bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uniqueness of an inverse cavity scattering problem for the time-harmonic biharmonic wave equation
Authors: Dong Heping , Li Peijun 
Published: April 2024

Abstract
This paper addresses an inverse cavity scattering problem associated with the time-harmonic biharmonic wave equation in two dimensions. The objective is to determine the domain or shape of the cavity. The Green’s representations are demonstrated for the solution to the boundary value problem, and the one-to-one correspondence is confirmed between the Helmholtz component of biharmonic waves and the resulting far-field patterns. Two mixed reciprocity relations are deduced, linking the scattered field generated by plane waves to the far-field pattern produced by various types of point sources. Furthermore, the symmetry relations are explored for the scattered fields generated by point sources. Finally, we present two uniqueness results for the inverse problem by utilizing both far-field patterns and phaseless near-field data.
Effect of polarization on tunnelling electroresistance in ferroelectric tunnel junctions
Authors: Ge Tongxin , Wei Haoming , Wu Yangqing , Yang Tengzhou , Cao Bingqiang 
Published: April 2024

Abstract
High-quality epitaxial BiFeO3 (BFO) films were grown on (001)-, (110)- and (111)-oriented Nb:SrTiO3 (NSTO) substrates by pulsed laser deposition. The type of domain structure can be modulated using BFO ferroelectric films with different crystalline orientations. The ON/OFF ratios obtained in (001)-, (110)- and (111)-oriented Au/BFO/NSTO ferroelectric tunnel junctions (FTJs) are 6 × 103, 3 × 104 and 2 × 105, respectively. Analysis of the I–V curves of tunnelling current and average BFO ferroelectric barrier height proves that the polarization intensity of the BFO films modulates both the ferroelectric barrier and the Schottky barrier profile, which further influences the electronic tunnelling probability in BFO FTJs. This work will be useful for further study on achieving a giant ON/OFF ratio and developing insights into the barrier profile and transport mechanism of metal/ferroelectric/semiconductor-type FTJs.
A synergistic combination of 2D MXene and MoO3 nanoparticles for improved gas sensing at room temperature
Authors: Kale Shravani , Sabale Dhanashri , Srivastava Rajat , Londhe Vaishali Phatak , Kale S N 
Published: April 2024

Abstract
MXene Ti3C2T
x
(30% HF-etched, named Ti3C2T
x
-30) plays a pivotal role in the substantial enhancement of the structural modification of molybdenum trioxide (MoO3). Additionally, as the surface MoO3 molecules come into contact with reducing gas moieties, they actively participate in gas sensing at room temperature. The percentage of Ti3C2T
x
-30 in the MoO3 matrix was varied at 10%, 20%, and 40%, denoted as MM-10, MM-20, and MM-40, respectively. Structural analysis confirmed the composition of the basic elements and evolution of TiO2 at a higher percentage of Ti3C2T
x
-30. Spectroscopy analysis showed the interactions between Ti3C2T
x
-30 and MoO3, showcasing work functions of 6.91 eV, 6.75 eV, and 7.21 eV for MM-10, MM-20, and MM-40, respectively, confirming MM-20 to be an optimum composition. When the samples were exposed to ammonia gas, MM-20 showed a high response (93% for 100 ppm) at room temperature, with a response time of ∼10 s. Compared to bare MoO3, these samples showed ten-fold improvement. The excess electrons on the surface of Ti3C2T
x
-30 facilitate the formation of O2− species, which also provides stability to the otherwise highly reactive MXene surface. These species actively react with ammonia molecules in the presence of adsorbed MoO3, thereby changing the resistance of the system. This can be a significant step towards imparting high gas sensitivity to metal oxides at room temperature via incorporation of an optimum percentage of optimized Ti3C2T
x
.
Synthesis of ZnO and ZnO/Ag fine particles by plasma-assisted inkjet processing
Authors: Hato Takeru , Nitta Kaishu , Muneoka Hitoshi , Shimizu Yoshiki , Terashima Kazuo , Ito Tsuyohito 
Published: April 2024

