bluuebunny/crossref_metadata_2025_split huggingface dataset:
All-top-contact 0.59 eV InGaAs thermophotovoltaic cells and modules
Authors: Tang Liangliang , Yin Long , Shao Jianxiong , Tang Yili , Liu Yonghui 
Published: August 2023

Abstract
InGaAs cells are ideal converters for low temperature thermophotovoltaic power generation systems. Commonly, the positive and negative electrodes of InGaAs cells are deposited on the top and bottom of the cells, respectively. In the engineering of level modules, solder strips are used to connect the top and bottom of adjacent cells, the distance between the cells is considerable in order to prevent short circuits from the side wall of the cells, and the area ratio of cells to modules is relatively low. In this paper, we design and fabricate a novel all-top-contact InGaAs cell, with the positive electrode deposited on top of the p-InGaAs epitaxial layer, and the negative electrode deposited on top of the n-InPAs-grade epitaxial layer by precise etching of the p–n junction layers. The novel all-top-contact cells show good efficiencies compared to traditional cells with top-and-bottom electrodes under the same testing conditions. Novel flat and compact cell modules were fabricated using all-top-contact InGaAs cells, the distance between the adjacent cells was controlled within tens of microns, and the area ratio of cells to modules was improved efficiently.
Dynamics of polaron formation in 1D Bose gases in the strong-coupling regime
Authors: Will Martin , Fleischhauer Michael 
Published: August 2023

Abstract
We discuss the dynamics of the formation of a Bose polaron when an impurity is injected into a weakly interacting one-dimensional Bose condensate. While for small impurity-boson couplings this process can be described within the Froehlich model as generation, emission and binding of Bogoliubov phonons, this is no longer adequate if the coupling becomes strong. To treat this regime we consider a mean-field approach beyond the Froehlich model which accounts for the backaction to the condensate, complemented with Truncated Wigner simulations to include quantum fluctuation. For the stationary polaron we find a periodic energy-momentum relation and non-monotonous relation between impurity velocity and polaron momentum including regions of negative impurity velocity. Studying the polaron formation after turning on the impurity-boson coupling quasi-adiabatically and in a sudden quench, we find a very rich scenario of dynamical regimes. Due to the build-up of an effective mass, the impurity is slowed down even if its initial velocity is below the Landau critical value. For larger initial velocities we find deceleration and even backscattering caused by emission of density waves or grey solitons and subsequent formation of stationary polaron states in different momentum sectors. In order to analyze the effect of quantum fluctuations we consider a trapped condensate to avoid 1D infrared divergencies. Using Truncated Wigner simulations in this case we show under what conditions the influence of quantum fluctuations is small.
A large magnetocaloric effect and thermoelectric properties of anti-perovskite SnMn3N material: a DFT study and monte carlo simulation
Authors: Alaoui Y Charif , Jabar A , Tahiri N , El Bounagui O , Ez-Zahraouy H 
Published: August 2023

Abstract
In this paper, we have investigated the electronic, magnetic, magnetocaloric, and thermoelectric properties of the anti-perovskite material SnMn3N using density functional theory (DFT) calculations and Monte Carlo simulations. We observed a second-order phase transition at a temperature of T = 480 K. Firstly, we studied the structural and electronic properties of the material. The crystal structure of this material is cubic with a spatial group of Pm3m. Secondly, we examined the magnetocaloric properties of this metallic compound by calculating the magnetic entropy change

(

∆
S

max

) and the relative cooling power (RCP) under different magnetic fields: 1 T, 3 T, and 5 T. The values obtained for these parameters were 19.382 J kg−1 K−1 and 203.466 J kg−1 at an external magnetic field of 5 T, respectively. Lastly, we also analyzed the thermoelectric properties of the compound using the BoltzTraP and Gibbs2 methods. We determined that the Seebeck coefficient at room temperature is 17.7766 μV K−1) and 23.099 μV K−1) in the transition phase at 480 K. We are currently conducting measurements of the thermal conductivity and power factor of this material at both room temperature and the transition temperature of 480 K. In summary, this study provides a deeper understanding of the magnetocaloric, thermoelectric, and thermal properties of the SnMn3N material, which can potentially be utilized in the development of more efficient cooling systems.
Independent wavefront manipulation of broadband spin-decoupled metasurfaces based on equivalent circuit model
Authors: Chen Xinbo , An Cheng , Zhou Jianyang , Li Weiwen 
Published: August 2023

