bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinetics of rapid growth and melting of Al50Ni50 alloying crystals: phase field theory versus atomistic simulations revisited
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Authors: Rozas Roberto E , Ankudinov Vladimir , Galenko Peter K 
Published: October 2022

Abstract
A revised study of the growth and melting of crystals in congruently melting Al50Ni50 alloy is carried out by molecular dynamics (MDs) and phase field (PF) methods. An embedded atom method (EAM) potential of Purja Pun and Mishin (2009 Phil. Mag. 89 3245) is used to estimate the material’s properties (density, enthalpy, and self-diffusion) of the B2 crystalline and liquid phases of the alloy. Using the same EAM potential, the melting temperature, density, and diffusion coefficient become well comparable with experimental data in contrast with previous works where other potentials were used. In the new revision of MD data, the kinetics of melting and solidification are quantitatively evaluated by the ‘crystal-liquid interface velocity–undercooling’ relationship exhibiting the well-known bell-shaped kinetic curve. The traveling wave solution of the kinetic PF model as well as the hodograph equation of the solid-liquid interface quantitatively describe the ‘velocity–undercooling’ relationship obtained in the MD simulation in the whole range of investigated temperatures for melting and growth of Al50Ni50 crystals.
An enhanced multiscale generation and depth-perceptual loss-based super-resolution network for prostate ultrasound images
Authors: Lu Xu , Wu Shaohui , Xiao Zhiwei , Huang Xiongwei 
Published: October 2022

Abstract
Computer-aided diagnosis of prostate ultrasound images is gradually being combined with deep learning to help detect and treat diseases. However, ultrasound images of the prostate have problems such as low resolution and unbalanced categories. In addition, the current image classification algorithms have difficulty with classification network performance due to insufficient data volume. To solve these problems, inspired by CycleGAN, we propose an enhanced multiscale generation and depth-perceptual loss-based super-resolution (SR) network for prostate ultrasound images (EGDL-CycleGAN). We study and improve the generative network and perceptual loss of CycleGAN. In this work we achieve multiscale feature extraction through an improved generator, and utilize full-scale skip connections between encoder and decoder to capture fine-grained details and coarse-grained semantics at full scale. This effectively improves the performance of the generative network and makes the reconstruction effect better. We also use the residual structure for deep extraction of features to obtain perceptual loss, and add this to the network loss function for training the model. This enables the model to learn the global and local differences between the real and generated images. This approach pays more attention to the edge information and spatial information of the image, and provides relevant spatial information feedback to the generator to improve the generator’s ability to perceive consistent super-resolution. The method can enhance the prostate ultrasound image dataset and provide rich images for the next step in intelligence-assisted classification and diagnosis of prostate cancer ultrasound images. The evaluation of peak signal-to-noise ratio/structural similarity and visual effects against the benchmark of our datasets illustrates that our proposed approach is effective and superior to the bicubic classic image SR reconstruction algorithm, the SRGAN perception-driven method and the CycleGAN method applied to ultrasound images. In addition, the method of using the original dataset combined with the SR reconstruction image dataset can effectively improve the accuracy of the classification network in intelligence-assisted classification diagnosis of prostate cancer ultrasound images. In EfficientNetV2 the accuracy is improved from 0.843 to 0.867 and in Swin Transformer the accuracy is improved from 0.893 to 0.917.
Real-time VUV radiation monitoring in low-pressure hydrogen plasma based on fluorescence of sodium salicylate
Authors: Han Jonggu , Park Woojin , Mauchauffé Rodolphe , Lim Keon-Hee , Lee Gwang-Ho , In Seongjin , Park Jitae , Kang Chansoo , Moon Se Youn 
Published: October 2022

