bluuebunny/crossref_metadata_2025 huggingface dataset:
Interfacial reactions in actively brazed Cu-Al2O3 composites and copper using a newly developed Cu-Sn-Ag-Ti filler alloy
Authors: Habibi Farzad , Samadi Ahad
Published: February 2023

In dissimilar brazing, the differences in physical properties between the components lead to residual stresses. An active filler alloy Cu-20.5Sn-20Ag-3.5Ti was developed to braze the Cu-Al2O3 composites (containing 25 and 50 volume pct. Al2O3) to copper. Two mechanisms were proposed for chemical bonding as a result of alumina reinforcements reduction by the active titanium, including the formation of Ti3(Cu,Al,Sn)3O layer beside the Ti2O in Cu/Cu-25%Al2O3 joints; and the solidification of Ti3(Cu,Al,Sn)3O in the vicinity of TiO layer/Cu4Ti islands in the Cu/Cu-50%Al2O3 joints. Some intermetallic compounds such as Cu3Ti2 and Cu41Sn11 are formed/coarsened with an extra increase in brazing temperature. An increase in brazing time improves the thickness of the TiOx layer with no sensible effect on Ti3(Cu,Al,Sn)3O width.
DMD maskless digital lithography based on stepwise rotary stitching
Authors: Yuan Qixiang , Liu Chunxia , Huang Long , Zhao Shaoqing , Wang Zhengxiao , Zhang Han , Liu Minzhe , Jia Zhongqing , Zhai Ruizhan , Lu Zifeng , Liu Hua
Published: February 2023

Diffractive optical elements (DOEs) with rotationally symmetric phase distribution are mainly produced by laser direct writing technique in a polar coordinate system, which has slow processing speed and limited fabrication area. In this paper, we propose a digital micro-mirror device maskless digital lithography technique based on stepwise rotary stitching. DOEs with rotationally symmetric phase distribution are fabricated by exposure of stitching units and rotation of rotary tables. Then, different stitching units are designed to compensate for the errors caused by the accuracy of the rotary table. Finally, the high quality DOEs are produced by the double-exposure method. When increasing the fabrication area, significantly improves the saw-tooth of the lithography pattern edge while reducing misalignment and overlap of stitching caused by residual errors. The diameter of the fabricated Fresnel zone plate was increased from 5.25 mm to 11.40 mm, and the fabrication area was 4.72 times larger than conventional lithography. The stitching error of 18.95 μm has been eliminated after optimization, and the pixelization has been smoothed. The diffraction results show that the method not only can produce large area and high-quality diffraction elements but also greatly reduce the processing cost.
The effect of DRIE notching on field emission enhanced breakdown in SOI based MEMS electrodes
Authors: Zhang Xuan , Qiao Dayong , Zhu Yao
Published: February 2023

Microscale (<5 μm) gas breakdown is usually dominated by field emission, which is influenced largely by electrode surface morphology. At present, there is a large number of studies on the breakdown and discharge of different metal electrode geometry and electrode spacing as well as micro-electro-mechanical system (MEMS) device structures, but few studies on the breakdown of MEMS electrodes affected by notching, which will greatly change the electrode surface morphology but is difficult to completely avoid in deep reactive ion etching process based on silicon on insulator (SOI) wafer. In response to this situation, this paper conducted breakdown tests and field emission tests on MEMS samples with and without notching. It was found that samples with notching could withstand more breakdowns of about 6–13 times before the formation of internal resistance, increased by 200%–300% compared with samples without notching, and have a lower breakdown voltage of about 210 V, 16% lower than that of samples without notching. In addition, it was also found that for the samples with notching, the field enhancement factor gradually decreases with the increase of the number of breakdown events. When the field enhancement factor decreases to about 100, the subsequent breakdown is highly likely to cause the sample to form electrical connection, thus completely damaging the sample. Above conclusions have certain reference value for designing the actuation voltage of MEMS devices based on SOI wafers.
Influence of magnetic relaxation on magnetoelastic resonance-based detection
Authors: Sisniega B , Gutiérrez J , Barandiaran J M , Porro J M , García-Arribas A
Published: February 2023

The phenomenon of magnetic relaxation in amorphous ferromagnetic alloys can result in an undesired time evolution of the magnetization that produces serious drawbacks in the use of these materials in sensor applications. The present work studies, at room temperature, the influence of magnetic relaxation on the performance of an amorphous ferromagnetic ribbon as the main element of a magnetoelastic resonance (MER)-based sensor. The time evolution was observed through the evolution of the MER signal, in particular through the variation experienced by the resonance frequency

f

r

, which is the main parameter used for sensing. It is found that, after the bias field is changed to a given value, and under constant excitation conditions,

f

r

increases with time in a typical relaxation behavior with a relaxation amplitude

Δ

f

r

and a relaxation time

τ

that depend on the excitation conditions. The amplitude of the excitation h turned out to be a key factor on the relaxation, since larger excitation field amplitudes (h