Abstract
Various functional meta-devices have exhibited powerful manipulation of orbital angular momentum spectrums, but they are still faced with the issue of inherent spin-correlated characteristic and lack of effective method to design metasurface. In this work, a broadband spin-decoupled metasurface is presented to realize independent regulation of dual circularly polarized waves. Based on the transmission line theory, an equivalent circuit model of meta-atom is proposed to establish the relationship between reflection coefficients and structural parameters. By utilizing the model, a group of meta-atoms has been designed with a step phase difference of 45°, which can form a 3-bit coding metasurface. The proposed meta-atoms have a broad frequency band covering 11.56 − 18.17 GHz (44.5%). Moreover, the bifunctional reflection-type metasurfaces are constructed for producing the vortex waves along the +z axis, the off-axis pencil beams, and their synthetic beams. Based on the Fourier transform analysis, the mode purity and the electric field distribution of the generated beams are discussed in detail. The experimental measurements have good agreement with the simulation results, thus revealing the effectiveness of the proposed methodology to design metasurface.
First-principles study of the phase stability and elastic properties of TiVNbMoM (M = Al, Sc, Ni and Cu) high entropy alloys
Authors: Al-Zoubi N 
Published: August 2023

Abstract
The ab initio exact muffin-tin orbitals (EMTO) method in combination with the coherent potential approximation (CPA) were used to study the influence of alloying elements M = Al, Sc, Ni and Cu on the phase stability, lattice constants, elastic constants, polycrystalline elastic moduli and electronic structure of equiatomic and non-equiatomic TiVNbMoM refractory high entropy alloys. The agreement between our results and the available experimental and theoretical data is quite good. It was found that the equiatomic systems are stable in the body-centered cubic (bcc) structure. Alloying elements decrease the stability of the bcc against the face-centered cubic (fcc) and the hexagonal close-packed (hcp) structures. Scandium enlarges the lattice constants of equiatomic and non-equiatomic systems significantly. According to the calculated bulk modulus to shear modulus, Poisson’s ratio and Vickers hardness, all studied equiatomic and non-equiaomic systems are found to be ductile. However, alloying elements Al, Ni and Cu reduce the ductility and improve the hardness of equiatomic and non-equiatomic TiVNbMoM systems, while the ductility (hardness) of non-equiatomic systems enhances (reduces) by substitution with Sc element. The present theoretical results provide insight for the design and improvement of high entropy alloys and complete information on the alloying effects.
Determination of the resonant parameters of excited vector strangenia with
data*
Authors: Zhu 朱 Wenjing 文静 , Wang 王 Xiaolong 小龙 
Published: August 2023

Abstract
We determine the resonant parameters of the vector states

and

by performing a combined fit to the

cross sections from the threshold to

measured by the BaBar, Belle, BESIII, and CMD-3 experiments. The mass

and width

are obtained for

, and the mass

and width

are obtained for

. The statistical significance of

is

. Depending on the interference between

,

, and a non-resonant

amplitude in the nominal fit, we obtain four solutions and

,

,

or

, and

,

,

or

. We also search for the production of

, and the significance is only

. We then determine the upper limit of

at the 90% confidence level.
CP asymmetry from the resonance effect of the B meson decay process with π and K final states*
Authors: Yuan 原 Xi-Liang 喜亮 , Lü 吕 Gang 刚 , Wang 王 Na 娜 , Zhang 张 Li-Ying 丽英 , Guo 郭 Xin-Heng 新恒 
Published: August 2023

Abstract
We present the novel

resonance, which generates a strong phase associated with vector meson resonances, leading to significant CP asymmetry in the interference region. The

,

, and

resonances arise from the mixing of the vector mesons ϕ, ρ, and ω. We calculate the CP asymmetry from the decay mode of

. Meanwhile, the localized CP asymmetries are presented and a detailed analysis is performed. The CP asymmetry from the decay mode of

is also presented in our framework, which is highly consisted with that of the LHC experiment. The introduced CP asymmetry can provide a favorable theoretical support for experimental exploration in the future.
Preparation and performance study of multichannel PLA artificial nerve conduits
Authors: Wang Shanlong , Wang Yuyu , Chen Biling , Zhao Mingda , Song Gongji , Wang Jiannan , Xu Jianmei 
Published: August 2023

