bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical guidance on the assessment of radiation risks for diagnostic radiological examinations
Authors: Golikov V , Vodovatov A , Chipiga L , Shatskiy I
Published: August 2024

Patient doses cannot be limited; instead, radiological examinations should be justified and optimised to ensure the necessary diagnostic or therapeutic effect with the lowest patient dose achievable. Assessment of the radiation risks from patient exposure is important part of the justification process. Hence, medical staff within the framework of their professional activities should possess necessary information on the data on radiation risk from different types of radiological procedures. An approach has been developed that allows considering age and gender dependences of the risk coefficients of radiogenic cancer and the age and gender distribution of patients for various radiological examinations to assess the individual radiation risk for patient and collective risk for population from medical exposure. The approach is based on a new expanded use of the effective dose concept proposed in ICRP Publication 147 and demonstrated using the medical exposure in the Russian Federation as the example. For 30 radiological examinations that compose about 80% of the collective dose from medical exposure of the public in the Russian Federation radiation risk was assessed based on calculated age and gender specific risk coefficients per unit effective dose. For the rest of the examinations a simplified approach was used to assess the risk, which was based on using an age and gender specific risk coefficient determined for one of 4 anatomical regions (head, neck, chest and abdomen) or for uniform irradiation of the whole body. The proposed approach allows significantly improving the assessment of the radiation risk while continuing to use the effective dose as a dosimetric quantity within the framework of the state program in the Russian Federation. As a result the collective risk from medical examinations in the Russian Federation in 2022 was lower by the factor of 3 compared to the previous assessment based on the effective dose with the nominal risk coefficient.
A General and Efficient Fault Diagnosis Approach Using Hyperdimensional Computing Enhanced by Local Feature Extraction
Authors: Jiang Guoqian , Ma Zhenzhen , He Qun , Xie Ping
Published: August 2024

Ensuring the safe and reliable operation of industrial equipment is of great importance, and accordingly, machine fault diagnosis has attracted considerable attention. Recently, various deep learning-based fault diagnosis models have been widely developed due to the powerful ability of feature learning and nonlinear modeling of deep learning models, and these methods heavily rely on large amounts of data and high memory and resources. However, it is difficult to obtain enough data in practical applications, thus leading to the unsatisfactory performance of deep learning-based models and high cost. In this paper, we propose a new and efficient fault diagnosis approach based on Hyperdimensional computing (HDC), which can learn high-dimensional, random, and holographic distributed representations of input features. It has the advantages of single training, low training cost, and does not require a large amount of data. Therefore, we apply HDC to the field of few-shot fault diagnosis for the first time, and propose a simple and efficient approach for few-shot fault diagnosis based on hyperdimensional computing with local feature extraction(L-HDC). Instead of using original data, the model firstly extracts the local features of original data by hand-designed features, and then carries out HDC-encoding, training, and test classification. Through the comparison of various models and the analysis of various data, the effectiveness of our proposed model is verified. In the case of few-shot learning, the recognition accuracy is as high as 90\% and the training time of ordinary HDC model is 5-10 times that of L-HDC model, which is superior to other models.
Indoor fingerprint localization algorithm based on WKNN and LightGBM-GA
Authors: Zhang Lieping , Zheng Xinpeng , Chen Yao , Lu Haizhao , Zhang Cui
Published: August 2024

WiFi-based indoor fingerprint localization is widely used in indoor localization owing to its high accuracy and low deployment costs. Changes in the indoor signal environment directly affect localization accuracy. To improve localization accuracy and stability, this paper proposes a novel indoor fingerprint localization algorithm based on Weighted K-Nearest Neighbors (WKNN) and an enhanced Light Gradient Boosting Machine (LightGBM). First, in the offline phase, Gaussian filtering and K-Nearest Neighbors-Random Forest information completion algorithm with fusion of Euclidean and Manhattan distances are used to remove outliers from the fingerprint database dataset and fill in missing fingerprint information, ensuring the integrity of the fingerprint database. During the online phase, the fingerprint database is divided into training and testing sets. The LightGBM algorithm is used for modeling. Additionally, Genetic Algorithm (GA) is use d to optimize the parameters of LightGBM algorithm to find the best parameters by fitness evaluation. Then, the nearest neighbor set found by the WKNN algorithm is introduced into the LightGBM-GA model. Combining the predictions from the standalone LightGBM algorithm and performing weighted fusion yields the final predicted coordinates. The experiments are conducted in 8 m × 10 m laboratory containing 5 access points and 80 reference points to collect the Received Signal Strength Indication values of 5 WiFi hotspots. The experimental results show that the average localization error of the proposed algorithm is 1.11 m, which is reduced by 6.7%–38.3% compared to K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), LightGBM, KNN + XGBoost, WKNN + LightGBM, and WKNN + XGBoost-GA localization algorithms. The localization curve is smoother, and the cumulative distribution function converges faster. Moreover, the localization time is reduced by 13.3%–36.7%, effectively enhancing localization accuracy and decreasing localization time.
Nonlinear group constrained mode decomposition and its application in gear fault diagnosis
Authors: Yan Qiuyan , Liu Xuan , Wang Mingjun , Zou Yuxin
Published: August 2024