Abstract
Zinc oxide (ZnO) and its composite particles with controlled sizes, shapes, compositions, and physical and chemical properties are required for a wide variety of applications. In this study, we report a simple method for synthesising ZnO and ZnO/Ag composite particles via atmospheric-pressure plasma processing using inkjet droplets. Depending on the initial solution concentration, ZnO particles containing voids, with average sizes ranging from submicrons to several microns can be synthesised. Energy dispersive x-ray spectroscopy measurements of the synthesised ZnO/Ag particles suggest that the molar ratio of Ag to Zn in the initial solution was retained in the synthesised particles. A high surface-enhanced Raman scattering effect was observed in the particles synthesised from the solution with an Ag molar ratio of 50% to the total solute. The proposed method enables the synthesis of ZnO particles of various sizes, microstructures, compositions and optical properties with relatively narrow size distributions.
Enhanced second harmonic generation from supercavity mode and magnetic resonance in dumbbell-shaped silicon nanoblock
Authors: Yuan Yuwei , Zheng Yunbao , Ouyang Min , Fan Haihua , Dai Qiaofeng , Liu Haiying , Wu Lijun 
Published: April 2024

Abstract
Electromagnetic multipole resonance can be excited by dielectric nanostructures of appropriate size to effectively promote light-matter interaction. The interactions between light and nanostructures have the capability to enhance the electromagnetic near field, thereby improving the nonlinear effect of nanostructures. We illustrate that the supercavity mode and magnetic dipole (MD) resonance are activated by a single dumbbell-shaped silicon nanoblock, to trap the near-field electromagnetic field energy. Enhanced second harmonic generation (SHG) is achieved by exploiting the localized electromagnetic field at the surface of the nanostructure. Numerical simulations reveal that magnetic quadrupole (MQ) and total electric dipole (TED) can be coupled to the same radiation channel by adjusting continuously the aspect ratio L
out/Ly
(the outer edge length to the length of the nanoblock) of the nanoblock. When the aspect ratio L
out/L
y = 1, the supercavity mode formed by the interference of MQ and TED is excited at λ
1 = 1124 nm. And, the strong magnetic resonance mode formed by the coupling of two MDs in the same direction is also excited at λ
2 = 1248 nm. Supercavity mode and strong MD resonance can effectively capture electromagnetic fields on the surface of nanostructures to attain enhanced SHG. Our study presents a novel approach to enhance the nonlinear optical effect of a single silicon nanostructure, which can lead to the development of more efficient nonlinear optical devices.
Random broadband filters based on combination of metasurface and multilayer thin films for hyperspectral imaging
Authors: Guo Kai , Yang Duo , Liu Bingyi , Guo Zhongyi 
Published: April 2024

Abstract
Metasurface based micro-spectrometer presents a promising avenue for achieving compact, lightweight, and cost-effective solutions for miniaturization of hyperspectral imaging systems. Nevertheless, this type of design encounter limitations primarily due to constrained manipulation mechanism of light field, resulting in high cross-correlation among transmission spectra and imperfect reconstructed images. In this paper, we propose and numerically demonstrate a micro-spectrometer based on metasurface combined with multilayer thin films, whose spectral response improves performance for application, i.e. achieving low spectral cross-correlation. Additionally, we incorporate particle swarm optimization with compressed sensing algorithm to optimize the proposed micro-spectrometer. This approach effectively reconstructs both narrowband and broadband hyperspectral signals with minimal error, achieving an impressive 2 nm spectral resolution. The simulation results of hyperspectral imaging demonstrated that the proposed methodology successfully reconstructs broadband hyperspectral images with an average spectral fidelity of 91.42%. This method holds significant potential for integrating into smartphones and other portable spectrometers, advancing the design of compact hyperspectral imaging systems.
Secluded scalar dark matter and the muon anomalous magnetic moment
Authors: Ghorbani Karim 
Published: April 2024

