bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning assisted understanding of the layer-thickness dependent thermal conductivity in fluorinated graphene
Authors: Liang Jun-Nan , Tong Hua , Zeng Yu-Jia , Zhou Wu-Xing 
Published: July 2024

Abstract
Manipulating thermal conductivity (κ) plays vital role in high-performance thermoelectric conversion, thermal insulation and thermal management devices. In this work, we using the machine learning-based interatomic potential and the phonon Boltzmann transport equation to systematically investigate layer thickness dependent κ of fluorinated graphene (FG). We show that the lattice κ of FG can be significantly decreased with Bernal bilayer stacking. Surprisingly, the further increasing of stacking layer can no longer affect the κ, however, the κ is increased in the bulk configuration. The variation of κ can be attributed to the crystal symmetry change from P-3m1 (164) at single layer to P3m1 (156) at multilayer. The decreasing crystal symmetry from single layer to bilayer resulting stronger phonon scattering and thus leading a lower κ. Moreover, we also show that the contribution of acoustic mode to κ decreases with the increase of layers, while the contribution of optical mode to κ is increased with increasing layers. These results provide a further understanding for the phonon scattering mechanism of layer thickness dependent κ.
A multi-sensor fusion framework for localization using LiDAR, IMU and RGB-D camera
Authors: Guan Meng , Hao ZhiLong , Zhang Shitong , Chen Songming 
Published: July 2024

Abstract
In recent years, the increasing demand for precise and intelligent systems has been driven by advancements in indoor unmanned navigation and positioning technologies. Nonetheless, the indoor environment poses challenges as objects often intersect or obstruct each other due to spatial constraints, significantly impeding sensor recognition capabilities and compromising localization accuracy. This paper presented a multi-sensor fusion framework within a system primarily comprised of LiDAR, complemented by RGB-D and IMU sensors, to mitigate these challenges. To mitigate point cloud misalignment arising from occlusions, an improved PL-ICP algorithm have been proposed,resulting in improved accuracy and speed in occlusion scenarios. Meanwhile, this paper enhanced the Otsu algorithm by leveraging RGB-D matching to extract additional feature information, consequently enhancing the system’s convergence when occlusion happens. Ultimately, the Extended Kalman Filter (EKF) algorithm is employed to fuse point cloud and image data. Extensive experimental results demonstrate that the proposed approach not only enhances localization accuracy and stability but also exhibits superior convergence characteristics, offering an economical and efficient solution for robotic navigation.
Attention mechanism based on deep learning for defect detection of wind turbine blade via multi-scale features
Authors: Zhang Yu , Fang Yu , Gao Weiwei , Liu Xintian , Yang Hao , Tong Yimin , Wang Manyi 
Published: July 2024

Abstract
An enhanced wind turbine blade surface defect detection algorithm, CGIW-YOLOv8, has been introduced to tackle the problems of uneven distribution of defect samples, confusion between defects and background, and variations in target scales that arise during drone maintenance of wind turbine blades. This algorithm is given based on the YOLOv8 model. Initially, a data augmentation method based on geometric changes and Poisson mixing was used to enrich the dataset and address the problem of uneven sample distribution. Subsequently, the incorporation of the Coordinate Attention (CA) mechanism into the Backbone network improved the feature extraction capability in complex backgrounds. In the Neck, the Reparameterized Generalized Feature Pyramid Network (Rep-GFPN) was introduced as a path fusion strategy and multiple cross-scale connections are fused, which effectively enhances the multi-scale expression ability of the network. Finally, the original CIOU loss function was replaced with Inner-WIoU, which was created by applying the Inner-IoU loss function to the Wise-IoU loss function. It improved detection accuracy while simultaneously speeding up the model’s rate of convergence. Experimental results show that the mAP of the method for defect detection reaches 92%, which is 5.5% higher than the baseline network. The detection speed is 120.5 FPS, which meets the needs of real-time detection.
Soldered chip reversed polarity detection based on semi-combinatorial attention and size-sensitive IoU
Authors: Zheng Liming , Wu Yuxiang , Chen Enze 
Published: July 2024