Abstract
Compared with single-channel nerve conduits, multichannel artificial nerve conduits are more beneficial for repairing damaged peripheral nerves of long-distance nerve defects. Multichannel nerve conduits can be fabricated by the mold method and the electrospinning method but with disadvantages such as low strength and large differences in batches, while the braiding method can solve this problem. In this study, polylactic acid yarns were used as the braiding yarn, and the number of spindles during braiding was varied to achieve 4, 5, 6, 7 and 8 multichannel artificial nerve conduits. A mathematical model of the number of braiding yarn spindles required to meet certain size specification parameters of the multichannel conduit was established. The cross-sectional morphology and mechanical properties of the conduits were characterized by scanning electron microscopy observation and mechanical testing; the results showed that the multichannel structure was well constructed; the tensile strength of the multichannel conduit was more than 30 times that of the rabbit tibial nerve. The biocompatibility of the conduit was tested; the in vitro cell culture results proved that the braided multichannel nerve conduits were nontoxic to Schwann cells, and the cell adhesion and proliferation were optimal in the 4-channel conduit among the multichannel conduits, which was close to the single-channel conduit.
Quantifying impact-relevant heatwave durations
Authors: Polt Kelley De , Ward Philip J , de Ruiter Marleen , Bogdanovich Ekaterina , Reichstein Markus , Frank Dorothea , Orth René 
Published: August 2023

Abstract
Heatwaves are weather hazards that can influence societal and natural systems. Recently, heatwaves have increased in frequency, duration, and intensity, and this trend is projected to continue as a consequence of climate change. The study of heatwaves is hampered by the lack of a common definition, which limits comparability between studies. This applies in particular to the considered time scale for utilised metrics. Here, we study which durations of heatwaves are most impact-relevant for various types of impacts. For this purpose, we analyse societal metrics related to health (heat-related hospitalisations, mortality) and public attention (Google trends, news articles) in Germany. Country-averaged temperatures are calculated for the period of 2010–2019 and the warmest periods of all time scales between 1 and 90 days are selected. Then, we assess and compare the societal response during those periods to identify the heatwave durations with the most pronounced impacts. Note that these durations are based on average temperatures across the given time frame while individual days may be less warm. The results differ slightly between the considered societal metrics but indicate overall that heatwaves induce the strongest societal response at durations between 2 weeks and 2 months for Germany. Finally, we show that heatwave duration affects the societal response independent of, and additionally to, heatwave temperatures. This finding highlights the relevance of making informed choices on the considered time scale in heatwave analyses. The approach we introduce here can be extended to other societal indices, countries, and hazard types to reveal more meaningful definitions of climate extremes to guide future research on these events.
Artificial intelligence can dynamically adjust strategies for auxiliary diagnosing respiratory diseases and analyzing potential pathological relationships
Authors: Zhang Quan , Chen Binyue , Liu Guohua 
Published: August 2023

Abstract
Respiratory diseases are one of the leading causes of human death and exacerbate the global burden of non-communicable diseases. Finding a method to assist clinicians pre-diagnose these diseases is an urgent task. Existing artificial intelligence-based methods can improve the clinical diagnosis efficiency, but still face challenges. For example, the lack of interpretability, the problem of information redundancy or missing caused by only using static data, the difficulty of model to learn the interdependence between features, and the performance of model is limited by sparse datasets, etc. To alleviate these problems, we propose a novel RQPA-Net. It consists of Q&A diagnosis module (QAD) and pathological inference module (PI). The QAD is responsible for interacting with patients, adjusting inquiry strategies dynamically and collecting effective information for disease diagnosis. The designed multi-subspace network can alleviate the problem that classical method is difficult to understand the interdependence between features. The deep reinforcement learning designed also can alleviate the problem of classical methods lack of interpretability. The PI is responsible for reasoning potential pathological relationships between diseases or symptoms based on existing knowledge. Through integrating the advantages of deep learning and reinforcement learning techniques, PI can handle sparse datasets. Finally, for auxiliary diagnosis, the model achieves 0.9780 ± 0.0002 Recall, 0.9778 ± 0.0003 Acc, 0.9779 ± 0.0003 Precision and 0.9780 ± 0.0003 F1-score on the test set. In terms of assisting pathological analysis, compared with the end-to-end model, our model achieves higher comprehensive performance on different tasks and datasets with different degrees of sparsity. Even in sparse datasets, it can effectively infer potential associations between diseases or symptoms, and has higher potential clinical application. In this paper, we propose a novel network structure, which can not only assist doctors in diagnosing diseases, but also contribute to explore the potential disease mechanisms. It provides a new perspective for integrating AI technology and clinical practice.
Exploring the influence of nanocavity alignment on slow light generation via multiple EIT and Fano resonances in square lattice plasmonic silver nanostructures
Authors: Khan Haseeb Ahmad , Khan Adnan Daud , Shah Syed Waqar , Chaudhry Muhammad Rehan , Azeem Farhan , Ahmed Salman , Ahmad Khurshid 
Published: August 2023