Abstract
We consider a dark matter (DM) model with a singlet scalar, χ, as our DM candidate, which is secluded from the standard model (SM) and annihilates to the singlet scalar, ϕ, via a contact interaction. The singlet scalar, ϕ, has a leptophilic interaction with the SM leptons and may decay leptonically at tree level, and decays into a pair of photons at loop level. The focus of this work is to consider DM masses below 10 GeV. A viable secluded region is found in the parameter space after imposing the observed relic density. There is a one-loop interaction between scalar DM and the atomic electron in this model. We then apply the available direct detection bounds from Xenon10, Xenon1T and DarkSide on the DM-electron elastic scattering cross section. While the model can explain the muon anomalous magnetic moment, we apply bounds from current and future lepton collider experiments.
Electride pure α-Zr: interstitial electrons induced type-II nodal line
Authors: Jiang Jiayu , Meng Weizhen , Jin Lei , Gao Hongli , Zhang Xiaoming 
Published: April 2024

Abstract
Electrides have attracted significant attention in the fields of physics, materials science, and chemistry due to their distinctive electron properties characterized by weak nuclear binding. In this study, based on first-principles calculations and symmetry analysis, we report that the pure zirconium with alpha-phase (α-Zr) is expected to be the electrically neutral electride with topological nodal loop. Furthermore, the nodal loop located at the kz
= 0 plane exhibits a clear drumhead-like surface state. The energy levels of the topological nodal loop can be regulated by applying uniaxial strain, resulting in the topological nodal loop being closer to the Fermi level. Remarkably, the work function of the electride Zr shows a significant anisotropy along the (001), (100), and (110) directions, particularly with a low work function of 3.14 eV along the (110) surface. Therefore, we predict that α-Zr provides a promising platform for future research on topological electrides.
Moiré band renormalization due to lattice mismatch in bilayer graphene
Authors: Zhu Xingchuan , Sun Junsong , Feng Shiping , Guo Huaiming 
Published: April 2024

Abstract
We investigated the band renormalization caused by the compressive-strain-induced lattice mismatch in parallel AA stacked bilayer graphene using two complementary methods: the tight-binding approach and the low-energy continuum theory. While a large mismatch does not alter the low-energy bands, a small one reduces the bandwidth of the low-energy bands along with a decrease in the Fermi velocity. In the tiny-mismatch regime, the low-energy continuum theory reveals that the long-period moiré pattern extensively renormalizes the low-energy bands, resulting in a significant reduction of bandwidth. Meanwhile, the Fermi velocity exhibits an oscillatory behavior and approaches zero at specific mismatches. However, the resulting low-energy bands are not perfectly isolated flat, as seen in twisted bilayer graphene at magic angles. These findings provide a deeper understanding of moiré physics and offer valuable guidance for related experimental studies in creating moiré superlattices using two-dimensional van der Waals heterostructures.
Migdal–Eliashberg superconductivity in a Kondo lattice
Authors: Awelewa Samuel , Dzero Maxim 
Published: April 2024

Abstract
We apply the Migdal–Eliashberg theory of superconductivity to heavy-fermion and mixed valence materials. Specifically, we extend the Anderson lattice model to a case when there exists a strong coupling between itinerant electrons and lattice vibrations. Using the saddle-point approximation, we derive a set of coupled nonlinear equations which describe competition between the crossover to a heavy-fermion or mixed-valence regimes and conventional superconductivity. We find that superconductivity at strong coupling emerges on par with the development of the many-body coherence in a Kondo lattice. Superconductivity is gradually suppressed with the onset of the Kondo screening and for strong electron-phonon coupling the Kondo screening exhibits a characteristic re-entrant behavior. Even though for both weak and strong coupling limits the suppression of superconductivity is weaker in the mixed-valence regime compared to the local moment one, superconducting critical temperature still remains nonzero. In the weak coupling limit the onset of the many body coherence develops gradually, in the strong coupling limit it emerges abruptly in the mixed valence regime while in the local moment regime the f-electrons remain effectively decoupled from the conduction electrons. Possibility of experimental realization of these effects in Ce-based compounds is also discussed.
Spin-disorder intervened avoidance of quantum criticality in B20 cubic Mn
1−xVx
Si
Authors: Khandelwal Parul , Shanmukharao Samatham S , Babu P D , Suresh K G 
Published: April 2024

Abstract
The effect of negative chemical pressure with the substitution of transition metal V in an itinerant helimagnetically ordered MnSi, Mn

