bluuebunny/crossref_metadata_2025 huggingface dataset:
Discharge distribution in a multi-outlet spillway with varying adverse conditions
Authors: Solheim Nils , Hedberg Mikael P. A. , Hellström Gunnar I. J. , Lia Leif , Andersson Anders G. , Andreasson Patrik , Pummer Elena
Published: February 2025

Hydropower and dam structures worldwide are facing evolving requirements due to changes in climate, better methods for flood estimates, combined with the needs of surrounding interests. Improved understanding of the hydraulic behavior of spillways, and the approach flow leading up to them, is important for evaluation of existing spillways and considering potential redesigns. There is limited research on the distribution of flow across a multiple outlet spillway, therefore a purpose built experimental setup is utilized to examine the impact of various geometrical changes on the flow distribution across a spillway with three outlets. The maximum difference measured between the different outlets were as much as 10%. While small changes to abutment and pier corners were found to reduce total discharge capacity up to 8%, with increased discharge and overflow height causing greater reduction in the capacity of the spillway. To further investigate the flow behavior leading up to the spillway outlets, ADV measurements were conducted to capture flow velocities. The measured flow cross sections indicate a stable flow field leading away from the inlet, stagnation zones and recirculation zones leading up to the spillway, with minor variations occurring for increasing inlet flow rates.
Aflatoxin B1 (AFB1) biodegradation by a lignolytic phenoloxidase of Trametes hirsuta
Authors: Söylemez Tuncay , Berger Ralf Günter , Krings Ulrich , Yamaç Mustafa
Published: February 2025

Aflatoxin B1 (AFB1) is a highly potent mycotoxin that poses a serious threat to human and animal health. This study investigated the biodegradation of AFB1 by the supernatant of submerged cultured Trametes hirsuta, with a focus on identifying and characterizing the responsible enzyme(s). The extracellular enzymes of the white-rot mushroom were extracted from the supernatant and pre-separated using anion exchange fast protein liquid chromatography (FPLC). To pinpoint the specific enzyme, the eluted protein fractions exhibiting the highest degradation activity were subjected to detailed biochemical and proteomic analyses. A second purification step, ultrafiltration, yielded an electrophoretically pure enzyme. Sequencing of tryptic peptides using a nano-LC system coupled to a qQTOF mass spectrometer identified the enzyme as a lignolytic phenoloxidase. The enzyme exhibited a molecular mass of 55.6 kDa and achieved an impressive AFB1 degradation rate of 77.9% under optimized experimental conditions. This is the first fungal lignolytic phenoloxidase capable of aflatoxin degradation without requiring hydrogen peroxide as a cofactor, highlighting its unique catalytic mechanism. It may be used in mycotoxin remediation strategies, such as treating the surfaces of contaminated fruits, vegetables, and nuts.
Advancements in global water and sanitation access (2000–2020)
Authors: Ando Hiroki , Kitajima Masaaki , Oki Taikan , Murakami Michio
Published: February 2025

Globally equitable access to safely managed drinking water and sanitation is one of the major aims of the United Nations’ Sustainable Development Goals, specifically SDG goal 6. We assessed global-scale progress toward this goal from 2000 to 2020 with access rates to improved drinking water and sanitation services that are adjusted for socioeconomic, political, and hydrological conditions. We found that the adjusted access rates in 2020 were lower than 2000, although not-adjusted access rates had increased. Access rates improved more slowly in higher-GDP countries than in lower-GDP ones during this period. These show that access rates in lower-income countries improved, but were still lower, compared with those in countries with the same social conditions in 2000. This suggests the recent progress toward this goal has not aligned well with social development, emphasizing need for reflecting national management, international cooperation, and investment in water-related infrastructures to achieve the goal by 2030.
A short-term, high-caloric diet has prolonged effects on brain insulin action in men
Authors: Kullmann Stephanie , Wagner Lore , Hauffe Robert , Kühnel Anne , Sandforth Leontine , Veit Ralf , Dannecker Corinna , Machann Jürgen , Fritsche Andreas , Stefan Nobert , Preissl Hubert , Kroemer Nils B. , Heni Martin , Kleinridders André , Birkenfeld Andreas L.
Published: February 2025

Brain insulin responsiveness is linked to long-term weight gain and unhealthy body fat distribution. Here we show that short-term overeating with calorie-rich sweet and fatty foods triggers liver fat accumulation and disrupted brain insulin action that outlasted the time-frame of its consumption in healthy weight men. Hence, brain response to insulin can adapt to short-term changes in diet before weight gain and may facilitate the development of obesity and associated diseases.
Categorizing robots by performance fitness into the tree of robots
Authors: Kirschner Robin Jeanne , Karacan Kübra , Melone Alessandro , Haddadin Sami
Published: February 2025

