Navigation Satellite System (BDS)-3, GPS + BDS-3, GPS + BDS-3 + Galileo PPP with the augmentation of 1 and 2 LEO satellites is evaluated and analyzed. The results indicate that the observations from LEO satellites can significantly improve the GNSS convergence performance. Compared with GNSS-only PPP, the convergence time is shortened by more than 50% with the addition of 1 LEO satellite, while the two LEO satellites achieve an improvement of 68%–73%. In particular, to achieve a horizontal accuracy of better than 10 cm, the convergence time for the GPS + BDS-3 + Galileo PPP solutions is reduced from 10.8 min to 3–5 min with the augmentation of 1–2 LEO satellites, which reveals the excellent potential of LEO satellites for rapid PPP convergence. The correlation analysis between ambiguity parameters and other related parameters during the PPP processing also demonstrates the superior performance of the LEO satellites in accelerating the PPP convergence. Furthermore, the GNSS/LEO combined PPP improves the 3D positioning accuracy by 10%–20%.
Advanced detection methods for tunnels and roadways: a review
Authors: Chen Dingchao , Wang Xiangyu , Bai Jianbiao , Lu Jianfei , Wu Bowen , Li Xin , Li Yan , Zhang Feiteng , Li Menglong 
Published: November 2024

Abstract
As underground engineering construction expands globally, numerous tunnels and roadways are excavated annually. However, the complex and unpredictable underground geological conditions pose risks of accidents and casualties if not promptly and accurately identified. Therefore, precise identification and early prediction of adverse geological conditions are crucial. This paper reviews the development process of advanced detection technology for tunnels and roadways, categorizing it into four stages: manual stage, automatic stage, detection while excavation stage, and intelligent stage, China is currently transitioning from the second to the third stage. Additionally, this paper emphasizes the principles, characteristics, and applications of conventional advanced detection methods, including seismic methods, electrical methods, electromagnetic methods, etc. Addressing the limitations of conventional methods, including short detection distance, low efficiency, and high cost, this paper introduces integrated designs for detection instruments and tunneling machines, specifically tunnel seismic while drilling (TSWD) and tunnel electrical while drilling. These methods enable simultaneous excavation and detection, enhancing work efficiency by over 50%, with TSWD achieving a maximum detection distance of 200 m. In addition, this paper provides a unified summary of the advantages, disadvantages, and applicable conditions of both conventional and detection while excavation methods. Finally, this paper discusses two important future directions for tunnel and roadway advanced detection: multi-source signal cooperative detection and application of intelligent technology.
Deep learning-assisted magnetized inductively coupled plasma discharge modeling
Authors: Zhao Yang , Chen Wenyi , Miao Zongcheng , Yang Pengfei , Zhou Xiaohua 
Published: November 2024

Abstract
In recent years, magnetized inductively coupled plasma (MICP) has been proposed as an improved version of inductively coupled plasma to meet the increasing production process requirements. However, due to the more complex structure of the plasma system, numerical simulations face challenges such as modeling difficulty, model convergence issues, and long computation times. In this paper, a deep neural network (DNN) with a multi-hidden layer structure is developed based on deep learning technology to serve as an assisted modeling tool of traditional fluid simulations. This approach aims to study the discharge characteristics and plasma chemistry of argon-oxygen MICP more efficiently. The simulation data from the fluid model is used to train the neural network. The well-trained DNN can efficiently and accurately predict the target plasma characteristics under new discharge parameters, such as electron density, ionization rate, and particle reaction rate. The effectiveness of the DNN is verified by comparing its predictions with fluid simulation results. Compared to the traditional fluid simulation, which takes thousands of seconds, the trained DNN can produce highly consistent prediction results only within 1 s. The computing efficiency is significantly improved. The prediction results of the DNN demonstrate that by adjusting discharge parameters such as magnetic field coil current, power, and O2 ratio, the plasma discharge characteristics and plasma chemistry can be modulated, including charged particle density, ionization rate, chemical reaction rate, and plasma radial uniformity. Additionally, the DNN shows good generalization ability across multiple input and output scales, providing a paradigm for its application in other plasma research fields. This study indicates that the DNN is a feasible method for studying MICP discharge characteristics and offers a novel and effective computational tool for future plasma discharge research based on deep learning methods.
Interfacial polarization charge engineering with co-designed LQB and EBL for enhanced EQE of AlGaN DUV LEDs
Authors: Gao Yipin , Tian Wentao , Qi Ying , Li Shuti , Liu Chao 
Published: November 2024

Abstract
In this paper, we propose to modulate the polarization charges at the interface between the last quantum barrier (LQB) and the electron blocking layer (EBL) via strategically adjusting the Al composition in the LQB and EBL simultaneously. With appropriate design of the linear gradient profile in Al composition, the original positive polarization charges at the LQB/EBL interface can be diminished or converted into negative charges, which helps to reduce the positive electric field in EBL, thus adjusting the energy band near the LQB/EBL interface. Enhanced effective barrier height for electrons, decreased effective barrier height for holes, and accumulation of a large number of holes at the LQB/EBL interface are obtained, resulting in improved electron leakage and hole injection. In comparison with the reference deep ultraviolet light-emitting diode (DUV LED), an enhanced external quantum efficiency by 37.5% at an injection current density of 100 A cm−2 is achieved for the device with negative polarization charges. The modulation strategy of polarization charges at the LQB/EBL interface via co-designing the linear gradient of Al composition in LQB and EBL can be a feasible approach for obtaining high-performance DUV LEDs.
Variation-aware analysis of buried-channel-array transistors (BCATs) in scaled DRAM: insights from 3D quasi-atomistic simulations
Authors: Yoon Seokchan , Lim Jaehyuk , Shin Changhwan 
Published: November 2024