Due to the problem of modal confusion and extreme sensitivity to strong noise in signal decomposition using group-sparse mode decomposition, this paper proposes a new signal decomposition method, named nonlinear group constrained mode decomposition (NGCMD). First, NGCMD is based on modified discrete cosine transform, which enables the function to have ‘energy compression’ characteristics, resulting in a more approximate model of complex signals and avoiding the introduction of artifacts in frequency domain analysis. Meanwhile, the objective function adopts norm weighting as the penalty term, making the algorithm not only sparsity but also fast convergence. In addition, to maintain the adaptability of the algorithm, when the algorithm converges, the filter bank is decomposed into a set of non-overlapping filters, where each filter contains an adjacent non-zero term in the filter bank, and a series of sparse group constrained components with complete time–frequency distribution are obtained. Through the simulation signal and gear fault signal, the results show that the NGCMD method has obvious advantages in suppressing modal confusion and robustness, and can effectively diagnose gear fault.
PETcoil: first results from a second-generation RF-penetrable TOF-PET brain insert for simultaneous PET/MRI
Authors: Dong Qian , Ullah Muhammad Nasir , Innes Derek , Watkins Ronald D , Chang Chen-Ming , Zou Sarah J , Groll Andrew , Sacco Ilaria , Chinn Garry , Levin Craig S
Published: August 2024

Simultaneous positron emission tomography (PET)/magnetic resonance imaging provides concurrent information about anatomic, functional, and molecular changes in disease. We are developing a second generation MR-compatible RF-penetrable TOF-PET insert. The insert has a smaller scintillation crystal size and ring diameter compared to clinical whole-body PET scanners, resulting in higher spatial resolution and sensitivity. This paper reports the initial system performance of this full-ring PET insert. The global photopeak energy resolution and global coincidence time resolution, 11.74 ± 0.03 % FWHM and 238.1 ± 0.5 ps FWHM, respectively, are preserved as we scaled up the system to a full ring comprising 12, 288 LYSO-SiPM channels (crystal size: 3.2 × 3.2 × 20 mm3). Throughout a ten-hour experiment, the system performance remained stable, exhibiting a less than 1% change in all measured parameters. In a resolution phantom study, the system successfully resolved all 2.8 mm diameter rods, achieving an average VPR of 0.28 ± 0.08 without TOF and 0.24 ± 0.07 with TOF applied. Moreover, the implementation of TOF in the Hoffman phantom study also enhanced image quality. Initial MR compatibility studies of the full PET ring were performed with it unpowered as a milestone to focus on looking for material and geometry-related artifacts. During all MR studies, the MR body coil functioned as both the transmit and receive coil, and no observable artifacts were detected. As expected, using the body coil also as the RF receiver, MR image signal-to-noise ratio exhibited degradation (∼30%), so we are developing a high quality receive-only coil that resides inside the PET ring.
Finite orbit width effects on turbulent transport of ion parallel momentum
Authors: Li Yang
Published: August 2024

A kinetic model for ion turbulent parallel momentum transport is developed with finite orbit width effects for Tokamak plasmas. It is shown that the curvature and gradient drifts of ions can introduce pressure perturbations into the transport equation of ion parallel momentum, which leads to a new source term. And the source term can be understood as a Coriolis force and can play a key role in the toroidal symmetry breaking during the spontaneous spin-up process.
Design concept of intelligent integrated control system for neutral beam injection
Authors: Gu Yu , Hu Chundong , Li Yang , Zhao Yuanzhe , Cui Qinglong , Xie Yahong
Published: August 2024

Due to the specificity of neutral beam injection (NBI) system, the control of its actual physical system is achieved by the integrated control system (ICS). The current NBI ICS adopts a distributed design structure to balance the system load, which is also the mainstream system design and architecture model of ICS around the world. However, from a practical point of view, the distributed system architecture is not perfect. In the long run, upgrading the system intelligence and automation capabilities is an inevitable choice for the future, so it is necessary to explore ways to transform and upgrade the ICS. At present, Internet of Things (IoT), as an important part of the new generation information technology, can realize the control of everything through data exchange. This is because on the one hand, IoT has wide compatibility and powerful scenario-based capabilities, it not only has the advantages and characteristics of distributed design, but also can pull the NBI subsystems into the same level scenario and lay the foundation for the further construction of digital NBI; on the other hand, the intervention of artificial intelligence makes IoT have some new typical characteristics such as intelligent sensing, ubiquitous connectivity, precise control, digital modeling, real-time analysis and iterative optimization, which is enough to pull the current NBI ICS into a new intelligent control era. Finally, it is worth mentioning that due to its inherent design structure and functional characteristics, ICS tends to be broadly generic, so it is not exclusively used for NBI operation in nuclear fusion, and it can provide some insight into other application areas.
Emergent symmetry in TbTe3 revealed by ultrafast reflectivity under anisotropic strain
Authors: Kim Soyeun , Orenstein Gal , Singh Anisha G , Fisher Ian R , Reis David A , Trigo Mariano
Published: August 2024