⩾
100

mOe) result in a considerable decrease of relaxation times (

τ
<
460

 s

)

and a reduction of the variation of the resonance frequency (

Δ

f

r

<
77

 Hz

). The influence of this relaxation on the sensor performance and the possible approaches to overcome this problem are evaluated and applied to the case of a magnetoelastic sensor, operating as mass sensor, for monitoring a chemical precipitation reaction.
Dynamics of recombination in viscous electron–hole plasma in a mesoscopic GaAs channel
Authors: Pusep Yu A , Teodoro M D , T Patricio M A , M Jacobsen G , Gusev G M , Levin A D , Bakarov A K
Published: February 2023

The recombination dynamics are studied in viscous electron–hole plasma, consisting of electrons and photo-generated heavy and light holes, formed in the high-mobility mesoscopic GaAs channel. It is shown that an increase in the pump power reduces the concentration and mobility of background electrons, which, in turn, slows down their recombination with photogenerated holes. At a critical pump power, the recombination time begins to decrease, which is a consequence of the transition of a viscous electron–hole plasma from the hydrodynamic regime to the Drude diffusive regime. The observed transition occurs when the scattering of electrons with disorder begins to dominate over electron–electron scattering, which leads to the transformation of an inhomogeneous Poiseuille charge flow into a homogeneous diffusion flow. As a result, an optical analogue of the Gurzhi effect has been found.
Engineering Pt/Co/AlO
x
heterostructures to enhance the Dzyaloshinskii–Moriya interaction
Authors: Sankhi Babu R , Echeverria Elena M , Mandal Soumya , Annaorazov Muhammet , Sachan Ritesh , Mcllroy David N , Meyers Derek , Turgut Emrah
Published: February 2023

The study of interfacial Dzyaloshinskii–Moriya interaction (DMI) in perpendicularly magnetized structurally asymmetric heavy metal/ferromagnet multilayer systems is of high importance due to the formation of chiral magnetic textures in the presence of DMI. Here, we report the impact of cobalt oxidation at the Co/AlO
x
interface in Pt/Co/AlO
x
trilayer structures on the DMI by varying the post-growth annealing time, Al thickness and substrate. To quantify DMI we employed magneto-optical imaging of the asymmetric domain wall expansion, hysteresis loop shift, and spin-wave spectroscopy techniques. We further correlated the Co oxidation with low-temperature Hall effect measurements and x-ray photoelectron spectroscopy. Our results emphasize the importance of full characterization of the magnetic films that could be used for magnetic random access memory technologies when subjected to the semiconductor temperature processing conditions, as the magnetic interactions are critical for device performance and can be highly sensitive to oxidation and other effects.
Non-self-similar grain growth by zero-temperature Potts model
Authors: Zöllner D
Published: February 2023

Self-similar coarsening, a well-researched aspect of normal grain growth, is a key component of grain growth theories and visible in mesoscopic simulations of ideal grain growth. One particular simulation algorithm is the Potts model, which can be used to perform a thorough investigation of the temporal evolution of polycrystalline microstructures. Used with carefully selected parameters, the Potts model recreates normal grain growth quite accurately. One specific feature necessary to reach this goal is the simulation temperature, i.e. simulation thermal energy. It prevents grain boundaries from aligning along the underlying simulation lattice. Nevertheless, there are still today many researchers who implement classical zero-temperature Potts model simulations—often for reasons of simplification and/or modeling speed. In the current study, we show in detail the negative effect of setting the simulation temperature to zero. As a result, a unique type of non-self-similar coarsening is observed, where, e.g. the von Neumann–Mullins-relation shows unexpected time-dependent behavior. Hence, this study can be understood as a blueprint on why not to use a zero-temperature Potts model.
Cellulose nanocrystal functionalized aramid nanofiber reinforced epoxy nanocomposites with high strength and toughness
Authors: Jung Jaehyun , Sodano Henry A
Published: February 2023

The mechanical properties of polymer nanocomposites can be improved by incorporating various types of nanofillers. The hybridization of nanofillers through covalent linkages between nanofillers with different dimensions and morphology can further increase the properties of nanocomposites. In this work, aramid nanofibers (ANFs) are modified using chlorinated cellulose nanocrystals (CNCs) and functionalized with 3-glycidoxypropyltrimethoxysilane to improve the chemical and mechanical interaction in an epoxy matrix. The integration of CNC functionalized ANFs (fACs) in the epoxy matrix simultaneously improves Young’s modulus, tensile strength, fracture properties, and viscoelastic properties. The test results show that 1.5 wt% fAC reinforced epoxy nanocomposites improve Young’s modulus and tensile strength by 15.1% and 10.1%, respectively, and also exhibit 2.5 times higher fracture toughness compared to the reference epoxy resin. Moreover, the glass transition temperature and storage modulus are found to increase when fACs are incorporated. Thus, this study demonstrates that the enhanced chemical and mechanical interaction by the CNC functionalization on the ANFs can further improve the static and dynamic mechanical properties of polymer nanocomposites.
Design and characteristic analysis of flexible CNT film patch for potential application in ultrasonic therapy
Authors: Feng Yanxia , Zhang Qilin , Li Houyang , Qi Qianshou , Tong Zhenzhen , Rong Dalun , Zhou Zhenhuan
Published: February 2023