Robots are typically classified based on specific morphological features, like their kinematic structure. However, a complex interplay between morphology and intelligence shapes how well a robot performs processes. Just as delicate surgical procedures demand high dexterity and tactile precision, manual warehouse or construction work requires strength and endurance. These process requirements necessitate robot systems that provide a level of performance fitting the process. In this work, we introduce the tree of robots as a taxonomy to bridge the gap between morphological classification and process-based performance. It classifies robots based on their fitness to perform, for example, physical interaction processes. Using 11 industrial manipulators, we constructed the first part of the tree of robots based on a carefully deduced set of metrics reflecting fundamental robot capabilities for various industrial physical interaction processes. Through significance analysis, we identified substantial differences between the systems, grouping them via an expectation-maximization algorithm to create a fitness-based robot classification that is open for contributions and accessible.
5,5'-Biindeno[2,1-c]fluorene: importance of C5-C5' linkage for an indeno[2,1-c]fluorene dimer exhibiting open-shell ground state
Authors: Maurya Neha , Jana Palash , Sharma Himanshu , Bandyopadhyay Subhajit , Das Soumyajit
Published: February 2025

Mesityl-protected indeno[2,1-c]fluorene and its C2-C2' linked dimer 2,2'-biindeno[2,1-c]fluorene are closed-shell molecules. Herein, we report the synthesis and characterization of a mesityl-protected 5,5'-biindeno[2,1-c]fluorene displaying 26.4% diradical and 0.9% tetraradical characters. The...
Exploring the applications and carbon reduction of multi-technology-coupled membrane biofilm reactors for sustainable wastewater treatment: a review
Authors: Mei Chang , Zhang Meng , Chen YuChao , Dong Kun , Sun RuiZe , Zhang XueHong , Li HaiXiang
Published: February 2025

Membrane biofilm reactors are coupled with catalysts, electrochemistry, and anammox technology; their principles, applications, and carbon reduction efficiency are analyzed.
Formation of Hydrocarbons and Carbon Oxides in MXene Reactions with Water under Varying Oxidative Conditions
Authors: Huang Shuohan , Xiang Guanglei , Mochalin Vadym
Published: February 2025

Titanium carbide/carbonitride MXenes have garnered significant attention due to their remarkable properties, versatile solution processability, and a broad range of potential applications. However, when exposed to environment, MXenes are susceptible...
Organocatalyzed photoredox radical cyclopolymerization of methacrylate- and acrylamide-crotonate hybrid monomers
Authors: Yu Gaoyuan , Tian Yong-Le , Li Ke , Chen Dian-Feng
Published: February 2025

Visible light-driven organocatalyzed precision radical cyclopolymerization of hybrid dienes yields intriguing polymers with unique cyclic repeating units.
Heteroepitaxial Interface of Pt//CeO2 Nanoparticles for Enhanced Catalysis in Oxygen Reduction Reaction (ORR)
Authors: Shudin Hannah , Eguchi Ryuto , Ueda Shigenori , Ankit Singh , Hashimoto Ayako , Abe Hideki
Published: February 2025

Metal-oxide nanocomposites (MONs) have garnered significant interest in catalysis due to their excellent performance in various chemical reactions. A key focus of research on MONs is the heteroepitaxial metal-oxide interface,...
Enhanced electrochemical performance of aqueous Zn-ion batteries based on Na2V6O16·2H2O cathodes: insights from DFT and synchrotron X-ray analysis
Authors: So Younghee , Seo Huncheol , Lee Seung Hwan , Lee Eunseo , Lee Jinyoung , Kang Joonhee , Kim Young Yong , Kim Byung-Hyun , Mhin Sungwook
Published: February 2025

A Na2V6O16·2H2O cathode, synthesized via Na pre-intercalation using a sonochemical method, enhances Zn-ion storage by improving structural stability. The NaVO//Zn battery delivers 126 mA h g−1 and retains 91.8% of its capacity after 10 000 cycles.
Unlocking MOF A520 Synthesis: Investigating Critical Parameters
Authors: Froehly Marie , Chaplais Gérald , Nouali Habiba , Roucoules Vincent , Daou Jean
Published: February 2025

Aluminum based Metal-Organic Frameworks (MOFs) have emerged as versatile materials with applications in gas and vapor storage, catalysis, and separation. Among these, aluminum fumarate known as MOF A520 or MIL-53(Al)_Fu...
Novel hyperbranched polymers from transfer-dominated branching radical telomerisation (TBRT) of diacrylate taxogens
Authors: Mckeating Samuel , Smith Corinna , Penrhyn-Lowe Oliver , Flynn Sean , Wright Stephen , Chambon Pierre , Dwyer Andrew , Rannard Steve
Published: February 2025