We report ultrafast reflectivity measurements of the dynamics of the order parameter of the charge density wave (CDW) in TbTe3 under anisotropic strain. We observe an increase in the frequency of the amplitude mode with increasing tensile strain along the a-axis (which drives the lattice into a > c, with a and c the lattice constants), and similar behavior for tensile strain along c (c > a). This suggests that both strains stabilize the corresponding CDW order and further support the near equivalence of the CDW phases oriented in a- and c-axis, in spite of the orthorhombic space group. The results were analyzed within the time-dependent Ginzburg–Landau framework, which agrees well with the reflectivity dynamics. Our study presents an ultrafast approach to assess the stability of phases and order parameter dynamics in strained systems.
A class of memristive Hénon maps
Authors: Wang Zhihao , Li Chunbiao , Li Yongxin , Moroz Irene , Fu Haiyan
Published: August 2024

Memristor, the electronic component, is introduced in the Hénon map and is studied extensively. Several chaotic maps are proposed by constructing the memristors through nonlinear functions such as absolute value functions, trigonometric functions, and activation functions. It is found that in a part of the proposed chaotic maps, the local offset boosting of the system variable can be guided by a single parameter. Not only that, the generation of homogeneous multistability can be controlled by the initial conditions of the systems. Moreover, the number of homogeneous attractors produced changes when the system parameters are varied. In addition, the control of chaos can be achieved by adjusting the excitation fRequency of the memristor. The theoretical results and numerical laws presented in this paper are verified by circuit implementation based on the microcontroller unit.
Neural network approach to investigate heat transfer in SWCNTs nanofluid within trapezoidal cavity with varied corrugated rod amplitudes
Authors: Hussain Zakir , Fazia  , Anwar Muhammad Shoaib
Published: August 2024

This article presents Artificial Neural Networks (ANN) for convective heat transfer in a trapezoidal cavity subjected to corrugated heated rod inside it. The LevenbergMarquardt algorithm is utilized to optimize the Neural Networks. The trapezoidal cavity has low-temperature inclined walls and adiabatic upper and lower walls compared to the corrugated heated rod. Single-wall carbon (SWCNTs) nanomaterials are submerged in the base liquid water. The flow of SWCNTs-water is generated due to the temperature gradient in the cavity. The system of dimensional partial differential equations has been formulated for the physical setup under investigation. The dimensional system has been converted into a non-dimensional form using dimensionless variables. Finite element is used for the solutions. The dimensionless functions velocity, temperature, and heat transfer rates are studied against the Rayleigh number (Ra). The outcomes are presented in the form of isotherms, contours, tabular values, and graphs. The data for Artificial Neural Networks (ANN) has been generated by FEM against the Nusselt number. The ANN has been trained for a specific amplitude of the rod and predicted heat transfer against a larger amplitude. The results show good agreement for both training and testing data. The outcomes of analysis reveals that convection caused by temperature gradient is dominant for higher values of the Rayleigh number (Ra). Local Nusselt number has been discussed against different amplitudes, and predicted enhancement for the larger amplitude of the rod.
Empirical calculation of K-shell fluorescence cross sections for elements in the atomic range 16 ≤ Z ≤ 92 by photon effects ranging from 5.46 to 123.6 keV (Three-dimensional formulae)
Authors: Amari K , A Kahoul , Sampaio J M , Kasri Y , Marques J P , Parente F , Hamidani A , Croft S , Favalli A , Daoudi S , Deghfel B , Zidi A , Berkani B
Published: August 2024

The main objective of this study is to obtain three-dimensional empirical K-shell x-ray fluorescence cross-section (

σ

K

α

,

σ

K

β

and

σ

K

tot

)

values for a wide range of elements

16
≤
Z
≤
92

for photons with energies from 5.46 keV to 123.6 keV, using more than 3300 experimental data values published between 1985 and 2023 by numerous researchers. These data values are fitted using an interpolation method including a three-dimensional function against atomic number Z and excitation energy E, resulting in a three-dimensional plot to estimate empirically a three-dimensional set of

K

α

,

K

β

and

K

tot

x-ray fluorescence cross sections. The results of this empirical calculation are compared, for selected elements, with other empirical and experimental values reported in the literature, and a reasonable agreement is observed.
Characterization of field emission from oxidized copper emitters
Authors: Abuamr Adel M , Mousa Marwan S , Al-Bashaish Saleh R , Madanat Mazen A , AlSoud Ammar , Jaber Ahmad M D (Assa’d) , AlQaisi Ali F , Al-Anber Mohammed A , Barzinjy Azeez A , Arrasheed Enas A , Sobola Dinara
Published: August 2024