Ultrasonic therapy has drawn increasing attention due to its noninvasiveness, great sensitivity and strong penetration capabilities. However, most of traditional rigid ultrasonic probes cannot achieve a solid interfacial contact with irregular nonplanar surfaces, which leads to unstable therapeutic effects and limitations of widespread use in practical applications. In this paper, a new flexible ultrasonic patch based on carbon nanotube (CNT) films is designed and fabricated to achieve a potential application in ultrasonic therapy. This patch is composed of a CNT film, a thermal protective layer and a heat sinking layer, and has the advantages of simple structure, soft, ultrathin and completely conforming to the treatment area. Theoretical and experimental studies are performed to investigate the acoustic and temperature fields before and after deformation. Effects of key design parameters of the patch on acoustic performances and temperature distributions are revealed. Numerical results indicate that the CNT film patch can produce ultrasounds over a wide frequency range and temperatures under the threshold of burn injury whether it is bent or not. Furthermore, it is also noted that the sound waves emitted from the bending patch are focused at the center of the bending patch, which demonstrates that the target treatment area can be controlled.
Mesoscopic 2D molecular self-assembly on an insulator
Authors: Kumar Dhaneesh , Hellerstedt Jack , Lowe Benjamin , Schiffrin Agustin
Published: February 2023

Two-dimensional (2D) nanostructures and nanomaterials offer potential for a wide range of technological applications in electronics, optoelectronics, data storage, sensing and catalysis. On-surface molecular self-assembly – where organic molecules act as building blocks and where surfaces play the role of supporting templates – allows for the bottom-up synthesis of such 2D systems with tuneable atomically precise morphologies and tailored electronic properties. These self-assembly protocols are well established on metal surfaces, but remain limited on electronically gapped substrates (insulators, semiconductors). The latter are useful for preventing electronic coupling (that is, hybridization between molecular assembly and underlying surface) and for avoiding quenching of optical processes, necessary for prospective electronic and optoelectronic applications. In particular, molecular self-assembly on surfaces other than weakly interacting metals can be challenging due to substrate reactivity, defects and inhomogeneities, resulting in intricate energy landscapes that limit the growth kinetically and hampers the synthesis of large-area defect-free 2D systems. Here, we demonstrate the self-assembly of a 2D, atomically thin organic molecular film on a model wide bandgap 2D insulator, single-layer hexagonal boron nitride (hBN) on Cu(111). The molecular film consists of flat, aromatic 9,10-di-cyano-anthracene (DCA) molecules. Our low-temperature scanning tunnelling microscopy and spectroscopy measurements revealed mesoscopic (> 100 x 100 nm^2), topographically homogeneous crystalline molecular domains resulting from flat molecular adsorption and noncovalent in-plane cyano-ring bonding, with electronically decoupled molecular orbitals (MOs) lying within the hBN electronic gap. These MOs exhibit an energy level spatial modulation (~300 meV) that follows the moiré work function variation of hBN on Cu(111). This work paves the way for large-area, atomically precise, highly crystalline 2D organic (and metal-organic) nanomaterials on electronically functional wide bandgap insulators.
Deep learning based unpaired image-to-image translation applications for medical physics: a systematic review
Authors: Chen Junhua , Chen Shenlun , Wee Leonard , Dekker Andre , Bermejo Inigo
Published: February 2023

Purpose. There is a growing number of publications on the application of unpaired image-to-image (I2I) translation in medical imaging. However, a systematic review covering the current state of this topic for medical physicists is lacking. The aim of this article is to provide a comprehensive review of current challenges and opportunities for medical physicists and engineers to apply I2I translation in practice.Methods and materials. The PubMed electronic database was searched using terms referring to unpaired (unsupervised), I2I translation, and medical imaging. This review has been reported in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. From each full-text article, we extracted information extracted regarding technical and clinical applications of methods, Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) study type, performance of algorithm and accessibility of source code and pre-trained models.Results. Among 461 unique records, 55 full-text articles were included in the review. The major technical applications described in the selected literature are segmentation (26 studies), unpaired domain adaptation (18 studies), and denoising (8 studies). In terms of clinical applications, unpaired I2I translation has been used for automatic contouring of regions of interest in MRI, CT, x-ray and ultrasound images, fast MRI or low dose CT imaging, CT or MRI only based radiotherapy planning, etc Only 5 studies validated their models using an independent test set and none were externally validated by independent researchers. Finally, 12 articles published their source code and only one study published their pre-trained models.Conclusion. I2I translation of medical images offers a range of valuable applications for medical physicists. However, the scarcity of external validation studies of I2I models and the shortage of publicly available pre-trained models limits the immediate applicability of the proposed methods in practice.
Novel framework for determining TPS-calculated doses corresponding to detector locations using 3D camera in in vivo surface dosimetry
Authors: Sheen Heesoon , Park Ye-in , Cho Min-Seok , Son Junyoung , Shin Han-Back , Han Min Cheol , Kim Hojin , Lee Ho , Kim Dong Wook , Kim Jin Sung , Hong Chae-Seon
Published: February 2023