Abstract
Recently, vacuum ultra-violet (VUV) radiation emitted from plasmas has been of particular interest in semiconductor device fabrication because of the effects of its high-energy photons, such as induced damage or curing on low-k materials. Due to the difficulty of implementing conventional spectroscopic methods to monitor VUV radiation with high accuracy and time resolution in current plasma processing equipment, novel monitoring methods must be investigated. Therefore, in this work, we developed a compact VUV radiation monitoring system based on a scintillator, i.e. sodium salicylate (NaSal), for real-time VUV measurements. Compared to conventional VUV spectrometers, the system shows considerable implementation potential thanks to its compact size, higher detection accuracy and high time resolution. VUV radiation emitted by continuous and pulsed hydrogen plasmas generated at low pressure was investigated using the developed system. Using various filters, we were able to compare the VUV photon intensity in different wavelength ranges. It was found that the VUV photon intensity between 115 and 250 nm was about 2.5 times higher than in the region below 115 nm due to intense Lyman-α and molecular radiation, such as Lyman and Werner bands observed in low-pressure hydrogen plasmas.
Research on main bearing life prediction of direct-drive wind turbine based on digital twin technology
Authors: Zhao Wentao , Zhang Chao , Wang Jianguo , Peyrano Oscar García , Gu Fengshou , Wang Shuai , Lv Da 
Published: October 2022

Abstract
Large and expensive mechanical equipment such as wind turbines generally has limited fault datasets from real-world operations for digital model development. This often leads to poor accuracy in implementing a model based on the life prediction. To address this data shortage issue in developing deep learning models, a remaining useful life prediction approach is proposed in this paper, which combines digital twin technology with transfer learning theory and the embedded convolutional long short-term memory (CLSTM) extended model. First, the main bearing of a direct-drive wind turbine is mapped to the digital world using digital twin technology, allowing the fault datasets of main bearings to be generated and thereby ensuring the model is trained sufficiently with a balanced dataset. The CLSTM network then performs convolutional operations on input-to-state and state-to-state transitions, thereby integrating the time dependence and time-frequency characteristics of the data. Meanwhile, transfer learning is used to transfer the trained model to the wind field for real-world fault diagnostics and the life prediction of the main bearings. Finally, the approach is applied to predict the life of the main bearings, and is also compared with other methods of similar type. The results verified that the proposed approach can effectively overcome the low data density of large equipment, greatly improving the accuracy of life prediction.
Molecular dynamics analysis of the low-temperature shock behavior of the CoCrFeMnNi high-entropy alloy
Authors: Chen Xiang , Li Shuang , Tang Xiao , Lu Sheng , Zhao Yang , Fu Tao , Peng Xianghe 
Published: October 2022

Abstract
This study presents a non-equilibrium molecular dynamics simulation of the shock compression of a [1

1
ˉ

0]-oriented CoCrFeMnNi high-entropy alloy (HEA) at 77 K. The effects of different impact velocities on the mechanical properties were investigated in detail, as well as the changes in atomic microstructure and the formation of defects and dislocations under impact loading. In addition, the role of voids in the CoCrFeMnNi HEA was investigated. The results showed that with an increase in impact velocity, the average values of the atomic velocity, temperature, and stress increase. The phenomenon of double-wave separation of the elastic and plastic waves was apparent, and when the loading velocity increased, the propagation velocities of the elastic and plastic waves also increased incrementally. The change in the atomic microstructure and generation of dislocation defects further revealed the effect of different impact velocities on the CoCrFeMnNi HEA. The degree of change in the phase structure was positively correlated with the magnitude of the impact velocity; however, the number of dislocations and defects first increased to a maximum and then decreased with the increase in impact velocity. In addition, the void structure had almost no effect on the phase change of the HEA when subjected to impact loading, whereas the effect on dislocation defects was more pronounced.
Metal to insulator transition, colossal Seebeck coefficient and large violation of Wiedemann–Franz law in nanoscale granular nickel
Authors: Sharma Vikash , Okram Gunadhor Singh , Kuo Yung-Kang 
Published: October 2022

Abstract
We report on the electrical and thermal transport properties of nickel nanoparticles with crystallite size from 23.1 ± 0.3 to 1.3 ± 0.3 nm. These nanoparticles show a systematic metal to insulator transition with the change in the conduction type from n- to p-type, colossal Seebeck coefficient of 1.87 ± 0.07 mV K−1, and ultralow thermal conductivity of 0.52 ± 0.05 W m−1 K−1 at 300 K as the crystallite size drops. The electrical resistivity analysis reveals a dramatic change in the electronic excitation spectrum indicating the opening of an energy gap, and cotunneling and Coulomb blockade of the charge carriers. Seebeck coefficient shows transport energy degradation of charge carriers as transport level moves away from the Fermi level with decrease in crystallite size. The Lorenz number rising to about four orders of magnitude in the metallic regimes with decrease in crystallite size, showing a large violation of the Wiedemann–Franz law in these compacted nickel nanoparticles. Such an observation provides the compelling confirmation for unconventional quasiparticle dynamics where the transport of charge and heat is independent of each other. Therefore, such nanoparticles provide an intriguing platform to tune the charge and heat transport, which may be useful for thermoelectrics and heat dissipation in nanocrystal array-based electronics.
An image analysis method for quantifying precision and disorder in nanofabricated photonic structures
Authors: Carfagno Henry S , García Pedro David , Doty Matthew F 
Published: October 2022