In this work, the field electron emission from oxidized copper emitters was studied by aging with radii in the range of 80–300 nm. The samples were prepared by an electrochemical etching method using an H3PO4 solution. The samples were exposed to air for 30 d to form an oxide film owing to aging. Measurements were carried out under high vacuum conditions in the range of 10−6 mbar. Scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM- EDS) was used to calculate the emitter radius, study the purity of the samples, and detect the oxide layers. Current–voltage (I-V) characteristics were studied and analyzed using Murphy-Goode (MG) plots and rectification tests. Furthermore, the spatial distribution of the electron emission and current stability were recorded and used to analyze the electron emission behavior of the tip surface. The trap density was also studied when the oxide layer was 3 layers thick. The results show that the emitters passed the orthodoxy test at low voltages. It was found that traps play an important role in increasing the switch-on current as the area of the oxide layer increases. It was found that the emitter acts as a point capacitor based on the charging and discharging processes of the electrons in the traps. The emission pattern showed great stability, which opens up prospects for this type of emitter in industry.
Graphene-assisted metamaterial absorber for refractive index sensor at lower optical frequencies
Authors: Kumar Raghwendra
Published: August 2024

Numerical studies on a graphene-assisted metamaterial absorber operating at lower optical frequencies are presented. The metamaterial absorber comprises one-dimensional gold grating with a gold disk array in grooves on a monolayer graphene supported by a glass substrate. Numerical simulations are conducted using Computer Simulation Technology Microwave Studio to investigate the underlying absorption mechanisms in the system. The absorber shows a very sharp absorption band with almost unity absorptance and nearly 20 nm full width at half maximum at a wavelength of 766 nm. The simulated absorption spectrum of the absorber is theoretically validated using coupled mode theory, showing close agreement with the theoretical predictions. The absorption occurs due to the simultaneous excitation of localized and propagating surface plasmons under the transverse electric mode (where the electric field is aligned parallel to the length of the grating ridge) excitation in the system. The sensing performance of the absorber has been evaluated, demonstrating a sensitivity as high as 667 nm/RIU. Due to the robustness of the design, this absorber can be used to sense biological, chemical, gaseous, and even acidic samples since it is not comprised of any photoresist. The absorber holds potential for diverse applications, including graphene-based devices, narrowband filters, thermal emitters, solar cells, imaging apparatus, etc.
A four-dimensional no-equilibrium chaotic system with multi-scroll chaotic hidden attractors and its application in image encryption
Authors: Ding Pengfei , Zhu Jingge , Zhang Juan
Published: August 2024

In recent years, constructing hidden attractors with multi-scroll has become a key discussion point in the research and application fields of chaos science. In this paper, with the existing four-dimensional (4D) chaotic system as the base, a new four-dimensional chaotic system featuring significant characteristics of multi-scroll hidden attractors is constructed by adding a nonlinear function. Comprehensive studies including theoretical analyses and numerical simulations have been carried out on the dynamic properties of the new chaotic system, and all the results show that this system exhibits extremely complex chaotic behaviours and excellent unpredictability, which has great value in image encryption. Therefore, an image encryption scheme based on the new chaotic system is proposed, which cleverly integrates the new scrambling algorithm based on parity coordinate transformation and the new rotational diffusion algorithm. And the effectiveness of this encryption algorithm has been thoroughly analyzed and tested. The results based on the experiments show that this encryption algorithm exhibits significant advantages in performance, which can greatly enhance the security of images during encryption and transmission.
Image encryption algorithm based on DNA mutation and a novel four-dimensional hyperchaos
Authors: Li Tianchi , Tong Xiaojun , Zhang Miao , Wang Zhu
Published: August 2024

Aiming at the problem that insufficient complexity of ordinary multi-dimensional chaotic systems and the cumbersome design of encryption algorithms without excellent encryption effects. This paper constructs a four-dimensional hyperchaotic system with high Lyapunov exponent and complex dynamic behavior. We designed an encryption algorithm based on point mutation, mutation diffusion, and folding mutation in DNA mutations. During the encryption process, we perform point mutation transformation on the entire base sequence, then spread the mutations one by one starting from the second base of the sequence, and finally flip every four base sequences according to folding mutations. The images encrypted by this algo-rithm have a uniform grayscale histogram, high information entropy, and high key sensitivity. It can resist exhaustive attacks, noise attacks, cropping attacks, and differential attacks, and have a fast encryption speed.
A novel 4-port MIMO antenna with chamfered edge for 5G NR n77/n78/n79 bands and WLAN applications
Authors: Doloi Trishna , Das Gouree Shankar , Kalita Partha Protim , Buragohain Akash , Devi Reeta , Beria Yatish
Published: August 2024

A novel, compact, and low-cost four-element multiple-input multiple-output (MIMO) antenna with a high gain is proposed in this work, operating in the frequency range of 3.3–6 GHz. The suggested antenna structure uses easily accessible substrate material and has been designed and simulated using Ansys HFSS 3D electromagnetic simulation software. The radiating elements are placed orthogonally, each consisting of two circular rings. To improve the impedance matching and reduce mutual coupling, the corners of the radiating patch are chamfered, and partial ground structure is applied. The defected ground structure (DGS) method is used for further enhancement in isolation, making the isolation as high as −55 dB. The measured gain of the antenna is more than 12 dB over the considered frequency range. The diversity gain (DG) is more than 9.99 dB, while the envelope correlation coefficient (ECC) is less than 0.006. Also, the mean effective gain (MEG), channel capacity loss (CCL), and total active reflection coefficient (TARC) results are within the optimal range. These make the designed antenna suitable for the sub-6 GHz 5G new radio (NR) n77 (3.3–4.2 GHz), n78 (3.3–3.8 GHz), and n79 (4.4–5 GHz) bands along with WLAN (5.1–5.8 GHz) applications.
An adversarial-based domain generalization method for the health evaluation of axial piston pumps
Authors: Shao Yuechen , Chao Qun , Zhang Zhiqiang , Liu Chengliang
Published: August 2024