Abstract
As dynamic random access memory (DRAM) feature sizes continue to scale down, optimizing performance requires the evolution of architectures such as the buried-channel-array transistor (BCAT). Diminutive DRAM cell dimensions have increased susceptibility to variation, necessitating comprehensive simulations considering both systematic and random aspects. This study employs a three-dimensional quasi-atomistic model to implement surface random variations and investigates systematic structural variation induced by rounding between saddle-fin and source/drain regions. The impact on BCAT performance is analyzed using the standard deviation (SD) of output parameters, simultaneously simulating surface and structural aspects. Results show that increased surface roughness corresponds to increased SD, while alterations in structural variation, particularly channel and sidewall curvature, influence both mean and SD. Increased curvature leads to decreased threshold voltage and increased current levels. This simulation approach enables detailed estimation of variation distribution in BCATs, providing valuable insights for optimizing design and fabrication processes, ultimately enhancing DRAM performance and reliability. The findings highlight the importance of considering the interplay between surface and structural variations in advanced memory devices.
Neural network analysis for prediction of heat transfer of aqueous hybrid nanofluid flow in a variable porous space with varying film thickness over a stretched surface
Authors: Alnahdi Abeer S , Gul Taza 
Published: November 2024

Abstract
The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids. Enhanced heat transfer is a result of this high thermal conductivity, which has significant applications in heat exchangers and engineering devices. To optimize heat transfer, a liquid film of Cu and TiO2 hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance. The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film. The solution of the problem is acquired using the homotopy analysis method HAM, and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis. HAM data is utilized to train the ANN in this study, which uses Cu and TiO2 hybrid nanofluids in a variable porous space for unsteady thin film flow, and it is used to train the ANN. The results indicate that Cu and TiO2 play a greater role in boosting the rate.
Pole determination of
and
in the decay
*
Authors: Lu 卢 Jialiang 家亮 , Song 宋 Mao 昴 , Li 李 Gang 刚 , Luo 罗 Xuan 旋 
Published: November 2024

Abstract
Two near-threshold peaking structures with spin-parities of

were recently discovered by the LHCb Collaboration in the

invariant mass distribution of the decay process

. In our study, we employed a coupled-channel model to fit the experimental results published by the LHCb Collaboration, simultaneously fitting the model to the invariant mass distributions of

,

, and

. We utilized a coupled-channel model to search for the poles of

and

. The determination of the poles is meaningful in itself, and it also lays a foundation for future research on

and

. Upon turning off the coupled-channel and performing another fit, we observed a change in the fitting quality, and the effect was almost entirely due to the peak of

. Therefore, we suggest that

may not be a kinematic effect.
Application of incremental 4D-Var for real-time prediction of a fire enclosure oscillatory dynamics
Authors: Ikhou O , Stefic W , Gautier A , Varrall K , Vauquelin O 
Published: November 2024

Abstract
This study explores the use of data assimilation to enhance the prediction and management of enclosure fires. By crossing the data provided by a simplified physical model with observations, we demonstrated the feasibility of adjusting the more probable real state of the system, which could improve the prediction of fire evolution. Our method is tested with large-scale oscillating enclosure fire. After a preliminary study in which we evaluate the ability of our physical model to adequately represent reality by using the experimental mass loss rate as input data, we presented a study reconstituting this information from experimental data – the results of which show that this method seems to provide accurate real-time forecasts for this type of fire.
A review of fire safety separation distances between camping units and caravans
Authors: Wilkens Flecknoe-Brown Konrad 
Published: November 2024

Abstract
Almost 20 years ago, the Swedish civil contingency agency (MSB) representatives published a general advice on fire protection at camping facilities. Within this document there contains advice on what distances are needed between camping units to reduce the risk of fire spreading between them, however how these distances were decided on is lost to history and given the changes and development in caravans and camping over the last 30 years a review of this guidance was required. To do this an extensive literature review into both scientific and other countries regulations was performed. The scientific literature was found lacking or outdated in this area, and country regulations were shown to be sporadic and highly varied in their given guidance, with little evidence of scientific basis for chosen distances.
CFD Predictions of Fire Spread over Wood Cribs in Large Open-plan Compartments: New Insights
Authors: Liu C , Dai X , Ming X M , Welch S 
Published: November 2024

Abstract
A CFD-based numerical simulator, coupled with a multi-component pyrolysis model established for an isolated wood crib fire test, successfully predicts fire spread behaviours and the evolution in compartment boundary conditions in a large-scale test with an extended, uniform fuel bed. Five distinct fire spread modes are identified, showing a gradual transition from 2D to 1D planar fire spread patterns. Our new model is no longer constrained to follow prescribed burning rates and an analysis of the drivers of fire spread at the level of the individual wood sticks shows linear correlations of burning rates with the incident heat fluxes at the fire’s leading edge, and similar within the crib during the main travelling fire phase, but higher rates when preheating effects dominate later in the fire. There is also relative insensitivity to exposures on the surface of the crib at the trailing edge, and it is believed that burning rates here are effectively isolated from preheating effects by the development of rigid char layer with high thermal resistance, thereby decoupling them from the compartment boundary conditions. This is a feature long recognised in experimental studies, but which is very challenging to corroborate through direct experimental measurements.