bluuebunny/crossref_metadata_2025_split huggingface dataset:
Family behavior and Dirac bands in armchair nanoribbons with 4–8 defect lines
Authors: Gillen Roland , Maultzsch Janina 
Published: April 2024

Abstract
Bottom-up synthesis from molecular precursors is a powerful route for the creation of novel synthetic carbon-based low-dimensional materials, such as planar carbon lattices. The wealth of conceivable precursor molecules introduces a significant number of degrees-of-freedom for the design of materials with defined physical properties. In this context, a priori knowledge of the electronic, vibrational and optical properties provided by modern ab initio simulation methods can act as a valuable guide for the design of novel synthetic carbon-based building blocks. Using density functional theory, we performed simulations of the electronic properties of armchair-edged graphene nanoribbons (AGNR) with a bisecting 4–8 ring defect line. We show that the electronic structures of the defective nanoribbons of increasing width can be classified into three distinct families of semiconductors, similar to the case of pristine AGNR. In contrast to the latter, we find that every third nanoribbon is a zero-gap semiconductor with Dirac-type crossing of linear bands at the Fermi energy. By employing tight-binding models including interactions up to third-nearest neighbors, we show that the family behavior, the formation of direct and indirect band gaps and of linear band crossings in the defective nanoribbons is rooted in the electronic properties of the individual nanoribbon halves on either side of the defect lines, and can be effectively through introduction of additional ‘interhalf’ coupling terms.
Vibrational properties of disordered stealthy hyperuniform 1D atomic chains
Authors: Zhuang Houlong , Chen Duyu , Liu Lei , Keeney David , Zhang Ge , Jiao Yang 
Published: April 2024

Abstract
Disorder hyperuniformity is a recently discovered exotic state of many-body systems that possess a hidden order in between that of a perfect crystal and a completely disordered system. Recently, this novel disordered state has been observed in a number of quantum materials including amorphous 2D graphene and silica, which are endowed with unexpected electronic transport properties. Here, we numerically investigate 1D atomic chain models, including perfect crystalline, disordered stealthy hyperuniform (SHU) as well as randomly perturbed atom packing configurations to obtain a quantitative understanding of how the unique SHU disorder affects the vibrational properties of these low-dimensional materials. We find that the disordered SHU chains possess lower cohesive energies compared to the randomly perturbed chains, implying their potential reliability in experiments. Our inverse partition ratio (IPR) calculations indicate that the SHU chains can support fully delocalized states just like perfect crystalline chains over a wide range of frequencies, i.e.

ω
∈
(
0
,
100
)

cm−1, suggesting superior phonon transport behaviors within these frequencies, which was traditionally considered impossible in disordered systems. Interestingly, we observe the emergence of a group of highly localized states associated with

ω
∼
200

cm−1, which is characterized by a significant peak in the IPR and a peak in phonon density of states at the corresponding frequency, and is potentially useful for decoupling electron and phonon degrees of freedom. These unique properties of disordered SHU chains have implications in the design and engineering of novel quantum materials for thermal and phononic applications.
A novel residual global context shrinkage network based fault diagnosis method for rotating machinery under noisy conditions
Authors: Tong Jinyu , Tang Shiyu , Zheng Jinde , Zhao Hongjie , Wu Yi 
Published: April 2024

Abstract
In real industrial environments, vibration signals generated during the operation of rotating machinery are typically accompanied by significant noise. Existing deep learning methods often yield unsatisfactory diagnostic results when dealing with noisy signals. To address this problem, a novel residual global context shrinkage network (RGNet) is proposed in this paper. Firstly, to fully utilize the useful information in the raw vibration signal, a multi-sensor fusion strategy based on dispersion entropy is designed as the input of the deep network. Then, the RGNet is designed, which improves the long-distance modeling capability of the deep network while suppressing noise, optimizes the network gradient and computational performance. Finally, the noise suppression ability and feature extraction ability of the RGNet are intuitively revealed through an interpretability study. The advantages of the proposed method are proved through a series of comparison experiments under noisy backgrounds.
An acoustic emission identification model for train axle fatigue cracks based on deep belief network
Authors: Lin Li , Tang Xiaowen , Zhu Xiaoxiao , Yu Xinyuan , Bi Tianlong 
Published: April 2024