Purpose. To address the shortcomings of current procedures for evaluating the measured-to-planned dose agreement in in vivo dosimetry (IVD), this study aimed to develop an accurate and efficient novel framework to identify the detector location placed on a patient’s skin surface using a 3D camera and determine the planned dose at the same anatomical position corresponding to the detector location. Methods. Breast cancer treatment was simulated using an anthropomorphic adult female phantom (ATOM 702D; CIRS, Norfolk, VA, USA). An optically stimulated luminescent dosimeter was used for surface dose measurements (MyOSLchip, RadPro International GmbH, Germany) at six IVD points. Three-dimensional surface imaging (3DSI) of the phantom with the detector was performed in the treatment position using a 3D camera. The developed framework, iSMART, was designed to import 3DSI and treatment planning data for determining the position of the IVD detectors in the 3D treatment planning DICOM image. The clinical usefulness of iSMART was evaluated in terms of accuracy and efficiency, for comparison with the results obtained using cone-beam computed tomography (CBCT) image guidance. Results. The relative dose difference between the planned doses determined using iSMART and CBCT images displayed similar accuracies (within approximately ±2.0%) at all detector locations. The relative dose differences between the planned and measured doses at the six detector locations ranged from –4.8% to 3.1% for the CBCT images and –3.5% to 2.1% for iSMART. The total time required to read the planned doses at six detector locations averaged at 8.1 and 0.8 min for the CBCT images and iSMART, respectively. Conclusions. The proposed framework can improve the robustness of IVD analyses and aid in accurate and efficient evaluations of the measured-to-planned dose agreement.
Full waveform inversion for arterial viscoelasticity
Authors: Roy Tuhin , Guddati Murthy N
Published: February 2023

Objective. Arterial viscosity is emerging as an important biomarker, in addition to the widely used arterial elasticity. This paper presents an approach to estimate arterial viscoelasticity using shear wave elastography (SWE). Approach. While dispersion characteristics are often used to estimate elasticity from SWE data, they are not sufficiently sensitive to viscosity. Driven by this, we develop a full waveform inversion (FWI) methodology, based on directly matching predicted and measured wall velocity in space and time, to simultaneously estimate both elasticity and viscosity. Specifically, we propose to minimize an objective function capturing the correlation between measured and predicted responses of the anterior wall of the artery. Results. The objective function is shown to be well-behaving (generally convex), leading us to effectively use gradient optimization to invert for both elasticity and viscosity. The resulting methodology is verified with synthetic data polluted with noise, leading to the conclusion that the proposed FWI is effective in estimating arterial viscoelasticity. Significance. Accurate estimation of arterial viscoelasticity, not just elasticity, provides a more precise characterization of arterial mechanical properties, potentially leading to a better indicator of arterial health.
Screening left ventricular systolic dysfunction in children using intrinsic frequencies of carotid pressure waveforms measured by a novel smartphone-based device
Authors: Cheng Andrew L , Liu Jing , Bravo Stephen , Miller Jennifer C , Pahlevan Niema M
Published: February 2023

Objective. Children with heart failure have higher rates of emergency department utilization, health care expenditure, and hospitalization. Therefore, a need exists for a simple, non-invasive, and inexpensive method of screening for left ventricular (LV) dysfunction. We recently demonstrated the practicality and reliability of a wireless smartphone-based handheld device in capturing carotid pressure waveforms and deriving cardiovascular intrinsic frequencies (IFs) in children with normal LV function. Our goal in this study was to demonstrate that an IF-based machine learning method (IF-ML) applied to noninvasive carotid pressure waveforms can distinguish between normal and abnormal LV ejection fraction (LVEF) in pediatric patients. Approach. Fifty patients ages 0 to 21 years underwent LVEF measurement by echocardiogram or cardiac magnetic resonance imaging. On the same day, patients had carotid waveforms recorded using Vivio. The exclusion criterion was known vascular disease that would interfere with obtaining a carotid artery pulse. We adopted a hybrid IF- Machine Learning (IF-ML) method by applying physiologically relevant IF parameters as inputs to Decision Tree classifiers. The threshold for low LVEF was chosen as <50%. Main results. The proposed IF-ML method was able to detect an abnormal LVEF with an accuracy of 92% (sensitivity = 100%, specificity = 89%, area under the curve (AUC) = 0.95). Consistent with previous clinical studies, the IF parameter

ω

1

was elevated among patients with reduced LVEF. Significance. A hybrid IF-ML method applied on a carotid waveform recorded by a hand-held smartphone-based device can differentiate between normal and abnormal LV systolic function in children with normal cardiac anatomy.
Exploration of temperature stability of linearity and RF performance metrics for PGP negative capacitance FET
Authors: Chaudhary Shalini , Dewan Basudha , Singh Devenderpal , Sahu Chitrakant , Yadav Menka
Published: February 2023

The present work focuses on investigating the performance of partial ground plane selective buried oxide negative capacitance (NC) field-effect transistor (NCFET) electrical properties at high temperatures. The performance of the device has been studied between the temperature of 300–400 K using the Landau–Khalatnikov equation with the Poisson’s equation. In NCFET, ferroelectric material in the gate stack generates NC effect that enhances the device performance by the voltage amplification process. Doped