Abstract
Chips that have been automatically soldered may have defects such as short circuits, reversed polarity, offsets, and missing components. This paper proposes a reversed polarity detection algorithm (RPDNet) for soldered chips based on semi-combinatorial attention and size-sensitive IoU to solve the polarity reversal problem. To distinguish characters or patterns similar to polarity markings in the background, a semi-combination attention module (SCAM) is introduced, which effectively distinguishes the subtle feature differences between polarity markings and background elements by integrating the long-range dependence of the self-attention mechanism and the local focusing ability of the general attention mechanism, thereby reducing misdetection of polarity markings. Aiming at the problem of blurred chip polarity markings, a differential pooling module (DPM) is proposed, which optimizes the downsampling process of fuzzy polarity markings by combining the differential features obtained from subtracting the results of max pooling from average pooling with features derived solely from average pooling, thereby reducing the information loss of fuzzy markings during the feature extraction process. In order to solve the lack of sensitivity of CIoU to the side length of the bounding box, a size-sensitive IoU (SIoU) is introduced. Through the size-sensitivity factor and area difference loss term, the model strengthens the focus on boundary regression and achieves faster and more accurate target positioning. Using the Chip-Set provided by the company for experiments and tests, the detection accuracy reached 97.79% and the processing speed reached 107 FPS.
Semantic segmentation algorithm for video from UAV based on adaptive keyframe scheduling via similarity measurement
Authors: Gao Weiwei , Fan Bo , Fang Yu 
Published: July 2024

Abstract
Unmanned aerial vehicle (UAV) videos exhibit complex object motion features and significant differences between frame features. To solve the problems of feature information loss and drastic accuracy decline in applying the video semantic segmentation method based on the fixed-period update strategy of keyframes, a keyframe recognition method based on similarity measurement is proposed, forming a video semantic segmentation algorithm based on adaptive keyframe scheduling. One keyframe recognition method based on pixel similarity measurement is established by modeling the similarity relationship between low-level pixels in adjacent frames. Meanwhile, the other keyframe recognition method based on feature similarity measurement is established by constructing a shallow Siamese network to measure the similarity relationship between features of frames. Then a discriminative network is constructed based on the obtained similarity of inter frames, and the segmentation process is accelerated by reusing features of keyframes through the optical flow network. Thereby a video semantic segmentation method for UAV based on adaptive keyframe strategy is established. The effectiveness of the proposed video semantic segmentation algorithm is verified on UAVid dataset. The results demonstrated that the speed of the proposed algorithm reaches 53.2 frames per second (FPS) and 54.5 FPS on the premise that the mean intersection over union is higher than 40% (this value is compared with the segmentation accuracy in the balanced mode when the similarity threshold is 0.76 and 0.88, respectively), which is 18.5 FPS and 19.8 FPS higher than the PSPNet image semantic segmentation algorithm. In addition, analysis of experiment results shows that the pixel-similarity-based keyframe recognition is suitable for high-precision video semantic segmentation scenes that need to improve segmentation efficiency, and the feature-similarity-based keyframe recognition is more suitable for high real-time video semantic segmentation tasks that require a small decrease in overall algorithm accuracy. In a word, the proposed video semantic segmentation algorithm based on adaptive keyframe scheduling via similarity measurement can improve segmentation speed while ensuring segmentation accuracy and stability.
Thermodynamic analysis of a heat engine: experiments with the Stirling cycle
Authors: Butler Colin 
Published: July 2024

Abstract
This paper presents a practical thermodynamic analysis of a desktop Stirling engine to demonstrate some of the fundamental principles involving the conversion of heat to work as part of an introductory undergraduate course. Experimental measurements of temperature, pressure and volume using an Arduino microcontroller allows for the construction of P-ν and T-s process diagrams from thermodynamic relationships. By comparing the quantitative data from actual and ideal cycles, the Stirling engine represents an effective teaching tool for reinforcing core content with students.
DIY of dye cleaning from water using plasma and smartphone colorimetry
Authors: Dubey Shivam , Thakur Abhay Singh , Vaish Rahul 
Published: July 2024

