bluuebunny/crossref_metadata_2025 huggingface dataset:
Graphic processing unit accelerated time-domain harmonic balance method for multi-row turbomachinery flow simulation
Authors: Yong Xiaosong , Liu Yangwei , Tang Yumeng
Published: September 2024

Rotor–stator interaction is an inherently unsteady phenomenon in turbomachinery that significantly influences the performance of turbomachinery. Accurate prediction of the unsteady turbomachinery rotor–stator interaction flow remains a great challenge considering computational cost. In the Reynolds-averaged Navier–Stokes framework, the harmonic balance (HB) method emerges as a potential reduced-order modeling technique, offering significant computational savings over traditional unsteady methods, and revealing unsteady flow characteristics that are elusive to the steady mixing-plane method. In this study, a graphical processing unit (GPU)-based solver utilizing the finite volume method is developed to accelerate the computation of the HB method compared to the traditional central processing unit (CPU)-based solver. An implicit data-parallel block-Jacobi lower-upper relaxation (DP-BJ-LUR) method is first proposed to better fit the distinct parallel architecture of GPU. The HB method with different harmonics, as well as unsteady time marching method, is conducted to evaluate the accuracy and acceleration for convergence of the proposed method by a quasi-three-dimensional radial slice case and a full three-dimensional case for National Aeronautics and Space Administration (NASA) Stage 35 compressor. Acceleration performance of GPU-based solver, impact of relaxation steps on the DP-BJ-LUR method, and numerical accuracy are compared in detail. A maximum speedup of 102 times with 1 harmonic and 90 times with 12 harmonics is achieved by the GPU-based solver on a single NVIDIA Ray Tracing Texel eXtreme 3080Ti GPU compared with the CPU-based solver on a single CPU core of Intel® Xeon® Platinum 9242.
Blueshift or redshift? Effect of hydrogen bonding interactions on the C≡N stretching frequency of 5-cyanoindole
Authors: Yang Yuyao , Zhao Ruoqi , Zhang Wenkai , Gao Jiali , Gai Feng
Published: September 2024

The nitrile (C≡N) stretching vibration is widely used as a site-specific environmental probe of proteins and, as such, many computational studies have been used to investigate the factors that affect its frequency (νCN). These studies, most of which were carried out in the ground electronic state of the molecule of interest, revealed that the formation of a normal or linear hydrogen bond (H-bond) with the nitrile group results in a blueshift in its νCN. Recently, however, several experimental studies showed that for certain aromatic nitriles, solvent relaxations in their excited electronic state(s) induce a redshift (blueshift) in νCN in protic (aprotic) solvents, suggesting that the effect of hydrogen-bonding (H-bonding) interactions on νCN may depend on the electronic state of the molecule. To test this possibility, herein we combine molecular dynamics simulations and quantum mechanical calculations to assess the effect of H-bonding interactions on the νCN of 5-cyanoindole (5-CNI) in its different electronic states. We find that its C≡N group can form either one H-bond (single-H-bond) or two H-bonds (d-H-bonds) with the solvent molecules and that in the ground electronic state, a single-H-bond can lead νCN to shift either to a higher or lower frequency, depending on its angle, which is consistent with previous studies, whereas the d-H-bonds cause νCN to redshift. However, in its lowest-lying excited electronic state (i.e., S1), which has the characteristics of a charge-transfer state, all H-bonds induce a redshift in νCN, with the d-H-bonds being most effective in this regard.
Hypersonic shock–shock interaction over double wedge controlled by a supermultichannel high-energy pulsed arc discharge array
Authors: Zhang Dongsheng , Yang Hesen , Su Zhi , Liang Hua
Published: September 2024

Shock–shock interactions (SSIs) are widespread in hypersonic vehicles. The mutual interaction between multiple shock waves can result in severe pressure loads and increase the thermal load. The SSI induced by a double wedge configuration is a classical problem. This paper describes a novel U-electrode surface arc actuator that produces a supermultichannel array surface arc discharge under hypersonic conditions. High-speed schlieren measurements are used to investigate the SSI induced by the hypersonic double wedge and plasma control under Mach 8 flow conditions. The results show that the shock wave array induced by the plasma forms a virtual compression surface. This surface deforms the shock wave induced by the first wedge, and the oblique shock wave in front of the secondary wedge and the SSI region disappear due to the uplift and hot gas mass disturbance from the impact. Because the applied actuation frequency is higher than the characteristic frequency of the base flow field, the high-frequency pulsations of the shock wave are controlled by the plasma actuation. Additionally, the low-frequency instability is suppressed. Thus, the aerodynamic load and low-frequency instability of the double wedge configuration under high-Mach-number conditions are effectively regulated.
An immersed boundary method for modeling fluid–solid–acoustic interactions involving dynamic structures
Authors: He Yanfei , Zhang Xingwu , Chen Tairan , Li Ying , Deng Tao , He Yituan
Published: September 2024