The axial piston pump is the power component in hydraulic systems and evaluating its health status is of great importance to the safe operation of hydraulic systems. Discharge pressure signals are common monitoring signals for axial piston pumps, but it is difficult to obtain satisfactory health evaluation results by directly using raw discharge pressure signals since the degradation information lies in some specific frequency bands. Furthermore, the axial piston pump often operates under different operating conditions and most existing condition monitoring methods have low accuracies due to the problems of insufficient degradation data and different data distributions. This paper proposes an adversarial-based domain generalization (DG) method by integrating time-frequency analysis and data augmentation, to accurately predict the health status of axial piston pumps under unknown working conditions. First, discharge pressure signals under various operating conditions are decomposed by using the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and effective intrinsic mode functions (IMFs) are selected to train multiple convolutional neural network (CNN) models. Second, a novel data augmentation method based on the modified discrete cosine transform-composite spectrum (DCS) algorithm is introduced to fuse the IMFs from different domains and generate pseudo data sets. Finally, the adversarial training is adopted between the real data and the pseudo data to capture domain-generalized features. The discharge pressure signals of an actual axial piston pump at different health levels were collected on a test bench to verify the effectiveness of the proposed method. Results indicate that the proposed method has a higher prediction accuracy than the comparative methods.
Multifunctionality in vanadium dioxide-integrated metamaterials for switching between dual-band perfect absorption and asymmetric transmission
Authors: Zhang WenHao , Hu Xiang , Hu YanChao , Li Feng , Su Wei , Wu Hong
Published: August 2024

In this work, we present a theoretical proposal for an actively tunable metamaterial design that integrates vanadium dioxide (VO2). This VO2-integrated design demonstrates the ability to switch between dual-band perfect absorption and asymmetric transmission (AT) functionalities in the near-infrared and mid-infrared spectral ranges. By utilizing the unique properties of VO2, our proposed device achieves broadband absorption across approximately 2.47 μm with polarization independence when VO2 is in its metallic state. Furthermore, it exhibits narrowband absorption with polarization correlation, reaching a linear dichroism value of approximately 0.704. On the other hand, when VO2 is in its insulating state, the metamaterial structure realizes AT of 0.418 for circularly polarized light. We provide physical insight into the operating mechanisms through impedance matching analysis and electric field distributions. The integration of VO2 in this dynamically tunable, multifunctional metamaterial design offers a novel approach to developing reconfigurable nanophotonic and nanosystem technologies.
Regulation and analysis of multi-scroll attractors in a class of memristive Hopfield neural networks with high Lyapunov exponents
Authors: Wang Linghui , Ji’e Musha , Peng Hongxin , Duan Shukai , Wang Lidan
Published: August 2024

Multi-scroll chaotic systems have gained significant attention in recent years. However, there is little research on the chaotic systems of memristive neural networks with multiple complex structural attractors. A class of multi-scroll chaotic systems are designed in this paper, which are based on Hopfield neural network by using memristors as synapses. Implementing synaptic control with memristors at various coupling positions allows for the creation of multiple chaotic attractors with distinct topological structures. The proposed systems exhibit special and irregular shaped attractors, and can generate a fixed number of scrolls. Through analysis we find that the systems have high Lyapunov exponents, indicating strong sensitivity and randomness. Meanwhile, the systems exhibit extremely rich dynamic behaviors, such as symmetric coexistence phenomena. Especially, we observe signal amplitude control and offset boosting phenomena in the systems. In addition, simulation circuits are designed based on such chaotic systems to verify the physical feasibility of the systems.
Time domain optimization of pair production during vacuum breakdown triggered by frequency chirped external fields
Authors: Gong Chi , Lu Xinyu , Shang Dakai , Ren Zhi , Li Songtao
Published: August 2024

The electron–positron pair creation process during the Dirac vacuum breakdown triggered by strong external fields is analyzed. A frequency chirped, subcritical force field can significantly enhance the pair production yield under the identical total energy. This enhancement effect is caused by different chirp frequencies. We pay special attention to optimal field conditions as chirping parameter and phase of the time dependent field are varied. And the total number of created electrons with frequency weighted average under different chirp parameters are different from the theoretically calculated values. And no matter what the main mechanism is, the laser has the highest energy utilization rate when the electric field is symmetrical.
Conductively coupled terahertz metamaterials with dual functions of electromagnetically induced transparent and Fano effects for sensing applications
Authors: Chen Yuxuan , Sun Yongzheng , Zhou Weijun , Qin Xuefeng , Zhao Qian , Wang Yueke , Wang Ben-Xin
Published: August 2024