H
F

O

2

is used as the ferroelectric material because of its high dielectric capacitance and reliable polarization rate. This work primarily focuses on examining the effects of temperature change on the device’s dc performance metrics, analog/radio frequency performance parameters, and linearity performance parameters. Compared to kT/q, sub-threshold slope rises more rapidly as temperature rises and diminishing the ferroelectric effect after 350 K. Also reduced intrinsic delay at higher temperatures make the device an great option for ultra-low-power and high switching speed applications. Additionally, the proposed device performs better in terms of linearity at greater temperatures.
Machine learning based modeling of disordered elemental semiconductors: understanding the atomic structure of a-Si and a-C
Authors: Caro Miguel A
Published: February 2023

Disordered elemental semiconductors, most notably a-C and a-Si, are ubiquitous in a myriad of different applications. These exploit their unique mechanical and electronic properties. In the past couple of decades, density functional theory (DFT) and other quantum mechanics-based computational simulation techniques have been successful at delivering a detailed understanding of the atomic and electronic structure of crystalline semiconductors. Unfortunately, the complex structure of disordered semiconductors sets the time and length scales required for DFT simulation of these materials out of reach. In recent years, machine learning (ML) approaches to atomistic modeling have been developed that provide an accurate approximation of the DFT potential energy surface for a small fraction of the computational time. These ML approaches have now reached maturity and are starting to deliver the first conclusive insights into some of the missing details surrounding the intricate atomic structure of disordered semiconductors. In this Topical Review we give a brief introduction to ML atomistic modeling and its application to amorphous semiconductors. We then take a look at how ML simulations have been used to improve our current understanding of the atomic structure of a-C and a-Si.
First performance test of FeSe0.5Te0.5 coated conductor coil under high magnetic fields
Authors: Wei Shaoqing , liu xiao , Zhang Zhan , Shi Yi , Liu Fang , Qin Jinggang , Liu Huajun , Song Yuntao , Li Yijie , Liu Linfei , Shi Zhixiang , Ren Li , Xu Ying , Duan Pu , Yang Zhixing , Ge Junyi , Qi Yanpeng
Published: February 2023

Iron-based superconductors (IBS) have attracted intense interest from scientists around the world. The first FeSe0.5Te0.5 hybrid coil including one FeSe0.5Te0.5 single pancake coil (SPC) and eight YBCO double pancake coils (DPCs) was successfully fabricated and test in this study. The FeSe0.5Te0.5 tape used in the hybrid coil is encapsulated strengthen tape which is with 0.15 mm thickness and 10.5 mm width to withstand the high stress during the cold test. The FeSe0.5Te0.5 encapsulated tape exhibits good performance at 4.2 K cold test. YBCO DPCs were divided into two groups connected to both sides of the FeSe0.5Te0.5 SPC. The critical current of the FeSe0.5Te0.5 coil was measured under the background field increased from 0 T to 10 T. The transport critical current of the FeSe0.5Te0.5 SPC showed 108.1 A at self-field and 17.4 A at 10 T, which had almost the same performance as the short sample. The results in this study showed that the FeSe0.5Te0.5 coated conductor coil have good performance in high magnetic fields.
Simulating the effects of fabrication tolerance on the performance of Josephson travelling wave parametric amplifiers
Authors: Ó Peatáin S , Dixon T , Meeson P J , Williams J M , Kafanov S , Pashkin Yu A
Published: February 2023

We present the simulated performance of a Josephson traveling wave parametric amplifier based on a one-dimensional array of radio-frequency single-junction superconducting quantum interference devices. Using the capabilities allowed by the WRspice simulation platform and previous works on this scheme, we include in our study the effects of fabrication tolerances in the device parameters on the gain of the amplifier. Our simulations show the negative effects of parameter variation and the resulting microwave reflections of signal and pump waves between individual cells. We present a method to understand the inner dynamics of the device using an impedance model that substitutes the need to simultaneously consider phase bias points and wave mixing dynamics. This should allow the application of the results presented here to more complex schemes, which promise higher amplification and fewer drawbacks. We highlight the strict limitations on parameter spread in these devices while also discussing the robustness of the scheme to defects.
Stable wavelength-swept single-frequency erbium fiber laser in L-band tuning bandwidth
Authors: Lai Yu-Ting , Chen Yuan-You , Chen Hao-Zhong , Yeh Chien-Hung , Lin Chun-Yen , Chen Ying-Zhen , Liao Chien-Yu , Chang Dung-Chiun , Chen Lan-Yin , Chow Chi-Wai
Published: February 2023

In the study, we demonstrate an erbium-doped fiber (EDF) laser system by integrating the Mach–Zehnder interferometer (MZI) and triple-fiber-ring structures to generate the single-longitudinal-mode (SLM) output in L-band bandwidth. Here, a sub-ring with a 5.5 m unpumped EDF based saturable absorber (SA) is also applied to induce the narrowband auto-tracking filter behavior. Based on the proposed fiber cavity induced mode-filter effect, the EDF laser can achieve the stable, narrow and wavelength-tunable output characteristics over an effective tuning range of 1568.0 to 1613.0 nm. Furthermore, the output stability, optical signal to noise ratio (OSNR), output power and laser linewidth of the laser are also performed and discussed.
Independently tunable concentric graphene ring resonators based ultrathin broadband THz absorber
Authors: Kumar Abhishek , Varshney Gaurav
Published: February 2023