Abstract
In this paper, we present a comprehensive investigation of multiple electromagnetic induced transparency (EIT) and Fano resonances in a square lattice plasmonic nanostructure, which is composed of four silver slabs arranged in a square configuration, with each slab featuring a cylindrical nanocavity at its center. Initially, symmetric structures were analyzed to explore the potential for achieving EIT effects. Subsequently, we introduce deliberate symmetry breaking by precisely aligning the nanocavity in a controlled manner, first within a single slab, then in combinations of two, three, and all four slabs simultaneously. This controlled alignment strategy enabled the relaxation of dipole coupling selection rules, leading to the mixing of dipole and higher-order modes. The interaction between these modes resulted in the generation of multiple EITs and Fano resonances in the optical spectrum. Furthermore, the effective group index was evaluated for the optimal results obtained in the single, double, triple, and four symmetry reduced structures. High group index values were observed in the vicinity of the EIT and Fano resonances, with a remarkable maximum group index value of 6900 achieved within the EIT window. These findings highlight the significant potential of these structures in the design of slow light devices and sensitive sensors.
Preparation of corrosion-resistant surface of magnesium alloy and its performance study
Authors: Li Shimeng , Sun Baofu 
Published: August 2023

Abstract
The susceptibility of magnesium alloys to corrosion has hindered the wide application of magnesium alloys. A natural green method was proposed in this study to prepare a corrosion-resistant film layer whose main substance is MgO on the magnesium alloy substrate by a two-step hydrothermal method combining water steaming and annealing treatment. The morphology, composition, structure and corrosion resistance of the coating were investigated by SEM, FTIR, XRD and electrochemical methods. The results showed that the prepared coating has excellent corrosion resistance, reducing corrosion current by about four orders of magnitude compared with the bare Mg alloy substrate, and the corrosion potential and corrosion rate are also increased in different degree.
Interaction of 1/2〈111〉 interstitial dislocation loop with hydrogen and helium in tungsten: molecular dynamics simulation
Authors: Xu Bai-Chuan , Li Xiao-Chun , Wang Jinlong , Li Ya-Wen , Pan Xin-Dong , Lyu Yi-Ming , Zhou Hai-Shan , Luo Guang-Nan 
Published: August 2023

Abstract
The interaction of hydrogen and helium atoms with 1/2 〈111〉 interstitial dislocation loop in tungsten is investigated by molecular dynamics simulation. The binding energies of hydrogen and helium atoms around dislocation loop are calculated by molecular statics method. The results show that the outer region of the loop is attractive to the two atoms and the inner region is repulsive. Notably, the maximum binding energies are located in the core region of the dislocation loop. We have also studied the influence factors of the interaction between the dislocation loop and two atoms: free volume, lattice distortion degree, the radius and shape of the dislocation loop. The results show that large free volume benefits the retention of hydrogen and helium atoms, especially for helium. The less lattice distortion caused by the impurity atom, the more favorable for the dislocation loop to trap it. In addition, the larger dislocation loop with higher defect concentration results in stronger capture ability for the hydrogen and helium atoms. The different dislocation loop shapes lead to different binding energy distribution patterns. And the hydrogen and helium atoms tend to occupy the groove region of the concave dislocation loop. Finally, we employ the nudged elastic band theory and dynamics method to investigate the diffusion pattern of the hydrogen atom in the dislocation loop and find that the hydrogen atom tends to migrate spirally around dislocation line. Based on the obtained results, a reasonable interpretation of the interaction behaviors between the dislocation loop with hydrogen and helium atoms are discussed, which can provide essential parameters for mesoscopic scale simulations.
Microstructure and properties study of Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3) hydrogen storage alloys
Authors: Li Defa , Huang Feng , Zhang Wei , Li Yanzhou , Zhou Binjun 
Published: August 2023