In equipment within the aviation and marine industries, aerodynamic and hydrodynamic noises generated by the coupling effect between moving structures (such as equipment shells, landing gears, blades, etc.) and fluid media are ubiquitous. These noises significantly impact the noise levels of the equipment and its surrounding environment, posing threats to the health of users and organisms in the environment. While existing noise calculation methods effectively address aerodynamic and hydrodynamic noises from fixed structures under uniform incoming flow conditions, few literatures delve into the computational methods for aerodynamic and hydrodynamic noises arising from the interaction between moving structures and fluid media. To calculate fluid noises induced by structural vibrations and motions, this paper proposes an immersed boundary method for fluid–structure–acoustic interactions with moving structures. This method concurrently employs the Navier–Stokes equation and wave equation to describe the time-averaged quantities and fluctuating variables of the fluid, taking into account the influence of non-uniform fluids during sound propagation. Based on this methodology, noise tests and numerical calculations were conducted on vibrating cylindrical shells, along with fluid–structure–acoustic coupling calculations for linearly moving cylinders in static fluids. These examples validate the effectiveness and accuracy of the proposed method in simulating the generation and propagation processes of radiation noise and flow-induced noise caused by structural motion.
Optimal control of COVID-19 through strategic mathematical modeling: Incorporating harmonic mean incident rate and vaccination
Authors: Shah Kamil , Shah Jamal , Bonyah Ebenezer , Alballa Tmader , El-Wahed Khalifa Hamiden Abd , Khan Usman , Khan Hameed
Published: September 2024

COVID-19 is a novel virus that has spread globally, and governments around the world often implement different strategies to prevent its spread. In the literature, several COVID-19 models have been studied with the bilinear incident rate. In this study, the S1V1E1I1Q1R1 (susceptible-vaccinated-exposed-infective-quarantined-recovered) COVID-19 model is proposed. To investigate how the disease spreads in the population, an algorithm is used. The efficacy of the algorithm is used to calculate the disease-free equilibrium point. A next generation matrix technique is used to find R0. Furthermore, to check the effect of parameters on the basic reproduction number (R0), the sensitivity analysis is conducted. Numerical simulation displays that the disease spreads in the population by increasing the value of the contact rate β while the disease spread in the population reduces by increasing the value of the vaccination rate θ, quarantine rate ϕ, and recovery rate γ. Different optimal control strategies, such as social distance and quick isolation, are also implemented.
Crossing boundaries in an age of post-translation studies
Authors: Lifei Pan
Published: September 2024

The cycle of symphonic songs Das Lied von der Erde was based on Die Chinesische
Flöte, a German version of classical Chinese poems. As a result, Die Chinesische Flöte crossed the
boundary between literature and music, encompassing intralingual, interlingual, and intersemiotic translations. While comparative
textual analysis reveals that these two works made changes to the original Chinese texts, intersemiotic translation illustrates
that the borders between verbal texts and nonverbal works are fluid. This post-translation study traces the translation context of
Das Lied, maps Die Chinesische Flöte’s transitions between literary and musical polysystems,
and traces Das Lied’s afterlife in the creation of new artworks. It concludes that poetry, music, and other art
forms can mutually translate, complement, and become afterlives of one another.
Micromixing strategies for efficient mixing processes: a comprehensive review
Authors: Soltani Delara , Persoons Tim , Alimohammadi Sajad
Published: September 2024

The demand for rapid, high-quality, and controlled mixing at the microscale has led to the development of various types of micromixers. Micromixers are commonly categorised as active, or passive based on whether they utilise external energy to enhance mixing. Passive micromixers utilise a complex geometry to enhance the diffusion coefficient at lower Reynolds numbers and induce chaotic advection at higher Reynolds numbers for effectively mixing fluids without external energy. Active micromixers, on the other hand, achieve precise, fast, and controllable mixing by employing external energy sources such as pressure, electric, magnetic, or acoustic fields. Some active methods such as magnetic field-driven micromixers need fluids with specific properties. Others, such as acoustic field-driven micromixers apply to various types of fluids. Bubbles can be used as membranes or stirrers in microfluidic devices for both passive and active micromixers. They are easy to use, compatible with microfluidic systems, low cost, and effective. Improvements in manufacturing methods, notably, 3D printing have emerged as promising methods for the development of new micromixer designs. In this paper, a wide range of micromixer types is reviewed and the main mechanism for enhanced mixing is investigated. This study aims to guide researchers proposing innovative designs. Furthermore, it is shown that combining different methods can lead to the development of more effective micromixers, promising further advancements in microscale mixing technology.
Physics-informed neural networks with data-driven in modeling and characterizing piezoelectric micro-bender
Authors: Nguyen Binh Huy , Torri G B , Rochus V
Published: September 2024

Despite the rapid development and widespread adoption of physics-informed neural networks (PINNs) in various engineering fields, their applications in microelectromechanical coupling systems (MEMS) remain relatively unexplored. In this study, we demonstrate a novel implementation of PINNs for modeling and characterizing a piezoelectric microactuator. By leveraging the beam-like structure, the governing equations for a multi-layered piezoelectric actuator are first derived and subsequently incorporated into the PINNs model to accurately predict the deformation of the piezoelectric actuator in response to a given voltage input. Furthermore, by integrating experimental deflection data obtained from Laser Doppler Vibrometer measurements into the neural network, we further demonstrate the potential of PINNs in identifying the piezoelectric material coefficient through inverse analysis. Our contribution in applying PINNs to models and characterizing piezoelectric actuators in MEMS serves as a promising starting point for the broader utilization of machine learning techniques in this field.
Radiation properties of [C4F7N-CO2-O2]-PTFE-Cu mixtures at high temperatures and pressures for high-voltage circuit breakers
Authors: Deng Junwei , Zhang Boya , Cao Minchuan , Wang Guanyu , Chen Shizhe , Wang Zhoujing , Li Xingwen , Murphy Anthony B
Published: September 2024