An ultrathin structure of graphene-based absorber is implemented and numerically analyzed. The absorber is designed with the usage of graphene ring resonators and graphene reflector in the lower terahertz (THz) frequency ranges. The geometry of the absorber can be implemented with the thickness as small as λ/193; (λ: free space wavelength). A number of resonances is generated using concentric graphene ring resonators which can individually tuned over frequency using chemical potential of graphene for merging and achieving the broad absorption band. An absorption of more than 90% is achieved over the frequency range of 10.34–16.23 THz and more than 80% in the frequency range of 9.89–16.77 THz. The proposed absorber provides the polarization independent geometry with the allowed incident angle up to 50°. The ultrathin geometry of the proposed absorber can provide a way to implement the absorber with broad absorption bandwidth.
A novel fractal-fractional analysis of the stellar helium burning network using extended operational matrix method
Authors: Shloof A M , Senu N , Ahmadian A , Nouh M I , Salahshour S
Published: February 2023

The second stage, in which the star uses nuclear fuel in its interior, represents the helium burning phase. At that stage, three elements are synthesised: carbon, oxygen, and neon. This paper aims to establish a numerical solution for the helium burning system (HBN) fractal-fractional differential equations (FFDEs). The extended operative matrix method (OM) is employed in the solution of a system of differential equations. The product abundances of the four elements (helium, carbon, oxygen and neon) were obtained in a form of divergent series. These divergent series are then accelerated using Euler-Abell transformation (EUAT) and Pade approximation (EUAT-PA) to obtain more reliable results. Nine fractal-fractional (FF) gas models are calculated, and fractal-fractional parameters’ influence on product abundances is discussed. The findings show that modeling nuclear burning networks with the OM fractal-fractional derivative produces excellent results, establishing it as an accurate, resilient, and trustworthy approach, and the fractional HB models can have a considerable impact on stellar model calculations.
Molecular dynamics study of the repetitive friction mechanism of nickel-based single crystals in an aqueous environment
Authors: Zheng Ming , Zhang Zhou , Zhu Zongxiao , Qu Dingfeng , Chen Weihua , Wu Zhuo , Wang Linjun , Ma Xuezhong
Published: February 2023

In this study, molecular dynamics simulations were used to simulate the iterative rotational friction of nickel-based single crystals using diamond grinding balls in both the presence and absence of water. First, the friction force, depth and morphology of wear marks, wear rate, and evolution of internal defects during the friction process of nickel-based single crystals were investigated. Second, a comparative study of the frictional wear of nickel-based single crystals in both the presence and absence of water was carried out in terms of temperature, water molecule distribution, atomic displacement vector, and wear scar depth during the friction process. Finally, the formation process of irregular grinding chips under aqueous conditions was elucidated. The following phenomena were observed: As the number of rubs increased, the single rub depth of the workpiece, the wear rate, and the rate of increase in the number of defective atoms produced all decreased. A comparison of friction under aqueous and water-free conditions showed that, in the presence of water, the force exerted by the grinding ball on the workpiece was shared by the water molecules. This resulted in a decrease in the roughness of the machined surface, a reduction in the number of internally generated layer errors, a lower overall friction temperature, and a nickel matrix that was protected by water molecules. Finally, when grinding under aqueous conditions, water molecules interfered with the normal chip removal process of the grinding balls, leading to the production of irregular grinding chips.
The effect of collisions on the rayleigh-taylor instability in magnetized quantum plasma
Authors: Rajaei Leila , Golpar-Raboky Effat
Published: February 2023

Rayleigh-Taylor instability occurs at the interface between light and heavy fluids whenever the heavier fluid is accelerated by the light one. An important issue is the stability conditions of these systems. Various parameters such as density difference between two fluids, density inhomogeneity length, magnetic field, viscosity, collision can affect the stabilization or destabilization of the system. So far, some of these factors have been investigated in the fields of classical and quantum physics. This process has also been studied in both linear and nonlinear states. Here we consider a collisional magnetic inhomogeneous quantum plasma. For the inhomogeneity profile of density as an exponential function, we calculated the second ordinary equation for the disturbed velocity. Since the differential equation does not have an analytical solution, we have calculated the growth rate curve using numerical methods and obtained the disturbed velocity profile in the discontinuity. Then the effects of different parameters such as collision, magnetic field, quantum effects, and density difference of two fluids on the system stabilization are studied. The various branches of the instability growth rate curve and its relationship with the turbulent velocity profile in discontinuity are also discussed.
A novel method for predicting the occurrence of the large-scale shunting in the reverse-polarity plasma torch
Authors: Yin Zhengxin , Yu Deping , Xiao Yu , Zhang Qingbo , Qiu Jier
Published: February 2023