A terahertz metamaterial structure consisting of two U-shaped split-ring resonators and a horizontal cut-line resonator is designed for realizing the electromagnetically induced transparency (EIT) effect and the Fano resonance effect. The genesis of the EIT and Fano resonance bifunctionality is illustrated by combining the near-field distribution analysis of transparent windows and transmission dips. Interestingly, the bifunctional dual-band transparency effect could transform into a single-functional single-band transparency effect when we change the position of the square metal sheet in the vertical direction of the composited terahertz metamaterial structure. In addition, based on the high-quality factor of Fano resonance response, the proposed bifunctional terahertz metamaterial device has good refractive index sensing sensitivity. These results indicate that our proposed terahertz metamaterial can provide guidance for the design of subsequent multifunctional and integrated metamaterials and optoelectronic devices.
2D-GeP3 as an exemplary prospect for NO sensing: unveiling highly sensitive and selective at room temperature
Authors: Ahmed A Sara , Cai Xinyong , M E Ali Mohanad , Ftahi Waleed , Wang Hongyan
Published: August 2024

Novel two-dimensional (2D) materials have garnered significant attention for constructing ultra-sensitive gas sensors. This study explores the potential of a novel 2D-GeP3 monolayer for sensing CO, CO2, NO, NO2, O2, and N2 gases using first-principle calculations. The results reveal that the GeP3 monolayer exhibits low sensitivity to CO2 and N2 gases due to low adsorption energies and minimal charge transfer. Conversely, it demonstrates appropriate adsorption properties for NO and CO, as well as strong chemisorption for NO2 and O2 molecules. Through an analysis of adsorption behavior, electronic and optical, and sensing characteristics, the GeP3 monolayer shows high sensing capability for NO, NO2, and O2 gases. Notably, it demonstrates appropriate selectivity and sensitivity for NO gas due to adsorption energy of −0.742 eV, charge transfer of −0.376 e, and significant changes in electronic properties upon interaction. Furthermore, the GeP3 monolayer exhibits a short recovery time of 0.29 s at room temperature. Based on these findings, the GeP3 monolayer holds promise as a reversible NO gas sensor and as an irreversible sensor for NO2 and O2 gas. These results serve as a valuable guide in subsequent experimental applications for using the GeP3 monolayer in gas sensing devices.
An ultrasensitive refractive index based THz optical biosensor based on plasmon induced transparency (PIT)
Authors: Tabassum Sumaiya Jahan , Mohsin Abu S M , Bhuian Mohammed Belal H , Haque Munima , Mosaddequr Rahman Md
Published: August 2024

A novel, label-free optical sensor based on plasmon induced transparency (PIT) has been designed for the detection of basal cell carcinoma in the terahertz (THz) frequency range. The sensor consists of a thin Indium Antimonide (InSb) layer on top of a silica layer with patterned plasmonic antennas where the biosamples are deposited. To overcome the problem associated with the absorption modes of water molecules in THz, the sensor is designed with resonances at frequencies where light absorption of water molecules is minimal. To enhance the reported sensor’s performance features, parametric sweeps have been conducted on the geometrical attributes of the nanostructure. Due to the strong coupling between radiative and dark plasmonic modes, the sensor has a very high sensitivity of 4.50 THz RIU−1, a Q factor of 112.7, and a figure of merit (FOM) of 43.3. The suggested design is ultracompact and easy to fabricate with the potential to be used in numerous biomedical sensing applications.
Fitting of giant magnetoimpedance curves using the complex method in optimization techniques
Authors: Sun Xutao , Shen Guotu , Zhao Zhenjie
Published: August 2024

The giant magnetoimpedance (GMI) effect is characterized by substantial variations in both the real and imaginary components of the impedance when subjected to an alternating current in the presence of a static magnetic field. In quasistatic models, the GMI profile can be effectively delineated by the changes in transverse permeability in response to variations in the external magnetic field. Building on this, the magnetic anisotropy field and anisotropy angle for specific magnetic phases can be determined by fitting the experimental data points. The dual magnetic phase structure of the CoP/NiCoP/Cu composite wire results in a four-peak profile in its GMI curves, making it suitable as a target curve for fitting. By preprocessing the GMI curves and applying the Complex Method within optimization techniques through multiple iterations, the theoretical target curve is ultimately obtained, along with the extraction of the physical parameters embedded within it. This approach presents a novel solution to the multi-parameter curve fitting.
Direct fabrication of rough gold nanoholes and investigation of their second-harmonic generation
Authors: Pham Quang Truong , Fandino Adriana Umbria , Ngo Gia Long , Lafargue Clement , Ledoux-Rak Isabelle , Lai Ngoc Diep
Published: August 2024