C4F7N–CO2–O2 is currently considered the most promising replacement for SF6 in high-voltage circuit breakers. During high-current interruption conditions, arc radiation plays a pivotal role in arc modeling and is frequently accompanied by vapors ablated from the electrodes and nozzles. To investigate the influence of ablated vapors on the radiative properties of gas mixtures, net emission coefficients (NECs) for various ratios of C4F7N mixtures and PTFE and Cu vapors are calculated under the assumption of local thermodynamic equilibrium. The NECs for [C4F7N–CO2–O2]-PTFE-Cu mixtures that are obtained are required for radiation modeling and arc simulation in high-voltage circuit breakers. It has been found that neglecting the presence of PTFE vapor does not affect the NEC at high temperatures. However, the influence of copper vapor on the radiative properties in the high-temperature region becomes apparent at elevated ratios, and self-absorption is more pronounced at very high pressures. Based on these findings, recommendations for choosing NECs for use in modeling that balance accuracy and efficiency are proposed.
First-principles study of oxygen vacancy defects in β-quartz SiO2/Si interfaces
Authors: Zheng Ruogu , Xu Zhengyu , Feng Muti , Xiang Bo , Wang Hai , Wang Qingbo , Zhong Hongxia
Published: September 2024

Understanding the electronic structures of gate oxides in Si-based devices is significant for improving device performance. We investigate the electronic properties of the oxygen vacancy defects in β-quartz SiO2/Si interface structure using first-principles calculations. The results indicate that the constructed (SiO2)4/(Si)4 structure is an indirect-gap semiconductor, with its band edges contributed by Si side and a large band-edge energy difference (

>

1.780 eV). Our study reveals that the presence of oxygen vacancy defects reduces the band gap, and

V

O

1

is transformed from indirect into direct band gap. The Si dangling bonds in

V

O

1

cause charge localization around the O vacancy, while the formation of Si–Si bonds in

V

O

2

and

V

O

3

lead to electron delocalization. In the calculation of defect formation energies, we find that

V

O

1

maintains the lowest formation energy across different states, making it more likely to form and structurally stable. Compared to O-rich environments, the formation energy in O-poor environments is overall reduced by approximately 4.5 eV, indicating that oxygen vacancy defects are more likely to form and be controlled under O-poor conditions. Our study emphasizes the importance of interface structure and defect characteristics in semiconductor research, providing insights for the development of Si-based devices.
Design of highly selective ultrawideband FSS based on deep learning for EMI shielding in 5G bands
Authors: Li Yan , Yu Shijia , Li Da , Zhang Ling , Liu Enxiao , Li Erping
Published: September 2024

In this paper, a frequency selective surface (FSS) for n41, n78, n257, n258, n260, and n261 bands electromagnetic interference (EMI) shielding is proposed using a deep learning method. The size of the FSS unit cell is 4.8 mm (0.071

 

λ
0

), where

 

λ
0

 

is the wavelength corresponding to the cutoff frequency of the −10 dB stopband where the n41 and n78 bands are located. This FSS exhibits three key characteristics. Firstly, it possesses ultrawideband capability, with a stopband frequency range of 23.922–40.023 GHz and a relative bandwidth reaching 50.4%. Secondly, it effectively shields against electromagnetic radiation in multiple 5 G bands, including n41, n78, n257, n258, n260, and n261. Thirdly, it demonstrates high selectivity, with a very narrow transition band of only 0.405 GHz between the passband and the stopband. To validate the designed FSS, a prototype of this structure was first fabricated for experimentation. The experimental results show that the measured S21 is highly consistent with the simulated S21. Secondly, the unit cell array of FSS is placed above the monopole antenna for co-simulation. It can be observed that after placing the FSS, the intensity of electromagnetic radiation propagating in space is significantly reduced by up to more than 90%. Therefore, the proposed FSS can be effectively applied for EMI shielding in 5 G bands.
Quantum theory of the spin dynamics excited by ultrashort THz laser pulses in rare earth antiferromagnets. DyFeO3
Authors: Popov A I , Gareeva Z V , Zvezdin A K
Published: September 2024