1
−
x

V
x
Si with x = 0–0.1, is explored using dc and ac-susceptibilities. With increasing x, the manifestations are unaffected crystal structure with increasing unit cell volume, suppression of long-range magnetic order, weakening of itinerant character and reduced spin-cooperative phenomenon. The emergence of spin-glass behaviour for

x
⩾
0.1

intervenes in the occurrence of quantum phase transition. The constructed concentration-temperature x-T phase diagram illustrates the substitution-driven changes in the magnetism of MnSi. Further, the study suggests that the presence of a precursor state can favour the formation of spin-textures in magnetically ordered compositions

0
<
x
⩽
0.05

below the ordering temperature.
A multichannel analysis of imbalanced computed tomography data for lung cancer classification
Authors: Sohaib Muhammad , Hasan Md Junayed , Zheng Zhonglong 
Published: April 2024

Abstract
Lung cancer holds the highest fatality rate among cancers, emphasizing the importance of early detection. Computer algorithms have gained prominence across various domains, including lung cancer diagnosis. These algorithms assist specialists, especially in medical imaging, yet current efforts lack comprehensive CT data analysis; especially in handling imbalanced datasets and fully exploiting spatial information. The lack of spatial analysis hinders the ability to identify subtle variations in texture and structure that are crucial for detecting lung cancer early and accurately. Therefore, this study uses a multichannel analysis of computed tomography (CT) images and deep learning-based ensemble learning (MC-ECNN) to find lung cancer even when the data is not balanced. Firstly, the data imbalance issue is tackled through the synthetic minority oversampling technique (SOMTE); afterwards, a multi-channel analysis of the data is performed to explore a distinct set of abstract features. Lastly, a deep ensemble learning method is used to classify the extracted distinct abstract feature set into the appropriate classes. The proposed method uses the discrete Fast Fourier transform (DFFT) and discrete cosine transform (DCT), along with the actual CT scans, for the multi-channel analysis of the data in different domains. The proposed model yielded 99.60% test accuracy on unseen data, which is at least 3% better than the other state-of-the-art studies considered for the comparison. In addition to the classification accuracy, the efficacy of the proposed model has also been justified through precision, recall, F1-score, support value, and misclassification rate.
Innovative integration of multi-scale residual networks and MK-MMD for enhanced feature representation in fault diagnosis
Authors: Li Xueyi , Yuan Peng , Su Kaiyu , Li Daiyou , Xie Zhijie , Kong Xiangwei 
Published: April 2024

Abstract
This article proposes a method based on multi-scale expansion of residual neural networks (ResNets) to address challenges in the operation of rotating components, such as bearings and gears, under complex conditions where they are often affected by environmental noise. This interference leads to weaker fault characteristics, making feature selection difficult and increasing the presence of extraneous information features. To tackle this issue, the proposed method first employs a multi-scale feature ResNet to extract features from vibration signals of rotating machinery. The method decomposes the signal into multiple sub-signals of different scales, extracting local features at each scale. It then uses residual connections to combine these local features to obtain a global feature representation. Furthermore, the article introduces a construction of the maximum mean discrepancy (MMD) and minimization of entropy boundaries to adapt to the differences between two domains. The method utilizes multiple kernel functions to calculate distances between data at different scales and combines these distances to obtain a comprehensive measure. By employing the MMD and minimization of entropy boundary approach, the method can more accurately determine whether signals at different scales belong to the same category, thereby improving diagnostic accuracy and robustness. Experimental results demonstrate the effectiveness of the proposed method in unsupervised cross-domain fault diagnosis tasks. Future work will focus on further optimizing the architecture of ResNets, enhancing feature extraction capabilities, and exploring advanced data augmentation methods to further improve the model’s generalization performance.
MF-LIO: integrating multi-feature LiDAR inertial odometry with FPFH loop closure in SLAM
Authors: Song Shuai , Shi Xiaojun , Ma Chunyun , Mei Xuesong 
Published: April 2024