Abstract
Railway axles are safety-critical components of the railroad rolling stock and the consequences of possible in-service failures can have a huge impact. Axle fatigue cracks are relatively common defects during train operation, but how to intelligently identify axle fatigue cracks in running trains is still a great challenge. In order to identify axle fatigue cracks more intelligently, the problem that needs to be solved is how to overcome the manual extraction of features by manual experience as well as shallow networks. Therefore, in this paper, an acoustic emission signal identification method based on deep belief networks (DBNs) for axle fatigue cracks is proposed. In this method, a DBN model is constructed. The axle fatigue crack acoustic emission signal data were obtained by our designed acquisition experimental setup, and these data were used to verify the accuracy of the constructed DBN network model identification. The experimental results show that the method of identification of axle fatigue cracks based on DBN, compared with the traditional fault diagnosis method, eliminates the operations of data feature extraction, feature screening, feature fusion, etc and makes complete use of all the information contained in the fault data. The method can not only identify fatigue crack signals but also has a high identification rate of fatigue cracks at different stages. In the axle fatigue crack acoustic emission identification field, it can be seen that the proposed method in this paper will be a promising approach.
Reference-free x-ray fluorescence analysis with a micrometer-sized incident beam
Authors: Hönicke Philipp , Wählisch André , Unterumsberger Rainer , Beckhoff Burkhard , Bogdanowicz Janusz , Charley Anne-Laure , Mertens Hans , Rochat Névine , Hartmann Jean-Michel , Giambacorti Narciso 
Published: April 2024

Abstract
Spatially resolved x-ray fluorescence (XRF) based analysis employing incident beam sizes in the low micrometer range (μXRF) is widely used to study lateral composition changes of various types of microstructured samples. However, up to now the quantitative analysis of such experimental datasets could only be realized employing adequate calibration or reference specimen. In this work, we extent the applicability of the so-called reference-free XRF approach to enable reference-free μXRF analysis. Here, no calibration specimen are needed in order to derive a quantitative and position sensitive composition of the sample of interest. The necessary instrumental steps to realize reference-free μXRF are explained and a validation of ref.-free μXRF against ref.-free standard XRF is performed employing laterally homogeneous samples. Finally, an application example from semiconductor research is shown, where the lateral sample features require the usage of ref.-free μXRF for quantitative analysis.
Nano-cutting mechanism of ion implantation-modified SiC: reducing subsurface damage expansion and abrasive wear
Authors: Kang Qiang , Kong Xianguang , Chang Jiantao , Fang Xudong , Kang Chengwei , Wu Chen , Li Changsheng , Maeda Ryutaro , Jiang Zhuangde 
Published: April 2024

Abstract
This study utilized ion implantation to modify the material properties of silicon carbide (SiC) to mitigate subsurface damage during SiC machining. The paper analyzed the mechanism of hydrogen ion implantation on the machining performance of SiC at the atomic scale. A molecular dynamics model of nanoscale cutting of an ion-implanted SiC workpiece using a non-rigid regular tetrakaidecahedral diamond abrasive grain was established. The study investigated the effects of ion implantation on crystal structure phase transformation, dislocation nucleation, and defect structure evolution. Results showed ion implantation modification decreased the extension depth of amorphous structures in the subsurface layer, thereby enhancing the surface and subsurface integrity of the SiC workpiece. Additionally, dislocation extension length and volume within the lattice structure were lower in the ion-implanted workpiece compared to non-implanted ones. Phase transformation, compressive pressure, and cutting stress of the lattice in the shear region per unit volume were lower in the ion-implanted workpiece than the non-implanted one. Taking the diamond abrasive grain as the research subject, the mechanism of grain wear under ion implantation was explored. Grain expansion, compression, and atomic volumetric strain wear rate were higher in the non-implanted workpiece versus implanted ones. Under shear extrusion of the SiC workpiece, dangling bonds of atoms in the diamond grain were unstable, resulting in graphitization of the diamond structure at elevated temperatures. This study established a solid theoretical and practical foundation for realizing non-destructive machining at the atomic scale, encompassing both theoretical principles and practical applications.
Magnetic tunnel junction random number generators applied to dynamically tuned probability trees driven by spin orbit torque
Authors: Maicke Andrew , Arzate Jared , Liu Samuel , Kwon Jaesuk , Smith J Darby , Aimone James B , Misra Shashank , Schuman Catherine , Cardwell Suma G , Incorvia Jean Anne C 
Published: April 2024