The reverse-polarity plasma torch (RPT) is a promising high enthalpy plasma source for material processing, e.g. plasma atomization for spherical powders and plasma synthesis for the nanostructured carbon. The quality and yield of the final product highly depend on the working stability of the RPT, which may be undermined by the large-scale shunting. Large-scale shunting is an abnormal discharge phenomenon existed in the RPT, which leads to the sudden drop of the arc voltage and shrink of the generated plasma jet. Inter-electrodes between the cathode and anode are designed to limit arc fluctuations and thus large-scale shuntings. However, the construction and maintenance of the RPT with inter-electrodes are highly complex. To alleviate the large-scale shunting and retain the advantage of simple structure of the conventional RPT, a novel method for predicting the occurrence of the large-scale shunting is proposed for optimizing the RPT’s internal structure and operation condition. The method is based on the thermal non-equilibrium modelling of the RPT to calculate the thickness of the cold boundary layer (CBL) and breakdown voltage. Then, the occurrence of the large-scale shunting is predicted by comparing the breakdown voltage with the voltage drop between the electrode inner surface and arc column. Three different shapes of the front electrode (cathode) corresponding to different thicknesses of the cold boundary layer (CBL) were manufactured based on the proposed numerical method. Experimental and numerical studies on the effect of the electrode geometry, arc current and gas flow rate on the working stability of the RPT and thickness of the CBL were conducted. Results showed the quantitative correlations between operating parameters and the instability of the RPT and verified that the proposed numerical method is useful for optimizing the design and operation of the plasma torch with minimizing large-scale shunting instabilities.
Singlet vector-like T quark production in association with Wb at the CLIC
Authors: Yang Bingfang , Wang Shiyu , Sima Xiaoli , Shang Liangliang
Published: February 2023

In a simplified model including an SU(2) singlet vector-like top quark T (VLT) with charge 2/3, we investigate the associated production of Wb with VLT at a Compact Linear Collider (CLIC). Focusing on the T → Wb decay channel, we discuss two decay models:

e

+

e

−

→

T

¯

W

+

b
→
(

l

−

ν

¯

b

¯

)
(
jjb
)

and

e

+

e

−

→

T

¯

W

+

b
→
(
jj

b

¯

)
(

l

+

ν
b
)

. In this paper, we consider recent experimental limits including the electroweak precision observables, the width of the top quark, and the direct LHC searches. Through a detailed detector simulation, we show the exclusion and discovery capability on the T at 3 TeV CLIC, where the initial state radiation effect has also been considered. The results show that it is promising to detect the VLT at future high-energy e
+
e
− colliders.
Reconstruction and stability of Fe3O4 (001) surface: An investigation based on particle swarm optimization and machine learning
Authors: Liu Hongsheng , Zhao Yuanyuan , Qiu Shi , Zhao Jijun , Gao Junfeng
Published: February 2023

Magnetite nanoparticles show promising applications in drug delivery, catalysis, and spintronics. The surface of magnetite plays an important role in these applications. Therefore, it is critical to understand the surface structure of Fe3O4 at atomic scale. Here, using a combination of first-principles calculations, particle swarm optimization (PSO) method and machine learning, we investigate the possible reconstruction and stability of Fe3O4(001) surface. The results show that besides the subsurface cation vacancy (SCV) reconstruction, an A layer with Fe vacancy (A-layer-VFe) reconstruction of the (001) surface also shows very low surface energy especially at oxygen poor condition. Molecular dynamics simulation based on the iron–oxygen interaction potential function fitted by machine learning further confirms the thermodynamic stability of the A-layer-VFe reconstruction. Our results are also instructive for the study of surface reconstruction of other metal oxides.
Tunable phonon–atom interaction in a hybrid optomechanical system
Authors: Li Yao , Li Chuang , Zhang Jiandong , Dong Ying , Hu Huizhu
Published: February 2023

We theoretically analyze a hybrid system consisting of a levitated neutral atom and a nanoparticle coupled to a cavity. The mechanical oscillator and the atom are effectively coupled to each other through the cavity photons as a bus. By adjusting the driving lasers, we can conveniently switch the phonon–atom coupling between Jaynes–Cummings (JC) and anti-JC forms, which can be used to manipulate the motional states of the mechanical oscillator. As an application, we prepare a superposition state of the mechanical oscillator via the effective phonon–atom interaction and investigate the effects of dissipation on the state generation.
Mutation detection and fast identification of switching system based on data-driven method
Authors: Zhang Zhonghua , Xu Wei , Song Yi
Published: February 2023

In the engineering field, switching systems have been extensively studied, where sudden changes of parameter value and structural form have a significant impact on the operational performance of the system. Therefore, it is important to predict the behavior of the switching system, which includes the accurate detection of mutation points and rapid reidentification of the model. However, few efforts have been contributed to accurately locating the mutation points. In this paper, we propose a new measure of mutation detection — the threshold-based switching index by analogy with the Lyapunov exponent. We give the algorithm for selecting the optimal threshold, which greatly reduces the additional data collection and the relative error of mutation detection. In the system identification part, considering the small data amount available and noise in the data, the abrupt sparse Bayesian regression (abrupt-SBR) method is proposed. This method captures the model changes by updating the previously identified model, which requires less data and is more robust to noise than identifying the new model from scratch. With two representative dynamical systems, we illustrate the application and effectiveness of the proposed methods. Our research contributes to the accurate prediction and possible control of switching system behavior.
A progressive surrogate gradient learning for memristive spiking neural network
Authors: Wang Shu , Chen Tao , Gong Yu , Sun Fan , Shen Si-Yuan , Duan Shu-Kai , Wang Li-Dan
Published: February 2023