In this study, we introduce a simple and cost-effective technique called one-photon absorption-based direct laser writing (OPA-based DLW) to directly fabricate noncentrosymmetric gold nanoholes (Au NHs). This technique relies on the optically induced local thermal effect at the focusing spot using a 532 nm excitation wavelength, which induces the evaporation of the Au thin film and thereby creating metal NHs. By controlling the exposure doses, including fabrication powers and writing velocities, we achieve Au NHs with small sizes around 300 nm and a periodicity of 500 nm. Moreover, due to the non-uniform heat transfer in an imperfectly flat Au film, the formed NHs lack perfect circularity, showing roughness and asymmetry. Thanks to this irregular shape of Au NHs, second-harmonic generation (SHG) signals are generated. This nonlinear signal can be amplified thanks to near electric field intensity enhancement at the borders of the holes. By moving the focusing spot, this DLW method allows us to fabricate any desired two-dimensional patterns, which exhibit SHG signals. This ability could be advantageous for applications in optical data storage and nonlinear imaging.
Clustering of primordial black holes from quantum diffusion during inflation
Authors: Animali Chiara , Vennin Vincent
Published: August 2024

We study how large fluctuations are spatially correlated in the presence of quantum diffusion during inflation. This is done by computing real-space correlation functions in the stochastic-δ N formalism. We first derive an exact description of physical distances as measured by a local observer at the end of inflation, improving on previous works. Our approach is based on recursive algorithmic methods that consistently include volume-weighting effects. We then propose a “large-volume” approximation under which calculations can be done using first-passage time analysis only, and from which a new formula for the power spectrum in stochastic inflation is derived. We then study the full two-point statistics of the curvature perturbation. Due to the presence of exponential tails, we find that the joint distribution of large fluctuations is of the form P(ζ
R

1, ζ
R

2) = F(R
1,R
2, r) P(ζ
R

1)P( ζ
R

2), where ζ
R

1 and ζ
R

2 denote the curvature perturbation coarse-grained at radii R
1 and R
2, around two spatial points distant by r. This implies that, on the tail, the reduced correlation function, defined as P(ζ
R

1 > ζc, ζ
R

2 > ζc)/[P(ζ
R

1 > ζc) P(ζ
R

2 > ζc)]-1, is independent of the threshold value ζc. This contrasts with Gaussian statistics where the same quantity strongly decays with ζc, and shows the existence of a universal clustering profile for all structures forming in the exponential tails. Structures forming in the intermediate (i.e. not yet exponential) tails may feature different, model-dependent behaviours.
GW230529_181500: a potential primordial binary black hole merger in the mass gap
Authors: Huang Qing-Guo , Yuan Chen , Chen Zu-Cheng , Liu Lang
Published: August 2024

During the fourth observing run of the LIGO-Virgo-KAGRA detector network, the LIGO Livingston observatory detected a coalescing compact binary, GW230529_181500, with component masses of 2.5–4.5M⊙and 1.2–2.0M⊙at the 90% credible level. The gravitational-wave data alone is insufficient to determine whether the components are neutron stars or black holes. In this paper, we propose that GW230529_181500 originated from the merger of two primordial black holes (PBHs). We estimate a merger rate of 5.0+47.0-4.9Gpc-3yr-1for compact binary coalescences with properties similar to GW230529_181500. Assuming the source is a PBH-PBH merger, GW230529_181500-like events lead to approximately 1.7+36.2-1.5× 10-3of the dark matter in the form of PBHs. The required abundance of PBHs to explain this event is consistent with existing upper limits derived from microlensing, cosmic microwave background observations and the null detection of gravitational-wave background by LIGO-Virgo-KAGRA.
Impact of astrophysical scatter on the epoch of reionization [H i]21 bispectrum
Authors: Murmu Chandra Shekhar , Datta Kanan K. , Majumdar Suman , Greve Thomas R.
Published: August 2024

It is believed that the first star-forming galaxies are the main drivers of cosmic reionization. It is usually assumed that there is a one-to-one relationship between the star formation rate (SFR) inside a galaxy and the host halo mass in semi-analytical/numerical modeling of large-scale ionization maps during the epoch of reionization. However, more accurate simulations and observations suggest that the SFR and ionizing luminosity in galaxies may vary considerably even if the host halo mass is the same. This astrophysical scatter can introduce an additional non-Gaussianity in the [H i]21cm signal, which might not be captured adequately in the power spectrum. In this work, we have studied the impact of the scatter on the [H i]21cm bispectrum using semi-numerical simulations. We find that the scatter primarily affects small ionized regions, whereas the large ionized bubbles remain largely unaffected. Although, the fractional change in the [H i]21cm bispectra due to the scatter is found to be more than a factor of 10 at large scales (k
1 ≲ 1 Mpc-1) for z=7.4, it is found to be statistically insignificant. However, at small scales (k
1 ~ 2.55 Mpc-1), we have found the impact due to the scatter to be high in magnitude (|〈Δ B 〉/B
no-scatter| ~ 1) and statistically significant (|〈Δ B〉/σ
ΔB| ≳ 5) at neutral fraction, x̅HI ~ 0.8 for z=7.4. The impact due to scatter is found to be even more prominent (|〈Δ B 〉/B
no-scatter| ≳ 10) at small scales for z=10 and x̅HI ~ 0.8, but with reduced statistical significance to some extent (|〈Δ B〉/σ
ΔB| ~ 3), compared to z=7.4 at the same neutral fraction. We have also found that in the most optimistic scenario, SKA1-Low might be able to detect these signatures of astrophysical scatter, at ~ 3σ and ~ 5σ detection significance for x̅HI ~ 0.8 and 0.9 respectively, for the equilateral [H i]21cm bispectrum at z=7.4.
FLARE: field line analysis and reconstruction for 3D boundary plasma modeling
Authors: Frerichs H.
Published: August 2024