Abstract
Disorder is an essential parameter in photonic systems and devices, influencing phenomena such as the robustness of topological photonic states and the Anderson localization of modes in waveguides. We develop and demonstrate a method for both analyzing and visualizing positional, size, and shape disorder in periodic structures such as photonic crystals. This analysis method shows selectivity for disorder type and sensitivity to disorder down to less than 1%. We show that the method can be applied to more complex shapes such as those used in topological photonics. The method provides a powerful tool for process development and quality control, including analyzing the precision of E-beam lithography before patterns are transferred; quantifying the precision limits of lithography, deposition, or etch processes; and studying the intentional displacement of individual objects within otherwise periodic arrays.
Application of a simple DNA damage model developed for electrons to proton irradiation
Authors: Matsuya Yusuke , Kai Takeshi , Parisi Alessio , Yoshii Yuji , Sato Tatsuhiko 
Published: October 2022

Abstract
Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keV μm−1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.
Performance evaluation of digital breast tomosynthesis systems: comparison of current virtual clinical trial methods
Authors: Marshall N W , Bosmans H 
Published: October 2022

Abstract
Virtual clinical trials (VCT) have been developed by a number of groups to study breast imaging applications, with the focus on digital breast tomosynthesis imaging. In this review, the main components of these simulation platforms are compared, along with the validation steps, a number of practical applications and some of the limitations associated with this method. VCT platforms simulate, up to a certain level of detail, the main components of the imaging chain: the x-ray beam, system geometry including the antiscatter grid and the x-ray detector. In building VCT platforms, groups use a number of techniques, including x-ray spectrum modelling, Monte Carlo simulation for x-ray imaging and scatter estimation, ray tracing, breast phantom models and modelling of the detector. The incorporation of different anthropomorphic breast models is described, together with the lesions needed to simulate clinical studies and to study detection performance. A step by step comparison highlights the need for transparency when describing the simulation frameworks. Current simulation bottlenecks include resolution and memory constraints when generating high resolution breast phantoms, difficulties in accessing/applying relevant, vendor specific image processing and reconstruction methods, while the imaging tasks considered are generally detection tasks without search, evaluated by computational observers. A number of applications are described along with some future avenues for research.
Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data
Authors: Marshall N W , Bosmans H 
Published: October 2022

Abstract
Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.
Optimization of SiGe interface properties with ozone oxidation and a stacked HfO2/Al2O3 dielectric for a SiGe channel FinFET transistor
Authors: Chen Anlan , Li Chun , Yao Qide , Ma Xueli , Li Yongliang , Wang Wenwu 
Published: October 2022

Abstract
In this paper, the optimization of SiGe interface properties for the SiGe channel fin field effect transistor (FinFET) transistor is explored in detail. First, optimal low-temperature ozone oxidation at 300 °C for 30 min was confirmed based on Al2O3/Si0.7Ge0.3 metal-oxide-semiconductor (MOS) capacitors. This is because a higher oxidation temperature and a longer oxidation time can suppress the formation of GeO
X
in the interface layer (IL) and significantly improve the interface state density (D
it). Moreover, compared with the Al2O3 sample, the HfO2 sample can obtain a thinner capacitance equivalent oxide thickness (CET), but it is more vulnerable to deterioration of Si0.7Ge0.3 interface properties because the GeO
X
in the IL is more likely to diffuse into the HfO2 layer. To further optimize the D
it and CET of the Si0.7Ge0.3 MOS capacitor simultaneously, a stacked HfO2/Al2O3 dielectric is proposed. Compared with the HfO2 sample, its frequency dispersion characteristics and D
it have been improved significantly, as the thin Al2O3 layer prevents the diffusion of GeO
X
to the HfO2 layer and controls the growth of GeO
X
. Therefore, a high-quality Si0.7Ge0.3 interface property optimization technology is realized via the development of a low-temperature ozone oxidation (300 °C, 30 min) method combined with a stacked HfO2/Al2O3 dielectric. In addition, a Si0.7Ge0.3 FinFET utilizing this newly developed interface property optimization scheme is successfully prepared. Its excellent subthreshold swing performance indicates that good interface quality of the Si0.7Ge0.3 is obtained. The above results prove that this newly developed interface property optimization scheme is a practical technology for high-mobility SiGe FinFET.
MEMS-compatible structuring of liquid crystal network actuators using maskless photolithography
Authors: Lall Jasleen , Zappe Hans 
Published: October 2022