A quantum theory of spin dynamics in the rare—earth orthoferrites excited by terahertz laser pulses is developed. The study demonstrates that dynamic magnetic configurations, triggered by a light pulse, exhibit stability even after the excitation source is ceased. The magnitude of post-excitation oscillations is linked to the ratio between the frequency of rare-earth ion excitations and the frequency of the external source. According to the analysis presented, dynamic response is significantly amplified when the system is exposed to ultrashort terahertz pulses. The physical characteristics of the oscillations emerging after the pulse are determined, and the factors governing their amplitude and phase are identified. The response signal is found to be dependent on the initial part of the pulse, specifically the half-period of the ultrashort light wave, while the subsequent part of the pulse contributes minimally to post-pulse magnetization dynamics. The findings highlight that in DyFeO3, terahertz dynamics primarily result from the influence of the magnetic field of the light, leading to excitations of electrons from the ground state to low-lying electronic levels of Dy3+ ions. Additionally, the dynamic magnetoelectric effect excited by the electric field of the pulse is explored, revealing the emergence of odd magnetic modes.
Optimizing the composition of (Ce,La)(Co,Fe)5for permanent magnet applications using density functional theory
Authors: Okumura Haruki , Fukushima Tetsuya , Fukazawa Taro , Miyake Takashi , Akai Hisazumi , Ogura Masako
Published: September 2024

In this work, we calculated physical quantities, including the magnetocrystalline anisotropy constant (Ku) and magnetization (Ms), for disordered (Ce,La)(Co,Fe)5systems. Based on the results, we propose CeCo4.7Fe0.3as the optimum composition for high-performance permanent magnets. The calculations employed the full-potential Korringa–Kohn–Rostoker Green’s function method, and dealt with the compositional disorder of the systems within the coherent potential approximation. It was found that the La doping reducesKuat 0 K but increases the Curie temperature (TC), which leads to improvement of the magnetic properties at high temperatures. CeCo4.7Fe0.3had the largest magnetic anisotropy ofKu= 15.14 MJ m−3, which is larger than that of CeCo5(Ku= 14.77 MJ m−3).TCof CeCo4.7Fe0.3estimated by the mean-field approximation was 1005 K, which exceeds that of CeCo5(965 K). Further, our calculations showed that while doping of Fe destabilizes the system, CeCo4.7Fe0.3is stable against decomposition into the simple substances. We also show calculated data that are informative for exploring high-performance permanent magnet materials in this paper.
Giant and negative magnetoresistances in conical magnets in the nonequilibrium Boltzmann equation approach
Authors: Rivlis Raz , Zadorozhnyi Andrei , Dahnovsky Yuri
Published: September 2024

We study magnetotransport in conical helimagnet crystals using the nonequilibriun Boltzmann equation approach. Spin dependent magnetoresistance exhibits dramatic properties for high and low electron concentrations at different temperatures. For spin up electrons we find negative magnetoresistance despite only considering a single carrier type. For spin down electrons we observe giant magnetoresistance due to depletion of spin down electrons with an applied magnetic field. For spin up carriers, the magnetoresistance is negative, due to the increase in charge carriers with a magnetic field. In addition, we investigate the spin dependent Hall effect. If a magnetic field reaches some critical value for spin down electrons, giant Hall resistance occurs, i.e. Hall current vanishes. This effect is explained by the absence of spin down carriers. For spin up carriers, the Hall constant dramatically decreases with field, due to the increase in spin up electron density. Because of the giant spin dependent magnetoresistance and Hall resistivity, conical helimagnets could be useful in spin switching devices.
Research on detection and classification of automotive body surface defects based on image processing and machine learning
Authors: Yang Zhiyong , He Yang , Zhang Ziyu , Liu Yanqi , Li Xiuhong , Zhang Daode
Published: September 2024

The high noise in the automotive body surface image makes it difficult to extract defects. Moreover, a single feature cannot describe the complex automotive body surface defects leading to low classification accuracy. This paper proposes a highly robust method for classifying body surface defects. Firstly, an edge detection method that integrates the wavelet transform and the mathematical morphology is applied to detect defects. Subsequently, the geometric features of detected defects are combined with scale-invariant feature transform features to be the classification basis. Finally, the classification accomplishes through a support vector machine(SVM) with the parameters optimized via the grey wolf optimizer-SVM. Experimental results show the proposed classification method based on feature fusion achieves an average of 93% accuracy in automotive body surface defects classification and exhibits a 100% classification accuracy for pseudo-defects, which demonstrates the fusion of the wavelet transform and the mathematical morphology for automotive body surface defects detection can effectively reduce the impact of image noise for ensuring the extracted edges are intact.
Tuning the structure and properties of carbon cloth by FeCl3 intercalation for efficient two-electron oxygen reduction catalysis
Authors: Gao Yu , Liang Guangyuan , Liang Huanhuan , Wang Lijing , Du Hongfang , Liu Dezheng , Lin Liangxu
Published: September 2024

The advancement of various energy conversion and storage technologies hinges on the development of efficient and stable electrocatalysts for the oxygen reduction reaction (ORR). In this study, we report the enhancement of carbon cloth (CC) for robust ORR through an FeCl3 intercalation reaction. Utilizing a thermal annealing method, FeCl3 was intercalated into the graphite structure on the surface of CC, resulting in the creation of numerous defects and the incorporation of Fe species. These newly introduced defects play a pivotal role in activating the ORR via a two-electron pathway. The presence of Fe species further stabilizes the catalytic activity, leading to efficient and stable ORR performance. Our findings highlight the significance of defect engineering and Fe species incorporation in carbon-based materials for improved ORR catalysis and pave the way for the development of advanced electrocatalysts for energy-related applications.
A comparative study on automatic treatment planning for online adaptive proton therapy of esophageal cancer: which combination of deformable registration and deep learning planning tools performs the best?
Authors: Draguet C , Populaire P , Vera M Chocan , Fredriksson A , Haustermans K , Lee J A , Barragán-Montero A M , Sterpin E
Published: September 2024