Abstract
Plasma has been generated using high voltage DC transformer. This plasma was further utilized in dye aqueous solution. Smartphone-based colourimetry was utilized to quantify dye degradation. These handy experiments will be helpful to understand plasma, its generation and potential applications.
A low cost and simple webcam spectrometer for exploring the visible wavelengths of light
Authors: Cahill Gary 
Published: July 2024

Abstract
This paper presents a method for constructing a simple, cost-effective, and versatile spectrometer using readily available materials such as a basic webcam, a DVD, tin foil, a cardboard tube, and a microphone boom arm. Building upon previous designs (Widiatmoko et al 2011 Phys. Educ.
46 332, Lorenz 2014 Am. J. Phys.
82 169–73, Rodrigues et al 2016 Phys. Educ.
51 014002, Likith et al 2021 J. Opt.
50 489–94), this spectrometer is mounted on a microphone boom arm, enhancing flexibility in capturing spectra from various angles and distant light sources. The spectrometer, coupled with Theremino Spectrometer V3.1 software, achieves sufficient resolution to measure solar Fraunhofer lines and closely spaced Mercury double lines at 436 nm and 577 nm. The procedure for assembling the spectrometer is detailed, including calibration using a Mercury CFL lamp or phone screens. Results demonstrate the spectrometer’s capability to capture high-resolution spectra of the blue sky and light sources, identifying significant spectral lines. This DIY spectrometer offers an accessible tool for amateur scientists and educators to explore visible light spectra, facilitating both qualitative and quantitative analyses. Also, through measuring the light from phone screens work, perception of colour can be explored.
Fundamental properties of ideal and resistive infernal modes in tokamaks
Authors: Coste-Sarguet M , Graves J P 
Published: July 2024

Abstract
Infernal modes are unstable in regions of weak magnetic shear and significant pressure gradients. These modes comprise a broad class of instabilities, encompassing interchange modes and kink modes, with both short and long length scales. Toroidal effects and fully electromagnetic fields are of crucial importance for their description. The role of resistive diffusion and compressibility are also critical. In order to investigate this awkward problem while still enabling fundamental physics interpretation, a new resistive MHD eigensolver has been developed. An outcome of this study is the identification of an unstable spectrum of resistive infernal modes in regions of the plasma with weak average curvature, and in regions where the average curvature is destabilising. These fast growing modes may be collectively important for our understanding of global reconnection events, stochastic magnetic fields states, and neighbouring supercritical bifurcations.
Hidden corrosion monitoring via phase shift evaluation of Lamb wave modes
Authors: Huang Liping , Zeng Liang , Zhang Xuhui , Wan Xiang , Chen Feiyu 
Published: July 2024

Abstract
Lamb wave inspection is a promising candidate for real-time monitoring of hidden corrosion in thin-walled metallic structures. The time-of-flight (ToF) which represents the variation of group velocity due to thickness reduction is commonly used, but its sensitivity is limited at the early stage of corrosion. To address this issue, the phase shift as a function of the phase velocity is defined and evaluated for corrosion detection in this paper. Specifically, the analytic cross-correlation method is applied, which estimates the group delay and the phase shift between two Lamb wave responses before and after the existence of corrosion simultaneously. The simulated examples show that the phase shift performs an obvious improvement on corrosion sensitivity compared to the ToF, and its value increases nearly linearly as the corrosion gets deeper. Ultimately, an experimental example is also introduced, where an active sensor network is deployed and a probabilistic imaging algorithm is introduced. The imaging results demonstrate that the proposed method could successfully identify and accurately localize the hidden corrosion.
A flexible piezoelectric energy harvester featuring an eccentric pendulum via frequency up-conversion for human motion
Authors: Zhu Yue , Chen Gantong , Zhang Jiaqin , Li Zhiyuan , Zhou Shengxi 
Published: July 2024