Abstract
We present a method to structure liquid crystal network actuators based on selectively polymerizing the network without any physical or hard masks in a process compatible with microelectromechanical system (MEMS) technology. The standard glass-cell filling technique is used to generate the actuator films; subsequently, selected areas are exposed to light and thus polymerized to structure the actuators. No further machining, such as laser cutting, is necessary. The polymerization pattern is defined by projection using a digital micromirror device-based optomechanical setup, with a resolution ranging from 1 to 2 mm. These processes are used to structure photothermally and photochemically stimulated actuators, which may thus be fabricated with high throughput and easily integrated with MEMS devices.
Equivalence and superposition of real and imaginary quasiperiodicities
Authors: Cai Xiaoming , Jiang Shao-Jian 
Published: October 2022

Abstract
We take non-Hermitian Aubry–André–Harper models and quasiperiodic Kitaev chains as examples to demonstrate the equivalence and superposition of real and imaginary quasiperiodic potentials (QPs) on inducing localization of single-particle states. We prove this equivalence by analytically computing Lyapunov exponents (or inverse of localization lengths) for systems with purely real and purely imaginary QPs. Moreover, when superposed and with the same frequency, real and imaginary QPs are coherent on inducing the localization, in a way which is determined by the relative phase between them. The localization induced by a coherent superposition can be simulated by the Hermitian model with an effective strength of QP, implying that models are in the same universality class. When their frequencies are different and relatively incommensurate, they are incoherent and their superposition leads to less correlation effects. Numerical results show that the localization happens earlier and there is an intermediate mixed phase lacking of mobility edge.
Fabrication and characterization of air-stable, highly efficient all-inorganic CsPbBr3 perovskite solar cell
Authors: Rana Naba Kumar , Samanta Pijus Kanti 
Published: October 2022

Abstract
Cesium lead bromide (CsPbBr3) Perovskite solar cell (PvSCs) is very popular and a most promising photovoltaic devices with outstanding environmental stability and low-cost fabrication method for commercial application. We have fabricated SnO2 and AZO-based n-i-p PvSCs and compared the power conversion efficiency (PCE) of both the devices. The AZO-based PvSCs exhibits higher value of PCE of 7.30%, with a fill factor (FF) of 63.13%, whereas SnO2-based PvSCs shows 6.17% efficiency with a low FF of 61.55%. Moreover, the unencapsulated device with AZO electron transporting layer (ETL) exhibited remarkable stability in ambient air and retained its 85% of efficiency after 2000 h.
Strong electroweak phase transition in t-channel simplified dark matter models
Authors: Biondini Simone , Schicho Philipp , Tenkanen Tuomas V.I. 
Published: October 2022

AbstractBeyond the Standard Model physics is required to explain both dark matter and the baryon asymmetry of the universe, the latter possibly generated during a strong first-order electroweak phase transition. While many proposed models tackle these problems independently, it is interesting to inquire whether the same model can explain both. In this context, we link state-of-the-art perturbative assessments of the phase transition thermodynamics with the extraction of the dark matter energy density. These techniques are applied to a next-to-minimal dark matter model containing an inert Majorana fermion that is coupled to Standard Model leptons via a scalar mediator, where the mediator interacts directly with the Higgs boson. For dark matter masses 180 GeV <Mχ≲ 300 GeV, we discern regions of the model parameter space that reproduce the observed dark matter energy density and allow for a first-order phase transition, while evading the most stringent collider constraints.