The first study of Transfer-dominated Branching Radical Telomerisation using diacrylate taxogens shows elevated temperatures are required to create soluble high molecular weight branched polymers with full vinyl group consumption.
Collaborative decision‐making for UAV swarm confrontation based on reinforcement learning
Authors: Jiao Yongkang , Fu Wenxing , Cao Xinying , Su Qiangqing , Wang Yusheng , Shen Zixiang , Yu Lanlin
Published: February 2025

With the advancement of unmanned aerial vehicle (UAV) technology, research on adversarial interactions within UAV swarms has gained significant attention domestically and internationally. However, the existing decision‐making algorithms are primarily tailored to homogeneous UAV swarm adversarial scenarios, facing challenges such as complex reward function design and limited decision‐making timeliness when applied to more intricate scenarios. This article investigates the real‐time control decision‐making issues in UAV swarm adversarial interactions. First, an adversarial simulation environment for UAV swarms is constructed, which effectively unifies the environment and state representation, enhancing the response speed of our UAVs. Second, a distributed UAV swarm collaborative control algorithm based on multi‐agent reinforcement learning is proposed, and an effective sparse reward function is designed to guide UAVs in adversarial gaming, making the UAV strategies more aggressive, enhancing the adversarial intensity, and further optimizing the control strategy to meet real‐world demands better. Finally, the real‐time performance and scalability of the proposed method are validated through simulations.
Enhanced Segment Anything Model for Accurate White Blood Cell Segmentation
Authors: Zang Yu , Su Yang , Hu Jun
Published: February 2025

White blood cell image segmentation plays a vital role in the accurate analysis and diagnosis of blood‐related diseases, facilitating the identification and quantification of white blood cells (WBCs) in microscopic images. This process is essential for early disease detection, treatment monitoring, and immune response studies, ultimately supporting clinical decision‐making. In this paper, we propose an enhanced approach based on the segment anything model (SAM). First, contrast limited adaptive histogram equalisation is applied for preprocessing to enhance the features of WBCs. Then, SAM is utilised for segmentation. Experimental results demonstrate that our method achieves state‐of‐the‐art performance on cross‐domain datasets, providing accurate and reliable segmentation of WBCs.
Analysis of DOM Distribution Characteristics and Environmental Response Capacity in Different Areas of Urban Water
Authors: Li Yuanzhi
Published: February 2025

To accurately define the conditions of urban water bodies, research was conducted on the distribution characteristics and environmental responsiveness of DOM in different areas of urban water bodies. Water samples were collected from the severely polluted Zaohe River, Chanhe River, and Bahe River in Xi'an, including surface water and wastewater discharged from sewage outlets on these rivers. After processing the water samples, established measurement techniques were employed to analyze the DOM in the water samples. Taking Beijing as an example, remote sensing imagery was used to extract surface temperature and water body information within the study area, combined with land use and land cover data, to analyze the environmental pattern characteristics of urban water bodies. By selecting the summer period, during which the water bodies exhibit significant cooling effects, typical water areas were divided into surface and linear parts, and high-resolution imagery and fixed-point measured data were used to further explore the characteristics of urban water bodies and their environmental responsiveness.
The Role of Plant Charcol in the Carbon Geochemical Cycle
Authors: Sun Xiang-ping , Wang Zhuo , Zhong Guo-qian , Zhong Wook Won
Published: February 2025

The role of plant charcol is to promote healthier and more vigorous growth in plants. Therefore, the carbon cycle is mainly manifested in green plants which absorbing carbon dioxide from the air, which converting it into glucose through photosynthesis, at the same time, releasing oxygen in the biosphere. However, artificial carbon fixation is the direct or indirect artificial removal of atmospheric carbon dioxide through spatiotemporal scale conversion in the study. This article reviews the flow patterns and mechanisms of plant-derived carbon in the carbon cycle. Which attempting to explain carbon moves from one reservoir to another through a variety of mechanisms in the carbon cycle. Which is expected to provide reference significance for the research on the biological cycle process of carbon and the carbon neutralization of carbon peak in the study.
Oxidation kinetics and crystal structure of high-titanium slag containing sodium salt
Authors: Huang Qingqing , Lv Xiaodong , Lv Wei , Huang Run , Lv Xuewei
Published: February 2025