Abstract
Perpendicular magnetic tunnel junction (pMTJ)-based true-random number generators (RNGs) can consume orders of magnitude less energy per bit than CMOS pseudo-RNGs. Here, we numerically investigate with a macrospin Landau–Lifshitz-Gilbert equation solver the use of pMTJs driven by spin–orbit torque to directly sample numbers from arbitrary probability distributions with the help of a tunable probability tree. The tree operates by dynamically biasing sequences of pMTJ relaxation events, called ‘coinflips’, via an additional applied spin-transfer-torque current. Specifically, using a single, ideal pMTJ device we successfully draw integer samples on the interval [0, 255] from an exponential distribution based on p-value distribution analysis. In order to investigate device-to-device variations, the thermal stability of the pMTJs are varied based on manufactured device data. It is found that while repeatedly using a varied device inhibits ability to recover the probability distribution, the device variations average out when considering the entire set of devices as a ‘bucket’ to agnostically draw random numbers from. Further, it is noted that the device variations most significantly impact the highest level of the probability tree, with diminishing errors at lower levels. The devices are then used to draw both uniformly and exponentially distributed numbers for the Monte Carlo computation of a problem from particle transport, showing excellent data fit with the analytical solution. Finally, the devices are benchmarked against CMOS and memristor RNGs, showing faster bit generation and significantly lower energy use.
A piezoelectric energy harvester with parallel connection using beams of different lengths to improve output performance
Authors: Wang Liang , Su Donghao 
Published: April 2024

Abstract
The purpose of this paper is to design an energy harvester to improve output performance. The theoretical analysis of the piezoelectric energy harvester has been performed. Reducing the length of one cantilever beam, thereby changing the relative impact position, causing the amplitude of the two cantilever beams to be different, and making the waveform of two beams different. Some experiments have been tested to verify the feasibility of the device and compare the differences with Plan A. Based on the experiment, it can be concluded that the output voltage is higher at both high and low speeds. When the rotation speed is 255 r min−1, Plan B arrives at the optimum speed, and the maximum output voltage is 166.2 V, which significantly increases from 97.2 V of Plan A. The maximum output power is 0.966 W under the load resistance of 10 kΩ. The maximum voltage is 157.7 V under the load resistance of 120 kΩ. Nevertheless, the maximum voltage and maximum power of Plan A are 92.62 V and 0.52 W. Besides, the prototype has fewer materials and nearly 1.5 times the energy conversion rate compares to Plan A. It can light up 42 LEDs easily and can adapt to environmental vibration frequency changes, so it has an intensely adaptable and outstanding performance in practical applications.
Electromagnetic lensing using the Aharonov–Bohm effect
Authors: Tokoro Schreiber Makoto , Cassidy Cathal , Saidani Menour , Wolf Matthias 
Published: April 2024

Abstract
We demonstrate theoretically and experimentally an electromagnetic lensing concept using the magnetic vector potential—in a region free of classical electromagnetic fields—via the Aharonov–Bohm (AB) effect. This toroid-shaped lens with poloidal current flow allows for electromagnetic lensing which can be tuned to be convex or concave with a spherical aberration coefficient of opposite polarity to its focal length. This field-free lens combines the advantages of traditional electromagnetic and electrostatic field-based lenses and opens up additional possibilities for the optical design of charged-particle systems. More generally, these results demonstrate that the AB effect can shape charged particle wavefronts beyond simple step shifts if topologies beyond simple flux lines are considered and further supports the physical significance of the magnetic vector potential.
Interpretative 3D MHD modelling of deuterium SPI into a JET H-mode plasma
Authors: Kong M. , Nardon E. , Hoelzl M. , Bonfiglio D. , Hu D. , Lee S.-J. , Samulyak R. , Sheikh U. , Silburn S. , Artola F.J. , Boboc A. , Bodner G. , Carvalho P. , Delabie E. , Fontdecaba J.M. , Gerasimov S.N. , Hender T.C. , Jachmich S. , Kos D. , Lawson K.D. , Pamela S. , Sommariva C. , S̆tancar Z̆. , Stein-Lubrano B. , Sun H.J. , Sweeney R. , Szepesi G. ,   the JOREK Team,   JET Contributors
Published: April 2024