Abstract
Simultaneous localization and mapping (SLAM) is a pivotal technology in autonomous vehicle navigation and a significant research area in robotics. Addressing the inaccuracies in point cloud registration of traditional LiDAR SLAM, which lead to localization and mapping errors, we propose a novel LiDAR inertial odometry approach integrating inertial measurement units and a multi-feature joint registration strategy. Initially, we introduce an innovative ground segmentation method and feature categorization strategy, enhancing ground detection mechanisms and optimizing the feature extraction process. Subsequently, our multi-feature joint registration method computes the pose transformations between current frames and the local map. Finally, we employ a global registration method based on fast point feature histograms feature descriptors for coarse alignment, providing initial estimates for the generalized iterative closest point algorithm, thus efficiently and accurately mitigating cumulative errors. Extensive evaluations on the KITTI dataset and real-world campus environment demonstrate that our approach significantly surpasses existing advanced LiDAR SLAM solutions, achieving over a 24% improvement in pose estimation accuracy.
Experimental dataset investigation of deep recurrent optical flow learning for particle image velocimetry: flow past a circular cylinder
Authors: Anjaneya Reddy Yuvarajendra , Wahl Joel , Sjödahl Mikael 
Published: April 2024

Abstract
Current optical flow-based neural networks for particle image velocimetry (PIV) are largely trained on synthetic datasets emulating real-world scenarios. While synthetic datasets provide greater control and variation than what can be achieved using experimental datasets for supervised learning, it requires a deeper understanding of how or what factors dictate the learning behaviors of deep neural networks for PIV. In this study, we investigate the performance of the recurrent all-pairs field transforms-PIV (RAFTs-PIV) network, the current state-of-the-art deep learning architecture for PIV, by testing it on unseen experimentally generated datasets. The results from RAFT-PIV are compared with a conventional cross-correlation-based method, Adaptive PIV. The experimental PIV datasets were generated for a typical scenario of flow past a circular cylinder in a rectangular channel. These test datasets encompassed variations in particle diameters, particle seeding densities, and flow speeds, all falling within the parameter range used for training RAFT-PIV. We also explore how different image pre-processing techniques can impact and potentially enhance the performance of RAFT-PIV on real-world datasets. Thorough testing with real-world experimental PIV datasets reveals the resilience of the optical flow-based method’s variations to PIV hyperparameters, in contrast to the conventional PIV technique. The ensemble-averaged root mean squared errors between the RAFT-PIV and Adaptive PIV estimations generally range between 0.5–2 (px) and show a slight reduction as particle densities increase or Reynolds numbers decrease. Furthermore, findings indicate that employing image pre-processing techniques to enhance input particle image quality does not improve RAFT-PIV predictions; instead, it incurs higher computational costs and impacts estimations of small-scale structures.
Terahertz emission mechanisms in low-temperature-grown and semi-insulating gallium arsenide photoconductive antenna devices excited at above- and below-bandgap photon energies
Authors: F Dela Rosa L N , Publico J B , F Cabello N I , R Ferrolino J P , P Juguilon V P , M Verona I C , Salvador A A , Somintac A S , De Los Reyes A E , Bardolaza H R , Estacio E S 
Published: April 2024

Abstract
In this work, the terahertz (THz) time-domain spectroscopy was employed in studying the carrier dynamics in low-temperature grown (LT-) and semi-insulating (SI-) gallium arsenide (GaAs) photoconductive antenna (PCA) at above- (

λ
=

780 nm,

E
g

=

1.59 eV) and below- (

λ
=

1.55 µm,

E
g

0.80 eV) bandgap excitation. We measured the excitation power dependence of the LT-GaAs (SI-GaAs) THz emission. Then, the equivalent circuit model which considers the (i) photogeneration, (ii) screening effects, and (iii) transport of carriers was utilized in analyzing the THz radiation mechanisms in the above- and below-bandgap excitation of the two substrates. In simulating the above-bandgap THz emission of both PCAs, we employed the direct bandgap excitation model which takes into account the band-to-band transitions of photoexcited carriers. Meanwhile, to simulate the LT-GaAs (SI-GaAs) THz emission at below-bandgap excitation we utilized the two-step photoabsorption facilitated by the mid-gap states. In this model the photoexcited carriers jump from the valence band to the mid-gap states and then to the conduction band. Results suggest that the THz emission from LT-GaAs and SI-GaAs at above- and below-bandgap excitation occur due to band-to-band transitions, and two-step photoabsorption process via midgap states, respectively.