Objective. To demonstrate the feasibility of integrating fully-automated online adaptive proton therapy strategies (OAPT) within a commercially available treatment planning system and underscore what limits their clinical implementation. These strategies leverage existing deformable image registration (DIR) algorithms and state-of-the-art deep learning (DL) networks for organ segmentation and proton dose prediction. Approach. Four OAPT strategies featuring automatic segmentation and robust optimization were evaluated on a cohort of 17 patients, each undergoing a repeat CT scan. (1) DEF-INIT combines deformably registered contours with template-based optimization. (2) DL-INIT, (3) DL-DEF, and (4) DL-DL employ a nnU-Net DL network for organ segmentation and a controlling ROIs-guided DIR algorithm for internal clinical target volume (iCTV) segmentation. DL-INIT uses this segmentation alongside template-based optimization, DL-DEF integrates it with a dose-mimicking (DM) step using a reference deformed dose, and DL-DL merges it with DM on a reference DL-predicted dose. All strategies were evaluated on manual contours and contours used for optimization and compared with manually adapted plans. Key dose volume metrics like iCTV D98% are reported. Main results. iCTV D98% was comparable in manually adapted plans and for all strategies in nominal cases but dropped to 20 Gy in worst-case scenarios for a few patients per strategy, highlighting the need to correct segmentation errors in the target volume. Evaluations on optimization contours showed minimal relative error, with some outliers, particularly in template-based strategies (DEF-INIT and DL-INIT). DL-DEF achieves a good trade-off between speed and dosimetric quality, showing a passing rate (iCTV D98% > 94%) of 90% when evaluated against 2, 4 and 5 mm setup error and of 88% when evaluated against 7 mm setup error. While template-based methods are more rigid, DL-DEF and DL-DL have potential for further enhancements with proper DM algorithm tuning. Significance. Among investigated strategies, DL-DEF and DL-DL demonstrated promising within 10 min OAPT implementation results and significant potential for improvements.
DBAII-Net with multiscale feature aggregation and cross-modal attention for enhancing infant brain injury classification in MRI
Authors: Jia Zhen , Huang Tingting , Li Xianjun , Bian Yitong , Wang Fan , Yuan Jianmin , Xu Guanghua , Yang Jian
Published: September 2024

Objectives. Magnetic resonance imaging (MRI) is pivotal in diagnosing brain injuries in infants. However, the dynamic development of the brain introduces variability in infant MRI characteristics, posing challenges for MRI-based classification in this population. Furthermore, manual data selection in large-scale studies is labor-intensive, and existing algorithms often underperform with thick-slice MRI data. To enhance research efficiency and classification accuracy in large datasets, we propose an advanced classification model. Approach. We introduce the Dual-Branch Attention Information Interactive Neural Network (DBAII-Net), a cutting-edge model inspired by radiologists’ use of multiple MRI sequences. DBAII-Net features two innovative modules: (1) the convolutional enhancement module (CEM), which leverages advanced convolutional techniques to aggregate multi-scale features, significantly enhancing information representation; and (2) the cross-modal attention module (CMAM), which employs state-of-the-art attention mechanisms to fuse data across branches, dramatically improving positional and channel feature extraction. Performances (accuracy, sensitivity, specificity, area under the curve (AUC), etc) of DBAII-Net were compared with eight benchmark models for brain MRI classification in infants aged 6 months to 2 years. Main results. Utilizing a self-constructed dataset of 240 thick-slice brain MRI scans (122 with brain injuries, 118 without), DBAII-Net demonstrated superior performance. On a test set of approximately 50 cases, DBAII-Net achieved average performance metrics of 92.53% accuracy, 90.20% sensitivity, 94.93% specificity, and an AUC of 0.9603. Ablation studies confirmed the effectiveness of CEM and CMAM, with CMAM significantly boosting classification metrics. Significance. DBAII-Net with CEM and CMAM outperforms existing benchmarks in enhancing the precision of brain MRI classification in infants, significantly reducing manual effort in infant brain research. Our code is available at https://github.com/jiazhen4585/DBAII-Net.
Modeling magnetic field amplification in supernova remnants driven by laser
Authors: Sun Wei , Lv Chong , Lei Zhu , Ping Yongli , Jin Mengqi , Tian Baoxian , Feng Li , Ren Can , He Cuhangye , Wang Zhao , Zhong Jiayong
Published: September 2024