Abstract
To enhance the hydrogen storage performance of Mg-Ni system alloys, multi-elemental alloys incorporating Y element, namely Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3), were synthesized through ball milling and sintering. The microstructures of Mg2-xYxNi0.9Co0.1 (x = 0, 0.1, 0.2, 0.3) alloys were characterized using XRD and SEM/EDS techniques, and the hydrogen storage properties of Mg2Ni0.9Co0.1 and Mg1.7Y0.3Ni0.9Co0.1 alloys were evaluated via the Sieverts method. At a sintering temperature of 500 °C, the Y element existed in the form of Y/Y2O3 phases and displayed no reactivity with other alloy constituents. The addition of Y enhanced the activation performance of Mg-Ni system alloys, because it takes 2 times for Mg1.7Y0.3Ni0.9Co0.1 alloy to complete activation, while Mg2Ni0.9Co0.1 needs 3, albeit causing a slight reduction from 3.6 wt% to 3.2 wt% in the hydrogen storage capacity when Y replaced Mg. The enthalpy of hydrogen desorption of Mg1.7Y0.3Ni0.9Co0.1 alloy was 57.4 kJ mol−1 H2, which was significantly lower than that of Mg2Ni0.9Co0.1 (68.0 kJ mol−1 H2) and Mg2Ni alloy (64.4 kJ mol−1 H2), indicating improved thermodynamic properties. Moreover, the apparent activation energy of Mg2Ni0.9Co0.1 (71.48 kJ mol−1 H2) was lower than that of Mg1.7Y0.3Ni0.9Co0.1 (83.62 kJ mol−1 H2), implying that the addition of Y reduced the kinetic properties.
Error scaling laws for kernel classification under source and capacity conditions
Authors: Cui Hugo , Loureiro Bruno , Krzakala Florent , Zdeborová Lenka 
Published: August 2023

Abstract
In this manuscript we consider the problem of kernel classification. While worst-case bounds on the decay rate of the prediction error with the number of samples are known for some classifiers, they often fail to accurately describe the learning curves of real data sets. In this work, we consider the important class of data sets satisfying the standard source and capacity conditions, comprising a number of real data sets as we show numerically. Under the Gaussian design, we derive the decay rates for the misclassification (prediction) error as a function of the source and capacity coefficients. We do so for two standard kernel classification settings, namely margin-maximizing support vector machines and ridge classification, and contrast the two methods. We find that our rates tightly describe the learning curves for this class of data sets, and are also observed on real data. Our results can also be seen as an explicit prediction of the exponents of a scaling law for kernel classification that is accurate on some real datasets.
Reflection equivariant quantum neural networks for enhanced image classification
Authors: T West Maxwell , Sevior Martin , Usman Muhammad 
Published: August 2023

Abstract
Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding its scale up. In particular, there is an emerging body of work which suggests that generic, data agnostic quantum machine learning (QML) architectures may suffer from severe trainability issues, with the gradient of typical variational parameters vanishing exponentially in the number of qubits. Additionally, the high expressibility of QML models can lead to overfitting on training data and poor generalisation performance. A promising strategy to combat both of these difficulties is to construct models which explicitly respect the symmetries inherent in their data, so-called geometric quantum machine learning (GQML). In this work, we utilise the techniques of GQML for the task of image classification, building new QML models which are equivariant with respect to reflections of the images. We find that these networks are capable of consistently and significantly outperforming generic ansatze on complicated real-world image datasets, bringing high-resolution image classification via quantum computers closer to reality. Our work highlights a potential pathway for the future development and implementation of powerful QML models which directly exploit the symmetries of data.