AbstractThe pre-thermal quench (pre-TQ) dynamics of a pure deuterium (D2) shattered pellet injection (SPI) into a3MA/7MJJET H-mode plasma is studied via 3D non-linear MHD modelling with the JOREK code. The interpretative modelling captures the overall evolution of the measured density and radiated power. The simulations also identify the importance of the drifts of ablation plasmoids towards the tokamak low field side (LFS) and the impurities in the background plasma in fragment penetration, assimilation, radiative cooling and MHD activity inD2SPI experiments. It is found that plasmoid drifts lead to an about 70% reduction of the central line-integrated density (compared to a simulation without drifts) in the JETD2SPI discharge considered. Impurities that pre-exist before the SPI as well as those from possible impurity influxes related to the SPI are shown to dominate the radiation in the considered discharge. With inputs from JOREK simulations, modelling with the Lagrangian particle-based pellet code PELOTON reproduces the deviation of the SPI fragments in the direction of the major radius as observed by the fast camera. This confirms the role of rocket effects and plasmoid drifts in the considered discharge and reinforces the validity of the JOREK modelling. The limited core density rise due to plasmoid drifts and the strong radiative cooling and MHD activity with impurities (depending on their species and concentration) could limit the effectiveness of LFSD2SPI in runaway electron avoidance and are worth considering in the design of the ITER disruption mitigation system.
Overview of the KSTAR experiments toward fusion reactor
Authors: Ko Won-Ha , Yoon S.W. , Kim W.C. , Kwak J.G. , Park K.L. , Nam Y.U. , Wang S.J. , Chung J. , Park B.H. , Park G.Y. , Lee H.H. , Han H.S. , Choi M.J. , Na Y.S. , In Y. , Lee C.Y. , Kim M. , Yun G.S. , Ghim Y.-C. , Choe W.H. , Kwon J.M. , Lee J.P. , Lee W.C. , Jeon Y.M. , Kim K. , Lee J.H. , Shin G.W. , Kim J. , Lee J. , Hahn S.H. , Lee J.W. , Kim H.S. , Bak J.G. , Lee S.G. , Lee Y.H. , Jeong J.H. , Woo M.H. , Kim J.H. , Juhn J.W. , Ko J.S. , Sung C. , Shin H.W. , Park J.M. , Kim S.K. , Park J.K. , Logan N.C. , Yang S.M. , Kolemen E. , Hu Q.M. , Shousha R. , Barr J. , Paz-Soldan C. , Park Y.S. , Sabbagh S.A. , Ida K. , Kim S. , Loarte A. , Gilson E. , Eldon D. , Nakano T. , Tala T. ,   KSTAR Team
Published: April 2024

Abstract
The Korean Superconducting Tokamak Advanced Research has been focused on exploring the key physics and engineering issues for future fusion reactors by demonstrating the long pulse operation of high beta steady-state discharge. Advanced scenarios are being developed with the goal for steady-state operation, and significant progress has been made in high ℓ
i, hybrid and high beta scenarios with β
N of 3. In the new operation scenario called fast ion regulated enhanced (FIRE), fast ions play an essential role in confinement enhancement. GK simulations show a significant reduction of the thermal energy flux when the thermal ion fraction decreases and the main ion density gradient is reversed by the fast ions in FIRE mode. Optimization of 3D magnetic field techniques, including adaptive control and real-time machine learning control algorithm, enabled long-pulse operation and high-performance ELM-suppressed discharge. Symmetric multiple shattered pellet injections (SPIs) and real-time disruption event characterization and forecasting are being performed to mitigate and avoid the disruptions associated with high-performance, long-pulse ITER-like scenarios. Finally, the near-term research plan will be addressed with the actively cooled tungsten divertor, a major upgrade of the NBI and helicon current drive heating, and transition to a full metallic wall.
Scintillating sampling ECAL technology for the LHCb ECAL Upgrade II
Authors: Picatoste E. ,   the LHCb ECAL Upgrade II R&D group
Published: April 2024