In recent years, spiking neural networks (SNNs) have received increasing attention of research in the field of artificial intelligence due to their high biological plausibility, low energy consumption, and abundant spatio-temporal information. However, the non-differential spike activity makes SNNs more difficult to train in supervised training. Most existing methods focusing on introducing an approximated derivative to replace it, while they are often based on static surrogate functions. In this paper, we propose a progressive surrogate gradient learning for backpropagation of SNNs, which is able to approximate the step function gradually and to reduce information loss. Furthermore, memristor cross arrays are used for speeding up calculation and reducing system energy consumption for their hardware advantage. The proposed algorithm is evaluated on both static and neuromorphic datasets using fully connected and convolutional network architecture, and the experimental results indicate that our approach has a high performance compared with previous research.
Energy Management Strategy for Shared Battery Energy Storage Systems Considering Economy and SOC Consistency
Authors: Li Hanning , Li Xiangjun , Chen Dawei , Li Zhicheng , Zhang Weijun , Dong Lizhi , Deng Chaoping
Published: February 2023

in an effort to solve the large fluctuation of renewable energy power generation output, which brings many challenges to power system operation, Battery Energy Storage Systems (BESS) are more and more widespread in power systems. This paper proposes an energy management strategy for shared energy storage power plants. First, the shared energy storage power plants are divided into different PCS unit groups, which trade according to different electricity prices. Secondly, the charging and discharging priorities of PCS unit groups are ranked according to the electricity price to maximize the benefits. At the same time, considering the consistency of system SOC (state of charge), the system has higher stability, and more average battery SOC is conducive to better scheduling of BESS. The trade model of a 100MW shared energy storage power station is built in this paper to verify the effectiveness of this method.
Construction of Battery Health Monitoring System for New Energy Vehicles from a Multi-dimensional Perspective
Authors: Cao Yu , Liang Hongyu , Peng Wenliang , Su Yu
Published: February 2023

With the continuous development of the national economy, new energy vehicles, as eco-friendly and low-carbon transportation tools, are gradually promoted by various countries and societies. Electric vehicles account for the highest proportion of new energy vehicles. Therefore, this study analyzed the battery health monitoring of new energy vehicles. By building a relevant evaluation index system, the paper quantified the battery health status to obtain the healthy life of the battery through the evaluation method. Experimental analysis shows that the method proposed in this study has a certain accuracy and can provide auxiliary decision support for relevant departments.
Research on optimal scheduling of thermal power system in thermal power plant based on deep reinforcement learning
Authors: Wang Pan , Liu Ye
Published: February 2023

Optimal dispatch is one of the key technologies to realize the efficient and economical operation of the thermal power system in thermal power plants. In order to reduce the energy consumption of thermal power system in thermal power plants, ensure the optimal dispatching effect and improve the efficiency of optimal dispatching, this paper introduces deep reinforcement learning to design a new optimal dispatching method for thermal power system in thermal power plants. The thermal power system structure of thermal power plant is analyzed, and the models of boiler, steam turbine and temperature and pressure reducer are established. The optimal scheduling problem of steam turbine and boiler thermal system is studied. By setting the objective function and determining the constraint function, the relevant optimal scheduling model is constructed. The SAC algorithm in deep reinforcement learning is used to solve the model to achieve the important goal of optimal scheduling. The experimental results show that the total fuel consumption of the proposed method is small, and the proposed method has a better optimal scheduling effect of thermal power system in thermal power plants, and can effectively improve the optimal scheduling efficiency.
Well Kill Simulation of Gas Drilling When Drilling into Gas Reservoir
Authors: Gong Peibin , Zhu Huangang , Sun Jiaxiang
Published: February 2023

Aiming at the situation of encountering high-pressure gas reservoir in gas drilling, a well-kill mathematical model is established using multi-flow theory. Then the simulation of bottom hole pressure and casing pressure during well kill is demonstrated under different good kick parameters. The results show that the successful well kill only depends on a reasonable combination of initial casing pressure, kill rate and kill mud density. As the maximum initial casing pressure can be determined, the other two well-kill parameters can be changed. A combination of low kill rate and low kill mud density may lead to a failure in well kill due to the impossibility of forming an annular mud column. A reasonable combination of kill rate and kill mud density can guarantee the success of well kill, which contains two cases. One is that the formation pressure is balanced with no casing pressure after a period of well kill, and the other is the formation pressure can only be balanced with a certain casing pressure. Over-weight kill mud may fracture the formation, which can cause complicated well control risk. This simulation is instructive for the design of well kill in gas drilling.
Prediction Model of Bailing Oil Dynamic Production and Periodic Optimization
Authors: Zhu Jing , Zhang Fuxing , He Jinbao , Tang Li
Published: February 2023

As a production method of low production wells and remote oil wells, bailing oil recovery is particularly important for its reasonable working system. The dimensionless bottom hole flowing pressure is solved by establishing the seepage mechanics equation of infinite homogeneous formation, and the productivity of bailed well is predicted by using the direct relationship between bottom hole flowing pressure and unit flow rate. On this basis, a mathematical model of the net income of bailing wells is established to determine a reasonable bailing period with economic benefits as the goal, and solve the problem that the oil bailing system relies on experience and lacks theoretical guidance.