The origin of magnetic fields and their amplification have always been hot topics in fields such as astrophysics and high-energy-density physics. Among them, the turbulent dynamo effect is an important candidate mechanism, and the interaction between supernova remnants (SNRs) is an important carrier for studying the amplification effect of turbulent magnetic fields. In this paper, we use the radiation magnetohydrodynamic simulation program to carry out a scaling simulation study on the amplification effect of turbulent magnetic fields in the interaction of SNRs driven by powerful lasers. We investigate and compare the evolution of turbulence under different laser driving methods, different directions, and different intensities of initial external environmental magnetic fields. Here, we carefully identify the contributions of Biermann self-generated magnetic fields and environmental magnetic fields in the process of magnetic field amplification, present magnetic energy spectra, and magnetic field amplification factors, and analyze the influence of radiative cooling effect on turbulence and magnetic field evolution. The results show that the collision direction component of the environmental magnetic field dominates the process of magnetic field amplification, and the frequency spectrum of turbulence is consistent with Kolmogorov’s law. The research results are necessary for sorting out and elucidating the physical mechanism of magnetic field amplification in SNRs, and have reference significance for regulating turbulence in strong magnetic fields in the future.
Design of piezoelectric quasi— zero—stiffness metastructures for improved low—frequency vibration isolation
Authors: Jiang Shouqian , Liu Zhiyuan , Yi Kaijun , Zhu Rui , Kovacic Ivana
Published: September 2024

In this paper, a novel type of piezoelectric quasi–zero stiffness (QZS) metastructure is proposed and the improved vibration isolation performance is investigated. A piezoelectric QZS metastructure is composed of curved beams covered with piezoelectric macro–fiber composite patches, to which digital circuits are connected. Based on the principle of minimum potential energy and the mode superposition method, the constrain on the geometry and material parameters of the piezo–curved beams to achieve QZS is given. According to this design criterion, 1D, 2D and 3D piezoelectric QZS metastructures are designed, and their improved low–frequency vibration isolation characteristics are comprehensively analyzed through theoretical, numerical and experimental studies. It is demonstrated that by optimizing the parameters of the resonant transfer functions implemented in the digital circuits, high–level damping localized near the first resonant peak can be introduced into the curved beams. As a result, the resonant peaks of the metastructures can be reduced without compromising the isolation performance beyond those peaks.
Design and manufacture of an ultra-compact, 1.5 T class, controlled-contact resistance, REBCO, brain imaging MRI magnet
Authors: Parkinson B , Bouloukakis K , Weijers H W , Olatunji J , Szmigiel M , Hunter M W , Froelich T , Bailey J , Garwood M
Published: September 2024

Brain imaging MRI comprises a significant proportion of MRI scans, but the requirement for including the shoulders in the magnet bore means there is not a significant size reduction in the magnet compared to whole-body magnets. Here we present a new design approach for brain imaging MRI magnets targeting ±20 kHz B
0 variation over the imaging volume rather than the more usual ±200 Hz making use of novel high-bandwidth MRI pulse sequences and distortion correction. Using this design approach, we designed and manufactured a 1.5 T class ReBCO cryogen-free magnet. The magnet is dome-like in form, completely excludes the shoulders and is <400 mm long. The magnet was wound using no-insulation style coils with a conductive epoxy encapsulant where the contact resistance of the coils was controlled so the emergency shut-down time of the magnet was less than 30 s. Despite acceptable coil testing results ahead of manufacture, during testing of the magnet, several of the epoxy coils showed signs of damage limiting stable performance to <55 A compared to the designed 160 A. These coils were replaced with insulated paraffin encapsulated coils. Subsequently the magnet was re-ramped and was stable at 81 A, generating 0.71 T as several other coils had sustained damage not visible in the first magnet iteration. The magnet has been passive shimmed to ±20 kHz B
0 variation over the imaging volume and integrated into an MRI scanner. The stability of the magnet has been evaluated and found to be acceptable for MRI.
Quantum multiphoton Rabi oscillations in waveguide QED
Authors: Mukhopadhyay Debsuvra , Shen Jung-Tsung
Published: September 2024

The future of quantum information processing hinges on chip-scale nanophotonics, specifically cavity QED and waveguide QED. One of the foremost processes underpinning quantum photonic technologies is the phenomenon of Rabi oscillations, which manifests when a qubit is irradiated by an intense laser source. Departing from the conventional semiclassical framework, we explore the more general, quantum theoretical case where the optical excitation takes the form of a multiphoton Fock state, and the qubit couples to a continuum of radiation modes. By employing the real-space formalism, we analytically explore the scattering dynamics of the photonic Fock state as it interfaces with a two-level emitter. The resulting amplitude for atomic excitation features a linear superposition of various independent scattering events that are triggered by the potential of sequential, time-delayed photon absorptions and emissions. The lowest-order excitation event, initiated by the stochastic scattering of one of the several photons, appropriately characterizes the dynamics in a weak-field environment. This event is complemented by a multitude of higher-order scattering events ensuing from repeated atom–photon interactions. The temporal evolution of the qubit excitation in our configuration closely mirrors the semiclassical predictions, particularly in the strong-pumping limit where Rabi oscillations unfold. Notably, this compatibility with the semiclassical paradigm transcends beyond the strong-excitation regime and applies both to the weak-driving and large-detuning limits. In a nutshell, our analysis extends the existing results on quantum Rabi oscillations pertinent to single-mode cavity QED, to the multimode, waveguide-QED configurations wherein flying photons are the information carriers. Additionally, we delve into the dynamics of pulsed wave packets, shedding light on the potential to substantially enhance excitation efficiency, even in scenarios involving just a few photons. Beyond their theoretical merit, these findings should hold practical relevance for future Fock-state-based quantum computing and emerging waveguide-integrated photonic technologies such as those involving superconducting circuitry.
Unbounded entropy production and violent fragmentation for repulsive-to-attractive interaction quench in long-range interacting systems
Authors: Molignini Paolo , Chakrabarti Barnali
Published: September 2024