Abstract
This paper presents an innovative design of a flexible piezoelectric energy harvester featuring an eccentric pendulum (FPEH-P), which has two major characteristics: frequency up-conversion and large deformation that can improve output capacity. To clarify operational principles, we establish a dynamic model of the pendulum, and the vibration of the flexible piezoelectric plate is analyzed. Then, the two major characteristics of the FPEH-P are verified by experiments and simulations. Furthermore, it is verified that the FPEH-P can work at a low frequency (about 2 Hz) experimentally. Due to the large deformation of the piezoelectric plate, the maximum peak open-circuit voltage can reach 6.82 V. At an excitation frequency of 1.9 Hz and amplitude of 100 mm, the maximum average power can reach 6.06 μW. The FPEH-P can efficiently harvest energy from individuals engaged in walking, jogging, and running, as evidenced by the output load voltage and average power. Moreover, it can also output voltage under multiple motion actions. Finally, it has been verified that the high-instantaneous voltage characteristic of the harvester can provide sustainable power to a timer.
Anodization-free fabrication process for high-quality cross-type Josephson tunnel junctions based on a Nb/Al-AlO
x
/Nb trilayer
Authors: Adam F , Enss C , Kempf S 
Published: July 2024

Abstract
Josephson tunnel junctions form the basis for various superconductor electronic devices. For this reason, enormous efforts are routinely taken to establish and later on maintain a scalable and reproducible wafer-scale manufacturing process for high-quality Josephson junctions. Here, we present an anodization-free fabrication process for Nb/Al-AlO
x
/Nb cross-type Josephson junctions that requires only a small number of process steps and that is in general intrinsically compatible with wafer-scale fabrication. We show that the fabricated junctions are of very high quality and, compared to other junction types, exhibit not only a significantly reduced capacitance but also an almost rectangular critical current density profile. Our process hence enables the usage of low capacitance Josephson junctions for superconductor electronic devices such as ultra-low noise dc-superconducting quantum interference devices (SQUIDs), microwave SQUID multiplexers based on non-hysteretic rf-SQUIDs and RFSQ circuits.
Investigation of normal zone propagation velocity in AgSn/Ag/Ba122 superconducting tapes using a conduction cooling test system
Authors: Li Chunyan , Zhou Jin , Zhao Ling , Zhu Yanchang , Kang Rui , Li Wei , Wang Chengtao , Wang Yingzhe , Wang Juan , Hou Zhilong , Ma Rui , Zhang Hongjun , Liao Kai , Zhang Xianping , Wang Dongliang , Liu Fang , Ma Yanwei , Xu Qingjin 
Published: July 2024

Abstract
The investigation of the behavior of quench propagation in iron-based superconducting (IBS) tapes is important for their application in magnets and the design of quench protection systems. However, little research has been done in this area. In this work, a conduction cooling test system for IBS tapes and coils has been built, which has functions such as charging test, temperature and voltage data acquisition, pulse current heating, quench detection and protection. A series of experiments were performed on several 27 cm long IBS tapes to measure their normal zone propagation velocity (NZPV). The variation trends of NZPV with different operating temperatures, and with different ratios of operating current to critical current were systematically explored. In addition, monitoring all the voltages between different positions of an IBS tape, including two joints, has provided more detailed results and findings.
Unconventional edge states in a two-leg ladder
Authors: Downing C A , Martín-Moreno L , Fox O I R 
Published: July 2024