The FLARE code is a magnetic mesh generator that is integrated within a suite of tools for the analysis of the magnetic geometry in toroidal fusion devices. A magnetic mesh is constructed from field line segments and permits fast reconstruction of field lines in 3D boundary plasma codes such as EMC3-EIRENE. Both intrinsically non-axisymmetric configurations (stellarators) and those with symmetry breaking perturbations of an axisymmetric equilibrium (tokamaks) are supported. The code itself is written in Modern Fortran with MPI support for parallel computing, and it incorporates object-oriented programming for the definition of the magnetic field and the material surface geometry. Extended derived types for a number of different magnetohydrodynamic equilibrium and plasma response models are implemented. The core element of FLARE is a field line tracer with adaptive step-size control, and this is integrated into tools for the construction of Poincaré maps and invariant manifolds of X-points. A collection of high-level procedures that generate output files for visualization is build on top of that. The analysis modules are build with Python frontends that facilitate customization of tasks and/or scripting of parameter scans.
Mapping the landscape of carbon dioxide removal research: a bibliometric analysis
Authors: Presty Romain , Massol Olivier , Jagu Emma , da Costa Pascal
Published: August 2024

An intense global research effort on carbon dioxide removal (CDR) technologies is generating a rapidly expanding scientific literature. These contributions stem from various disciplines and investigate various CDR concepts and their potential implications. This study conducts an updated analysis of the international research effort on CDR from 2012 to 2023, examining 7893 publications using bibliometric techniques. We focus on the geographic distribution of technology-specific research and the funding driving this research. Significant publication growth is observed post-2015, particularly after 2018 and in 2023, driven primarily by the EU, China, and the US. Notably, biochar, afforestation/reforestation, and soil carbon sequestration are among the most researched CDR options, with direct air carbon capture and storage, bioenergy carbon capture and storage, and blue carbon also receiving substantial attention, especially in 2023. Analysis of scientific funding patterns aligns with these trends. Based on these findings, the study proposes a knowledge roadmap to elucidate emerging trends in CDR literature, offering insights for future research and policy development.
The microhardness, morphology and tribological property of TC4 subjected to machine hammer peening
Authors: Zhang Xuewen , Jing Hongrui , Yang Ying , Zhong Zexin , Li Xiang , Liu Yu
Published: August 2024

Ti alloy has become an indispensable material in harsh working environments due to its excellent wear resistance, corrosion resistance and impact resistance. These environments place stringent requirements on the fatigue life, friction and wear, and surface strength of materials. Therefore, this study aims to deeply explore the surface mechanical properties of Ti-6Al-4V (TC4) alloy after machine hammer peening (MHP) treatment. By conducting experiments on TC4 alloys treated with different hammering energies, the changes in surface hardness, morphology, roughness, tensile properties, and friction properties were analyzed, and the strengthening mechanism of MHP was discussed. Experimental results show that MHP treatment can effectively improve the surface properties of TC4. With the increase of hammer energy, due to the double-sided hammering of the plate, the microhardness first increases, then decreases, and then rises again. The tensile strength and yield strength of the sample increase slightly, but the elongation at break decreases. The surface roughness of the sample increases first and then decreases. Similarly, after MHP treatment, the wear resistance of the samples increased, the friction coefficient decreased, and the wear amount and surface height difference showed a trend of first increasing and then decreasing. The wear mechanism mainly included adhesive wear, abrasive wear and fatigue wear.
A review on machine learning-guided design of energy materials
Authors: Kim Seongmin , Xu Jiaxin , Shang Wenjie , Xu Zhihao , Lee Eungkyu , Luo Tengfei
Published: August 2024

The development and design of energy materials are essential for improving the efficiency, sustainability, and durability of energy systems to address climate change issues. However, optimizing and developing energy materials can be challenging due to large and complex search spaces. With the advancements in computational power and algorithms over the past decade, machine learning (ML) techniques are being widely applied in various industrial and research areas for different purposes. The energy material community has increasingly leveraged ML to accelerate property predictions and design processes. This article aims to provide a comprehensive review of research in different energy material fields that employ ML techniques. It begins with foundational concepts and a broad overview of ML applications in energy material research, followed by examples of successful ML applications in energy material design. We also discuss the current challenges of ML in energy material design and our perspectives. Our viewpoint is that ML will be an integral component of energy materials research, but data scarcity, lack of tailored ML algorithms, and challenges in experimentally realizing ML-predicted candidates are major barriers that still need to be overcome.