Abstract
The aim of the LHCb Upgrade II is to be able to operate at a luminosity of 1.5×1034 cm-2 s-1 to collect a data set of 300 fb-1. The required substantial modifications of the current LHCb electromagnetic calorimeter due to high radiation doses in the central region and increased particle densities are referred to as LHCb ECAL Upgrade II. A consolidation of the ECAL already during the long shutdown 3 will reduce the occupancy and mitigate the effects of substantial ageing in the central region after Run 3.

Several scintillating sampling ECAL technologies are being investigated in an ongoing R&D campaign: Spaghetti Calorimeter (SpaCal) with garnet scintillating crystals and tungsten absorber, SpaCal with scintillating plastic fibres and tungsten or lead absorber, and Shashlik with polystyrene tiles, lead absorber and fast WLS fibres.

Timing capabilities with tens of picoseconds precision for neutral electromagnetic particles and increased granularity with a denser absorber in the central region are needed for pile-up mitigation. Time resolutions of better than 20 ps at high energy were observed in test beam measurements of prototype SpaCal and Shashlik modules. Energy resolutions with sampling contributions of about 10%/√E, in line with the requirements, were observed.
A decomposition algorithm for streak camera data
Authors: Oguzhan Kaan , Ranc Lucas , Verra Livio , Caldwell Allen 
Published: April 2024

Abstract
We describe a novel reconstruction algorithm for
time-resolved images obtained using a streak camera. This algorithm
operates by decomposing a recorded image into a set of individual
photoelectron-induced signals, thereby providing a powerful method
for streak camera image reconstruction. This deconstruction allows
for a standard statistical analysis of the resulting image. We
demonstrate the effectiveness of this technique by analyzing the
temporal spacing between the emitted fs-long laser pulse and its
succeeding first, second, and third reflections within a thick glass
captured by a streak image.
Utilizing CO2 as a strategy to scale up direct air capture may face fewer short-term barriers than directly storing CO2
Authors: Brazzola Nicoletta , Moretti Christian , Sievert Katrin , Patt Anthony , Lilliestam Johan 
Published: April 2024

Abstract
Direct air capture (DAC) is increasingly recognized as a necessary puzzle piece to achieve the Paris climate targets. However, the current high cost and energy intensity of DAC act as a barrier. Short-term strategies for initial deployment, technology improvement, and cost reduction are needed to enable large-scale deployment. We assess and compare two near-term pathways leading to the same installed DAC capacity and thus yielding the same cost reductions: its combination with CO2 storage as direct air carbon capture and storage, or its deployment for CO2 utilization as direct air carbon capture and utilization e.g. for synthetic fuels, chemicals, and materials; we characterize these as Direct and Spillover pathways. Drawing on the Multi-level Perspective on Technological Transition as a heuristic, we examine both technical and immaterial factors needed to scale up DAC under the two pathways, in order to assess the pathways’ relative advantages and to identify possible short-term bottlenecks. We find neither pathway to be clearly better: the Direct pathway offers technical advantages but faces regulatory barriers that need to be resolved before deployment, while the Spillover pathway offers market and governance advantages but faces challenges related to hydrogen production and increasing resource needs as it scales up. There may be reasons for policymakers to therefore pursue both approaches in a dynamic manner. This could involve prioritizing the Spillover pathway in the short term due to possibly fewer short-term regulatory barriers and its ability to produce net-zero emission products for existing and accessible markets. Once short-term governance obstacles have been addressed, however, the Direct pathway may allow for more efficient scaling of DAC capacity and cost reductions, especially if by then the needed infrastructure and institutions are in place.