Abstract
Some popular mechanisms for restricting the diffusion of waves include introducing disorder (to provoke Anderson localization) and engineering topologically non-trivial phases (to allow for topological edge states to form). However, other methods for inducing somewhat localized states in elementary lattice models have been historically much less studied. Here we show how edge states can emerge within a simple two-leg ladder of coupled harmonic oscillators, where it is important to include interactions beyond those at the nearest neighbor range. Remarkably, depending upon the interplay between the coupling strength along the rungs of the ladder and the next-nearest neighbor coupling strength along one side of the ladder, edge states can indeed appear at particular energies. In a wonderful manifestation of a type of bulk-edge correspondence, these edge state energies correspond to the quantum number for which additional stationary points appear in the continuum bandstructure of the equivalent problem studied with periodic boundary conditions. Our theoretical results are relevant to a swathe of classical or quantum lattice model simulators, such that the proposed edge states may be useful for applications including waveguiding in metamaterials and quantum transport.
Pressure tuning of superconductivity in TiN thin films
Authors: Zhang Yuqing , Yang Ye , Wen Xikai , Gui Zhigang , Li Yikang , Li Yanjun , Zhang Ruyi , Cao Yanwei , Ying Jianjun , Chen Xianhui 
Published: July 2024

Abstract
Titanium nitride (TiN) thin films are used for the fabrication of superconducting devices due to their chemical stability against oxidization and high quality at interfaces. The high-pressure technique serves as a useful tool to understand the mechanical and electrical properties of materials, which is crucial for practical applications. However, high-pressure transport measurements of thin films are extremely difficult due to the limited sample space of high-pressure cells and the fragility of thin films. Here, we successfully carried out high-pressure electrical transport and Raman measurements on TiN films up to ∼50 GPa. The superconducting transition temperature gradually decreases with increasing pressure, which can be attributed to the decrease of electron -phonon coupling and is consistent with our first-principles calculations. In addition, the coexistence of a symmetry-enforced Dirac nodal chain and a nodal box is revealed by our calculations in TiN. Our work provides a promising way to study the physical properties of thin films at high pressure, which would broaden the high-pressure research field.
First principle investigations of opto-electronic and thermoelectric response of A2TlAsX6 (A = K, Rb; X = Cl, Br) compounds
Authors: Rangar Kailash , Soni Amit , Sahariya Jagrati 
Published: July 2024

Abstract
We have investigated the structural, electronic, optical, and thermoelectric behavior of halide-based double perovskites A2TlAsX6 (A = K, Rb; X = Cl, Br) compounds to reveal their potential in various opto-electronic and thermoelectric applications using first-principle calculations. For the computation of the various properties of A2TlAsX6 (A = K, Rb; X = Cl, Br) compounds, we have used approximations available within density functional theory (DFT). The energy bands and density of states have been used to elucidate the electronic response of the studied compounds, while the interpretation of optical properties is presented in terms of dielectric tensor, absorption coefficient, reflectivity, refraction and energy loss spectra. The investigated compounds exhibit a direct band gap within the energy range of 1.36 to 2.24 eV, indicating the promising nature of these compounds for diverse optoelectronic applications. Moreover, thermoelectric properties such as the figure of merit, power factor, Seebeck coefficient, specific heat, electric and thermal conductivity have also been computed for the studied compounds. Our investigation unveils the remarkable optoelectronic characteristics of the studied perovskites, which can be attributed to their advantageous bandgap and highly effective light absorption capabilities. Furthermore, these perovskites showcase exceptional thermodynamic stability, elevated electrical conductivity, favorable figure of merit (ZT) values, and reduced thermal conductivities. These findings suggest their suitability for applications in optoelectronic devices and thermoelectric applications. In this study, it is found that A2TlAsBr6 compounds exhibit significant absorption in the visible spectrum, rendering them more favorable for optoelectronic applications compared to A2TlAsCl6 compounds. Conversely, for thermoelectric applications, the Cl-based perovskites studied show greater promise than their Br-based counterparts. The modified Becke–Johnson (mBJ) potential emerges as the most precise approach for analyzing the electronic, optical, and thermoelectric characteristics of A2TlAsX6 (where A = K, Rb; X = Cl, Br) perovskites, surpassing other approximations utilized in present study.