We study the non-equilibrium dynamics of a one-dimensional Bose gas with long-range interactions that decay as

(

1

r

α

)

(
0.5
<
α
<
4.0

). We investigate exotic dynamics when the interactions are suddenly switched from strongly repulsive to strongly attractive, a procedure known to generate super-Tonks-Girardeau gases in systems with contact interactions. We find that relaxation is achieved through a complex intermediate dynamics demonstrated by violent fragmentation and chaotic delocalization. We establish that the relaxed state exhibits classical gaseous characteristics and an asymptotic state associated with unbounded entropy production. The phase diagram shows an exponential boundary between the coherent (quantum) gas and the chaotic (classical) gas. We show the universality of the dynamics by also presenting analogous results for spinless fermions. Weaker quench protocols give a certain degree of control over the relaxation process and induce a slower initial entropy growth. Our study showcases the complex relaxation behavior of tunable long-range interacting systems that could be engineered in state-of-the-art experiments, e.g. in trapped ions or Rydberg atoms.
Cooperative engulfment of nanoparticles by membranes and vesicles
Authors: Bahrami Arash , Bahrami Amir H
Published: September 2024

Cellular uptake and expulsion of nanoparticles and viruses often involves a substantial particle concentration at the cell membrane. These particles, many of which are distributed across the cell at relatively large distances, cooperate to enter or exit the cell, highlighting the importance of engulfment cooperativity. Here, we explore the cooperative entry and exit of two and multiple distant nanoparticles to and from curved vesicles, representing cellular endocytosis and exocytosis, respectively. We discover indirect engulfment cooperativity between distant nanoparticles wrapped by vesicles, driven by vesicle curvature, which is absent for particles engulfed by a flat bilayer. For the cooperative entry of two identical particles into the vesicle, we identify a counter-intuitive symmetry-breaking in which one fully-engulfed and one non-engulfed particle is more likely than two fully-engulfed or two non-engulfed particles. As a result, with a high concentration of closely-sized external particles, only half of the particles are expected to be successfully internalized by the vesicle, while the remaining half remains unwrapped, and partially engulfed particles are unlikely. In contrast, the cooperative exit of internal particles from the vesicle is characterized by the simultaneous partial engulfment of the particles that are continuously wrapped by the vesicle. This explains how evolution has harnessed membrane curvature for the simultaneous budding of multiple viral particles, a crucial step in viral infection. Our findings for the cooperative entry of multiple particles have significant implication for achieving efficient drug concentration in drug delivery applications.
2D Skyrmion topological charge of spin textures with arbitrary boundary conditions: a two-component spinorial BEC as a case study
Authors: Sánchez-Reséndiz S , Neri E , González-Hernández S , Romero-Rochín V
Published: September 2024

We derive the most general expression for the Skyrmion topological charge for a two-dimensional spin texture, valid for any type of boundary conditions or for any arbitrary spatial region within the texture. It reduces to the usual one for the appropriate boundary conditions. The general expression resembles the Gauss-Bonet theorem for the Euler-Poincaré characteristic of a 2D surface, but it has definite differences, responsible for the assignment of the proper signs of the Skyrmion charges. Additionally, we show that the charge of a single Skyrmion is the product of the value of the normal component of the spin texture at the singularity times the Index or winding number of the transverse texture, a generalization of a Poincaré theorem. We illustrate our general results analyzing in detail a two-component spinor Bose–Einstein condensate (BEC) in 2D in the presence of an external magnetic field, via the Gross-Pitaevskii equation. The condensate spin textures present Skyrmions singularities at the spatial locations where the transverse magnetic field vanishes. We show that the ensuing superfluid vortices and Skyrmions have the same value for their corresponding topological charges, in turn due to the structure of the magnetic field.
Study of nonlinear optical properties of ZnCo2O4/GQD nanocomposite and their correlation with microstructure
Authors: Ebrahimi Mahdi , Sadeghi Farzad , Soleimanian Vishtasb , Ghasemi Mohsen , Nekoeinia Mohsen
Published: September 2024

In this study, ZnCo2O4/Graphene quantum dots (ZCO/GQDs) nanocomposite was fabricated by carbonization and hydrothermal methods in four volume ratios (40.0 ml/0.0, 37.5 ml/2.5 ml, 35.0 ml/5.0 ml, and 32.5 ml /7.5 ml) of ZCO/GQD where the total volume was fixed at 40 ml. To characterize the structural, morphological, and optical properties of the nanocomposites, x-ray diffraction, scanning electron microscopy, energy dispersive x-ray, UV-visible spectrometry, and Z-scan analysis were conducted. The variance and Williamson-Smallman methods were applied to calculate the microstructure features. The results illustrate that the crystallite size and strain are minimum while the dislocation density has a maximum value for 37.5 ml/2.5 ml of volume ratio. Band gap and nonlinear optical coefficients were obtained by Tauc and Z-scan techniques and the results show they are maximum in this ratio. These results confirm a correlation between microstructure and optical properties. Such a correlation can be applied to improve the optoelectronic applications of the nanocomposite.
Transport mechanism investigation of β-Ga2O3 based fin-shape heterojunction PN diodes
Authors: Liu Peng , He Yunlong , Lu Xiaoli , Wang Xichen , Song Xianqiang , Sheng Baisong , Chen Weiwei , Wang Lei , Yang Jun , Wang Zhan , Li Yuan , Zheng Xuefeng , Ma Xiaohua , Hao Yue
Published: September 2024

This paper proposes a new type of Fin-shape Ga2O3 heterojunction PN diode (Fin-PND), it not only maintains a high breakdown voltage, but also increases the current density, thereby reducing the on-resistance. The conventional Schottky barrier diode (SBD) and PN diode (PND) are also prepared for comparison. The I-V characteristics, breakdown characteristics, and temperature stability of these three devices have been studied. It has been found that the Fin-PND has a lower turn-on voltage of 2.05 V due to the lower ND caused by Cl-based etching. Furthermore, the Fin-PND has a higher current density of 692.1 A cm−2 and specific on-resistance (Ron,sp) of 7.31 mΩ·cm2 compared to the conventional PND. In addition, the breakdown voltage of the Fin-PND is similar to that of the PND and higher than that of the SBD, reaching a value of 2380 V. The Fin-PND overcomes the contradiction of the current density rising at the expense of the breakdown voltage. Moreover, under the same variable temperature test conditions, the Fin-PND shows more favorable temperature stability.
Effects of PEO and BN-PVD coatings on the wear, corrosion, and surface properties of AZ31 magnesium alloy
Authors: Senocak Taha Cagri
Published: September 2024

This study investigates the effects of Plasma Electrolytic Oxidation (PEO) and subsequent Boron Nitride (BN) coatings applied via Physical Vapor Deposition (PVD) on the wear, corrosion, and surface properties of AZ31 magnesium alloy. The AZ31 alloy samples were first coated using the PEO process, forming a ceramic-like layer that enhances surface properties. However, inherent microcracks and pores in PEO coatings can compromise corrosion resistance. To mitigate these issues, a BN layer was applied over the some of PEO coating using RF-PVD, significantly improving wear resistance, corrosion protection, and surface integrity. The coatings were characterized using x-ray diffraction (XRD), scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS), and electrochemical testing. The results indicate that the PEO-BN coatings provide the highest wear resistance, lowest friction coefficient, and most effective barrier against corrosion among the samples tested. These findings highlight the potential of PEO-BN coatings to enhance the durability and performance of magnesium alloys, making them suitable for demanding applications.
Extreme multi-stability and circuit implementation for a two-ReLU-memristor-based jerk oscillator
Authors: Lu Rending , Chen Zhuguan , Lu Haikong , Bao Bocheng
Published: September 2024

Memristor-based oscillation circuits are prone to produce coexisting infinite attractors depending on the initial conditions of memristors, leading to the appearance of extreme multi-stability. In this paper, we propose a novel memristive jerk oscillator by bringing two ReLU-type memristors in a simple jerk oscillator and investigate its dynamical behaviors associated with the coupling parameters using bifurcation plots and Lyapunov exponent plots. Further, we discuss the planar equilibrium state and its stability, and then numerically explore the coexisting infinite attractors driven by the initial conditions of two ReLU-type memristors. Because of the intervention of the two ReLU-type memristors, the memristive jerk oscillator has a planar equilibrium state whose stability closely relies on the initial conditions of two ReLU-type memristors, and different initial conditions cause different attractors to coexist, resulting in bidirectional extreme multi-stability. Finally, the memristive jerk oscillator is implemented by analog circuit and digital hardware platform, and the numerical results are confirmed by circuit simulations and hardware experiments.
Quantum superposing algorithm for quantum encoding
Authors: Kim Jaehee , Kim Taewan , Baek Kyunghyun , Hwang Yongsoo , Huh Joonsuk , Bang Jeongho
Published: September 2024

Efficient encoding of classical data into quantum state—currently referred to as quantum encoding—holds crucial significance in quantum computation. For finite-size databases and qubit registers, a common strategy of the quantum encoding entails establishing a classical mapping that correlates machine-recognizable data addresses with qubit indices that are subsequently superposed. Herein, the most imperative lies in casting an algorithm for generating the superposition of any given number of qubit indices. This algorithm is formally known as quantum superposing algorithm. In this work, we present an efficient quantum superposing algorithm, affirming its effectiveness and superior computational performance in a practical quantum encoding scenario. Our theoretical and numerical analyses demonstrate a substantial enhancement in computational efficiency compared to existing algorithms. Notably, our algorithm has a maximum of 2n − 3 controlled-not (CNOT) counts, representing the most optimized result to date.