A novel technology was suggested to obtain the high-quality upgraded titanium raw materials for chlorination process through semi-molten states reduction with sodium salt and magnetic separation. The oxidation behavior and crystal structure of the obtained high-titanium slag containing sodium salt were studied. The Me3O5 solid solution is a uniform solid solution formed by doping Fe2+, Mg2+, and Mn2+ in the Ti ion occupancy sites based on the Ti3O5 component. Doping of these impurities cause a decrease in lattice volume, which induces the lattice to distort. As the oxidation progresses, the Me3O5 solid solution was oxidized to Anatase, and impurity elements such as Fe were doped into the Ti ion vacancies in Na0.24TiO2 to form sodium-titanium-iron oxide. Anatase was completely transformed into Rutile when the oxidation temperature increased to 900 °C, untransformed Anatase reacted with the sodium-titanium-iron oxide to form sodium-titanium oxide. At 550 °C, 600 °C, and 650 °C, the reaction was controlled by chemical reaction and gas diffusion, the apparent activation energy was 231.48 kJ/mol kJ/mol. At 650 °C, 700 °C, 800 °C, and 900 °C, the reaction is controlled by gas diffusion, the apparent activation energy was 6.52 kJ/mol.
Helios HSK: Maximalversorger für Hessen
Authors: Engberg Anna
Published: February 2025

300 Millionen Euro kostete der Neubau der Helios HSK Wiesbaden. Acht Jahre lang wurde gebaut. Mit einem Festakt feierte die „Klinik der kurzen Wege“ nun ihre Fertigstellung. Architektonisch wurde der Fokus auf die Kompetenzfelder gelegt.
Krankenhausreform: Gibt es bald keine Kinderchirurgie mehr?
Authors: Eilers Susann
Published: February 2025

In Berlin schließt eine Klinik die Kinderchirurgie und nennt als Grund die Krankenhausreform. Werden bald weitere folgen? Ein Gespräch mit der DGKJCH-Präsidentin PD Dr. Barbara Ludwikowski über Warnungen und Lösungen.
Pflichtaufgabe: Elektronische Rechnung – Zeit zum Handeln
Authors: Lang Michael
Published: February 2025

Unternehmen müssen für innerdeutsche Geschäfte ab 2025 die E-Rechnung verwenden. Die Übergangsfristen sind großzügig bemessen. Krankenhäuser, die noch nicht auf die neuen Prozesse umgestellt haben, sollten den Aufwand nicht unterschätzen.
Estimation of channel capacity in CAT6 cable with circular waveguide modeling for future THz communication systems
Authors: Ahmed Arslan , Ishak Nurul Syafeeqa , Seman Fauziahanim Che , Yee See Khee , Ahmed Sajjad
Published: February 2025

Millimeter-wave and terahertz (THz) frequency bands are being explored in wired and wireless communication systems due to ongoing demands for increased data rates. Recently, it has been proposed that twisted-pair cables, already part of existing infrastructure, could be utilized for terabit-per-second data transmission by exploiting wireless THz radiation between the copper wires. THz radiation can be wirelessly transferred through the dielectric gap and the air gap in between the copper wires. The air gap and the dielectric material between the copper wires in a CAT6 (Category 6) cable can be considered a circular hollow-core waveguide, providing a suitable medium for the propagation of THz waves. Therefore, this work aims to estimate the data rate per distance by experimentally analyzing the copper circular waveguide. Furthermore, the impact of a waveguide radius is also examined. Waveguide propagation characteristics were experimentally analyzed using THz time-domain spectroscopy as well as on a simulation basis using CST (Computer Simulation Technology) Microwave Studio 2022. It was found that the radius of the waveguide has a significant effect on the transmission characteristics of the waveguide and the channel capacity for a longer range. The proposed waveguides achieved a maximum data rate in Tbps (terabits per second) for a few meters depending upon the diameter of the waveguide. This study investigates the propagation of THz waves through narrower spaces and explores the initial steps toward realizing the concept of a TDSL (Terabit Digital Subscriber Line) and future high-frequency communication systems.
Optimization of time modulated array antennas based on improved gray wolf optimizer
Authors: Zhu TianNing , Liu Yan , Li JianHui , Zhao WanRu
Published: February 2025

With the widespread application of intelligent optimization algorithms in engineering and scientific fields, the need for their improvement and optimization is increasingly evident. This paper proposes an Improved Gray Wolf Optimization (IGWO) algorithm based on the Gray Wolf Optimization (GWO) method, aiming to enhance global search capability and convergence speed. The proposed IGWO algorithm integrates goodset initialization and the golden sine strategy to enhance global search efficiency and improve local search accuracy. The algorithm is specifically applied to the temporal modulation optimization of antenna arrays, where the switching durations of array elements are modulated to optimize the synthesis of the radiation pattern. The core goal of temporal modulation is to adjust the switching times of individual elements to alter the array’s radiation pattern, achieving effects such as sidelobe suppression, main beam optimization, and reduction of harmonic distortion. Experimental validation using four benchmark functions demonstrates that the IGWO algorithm significantly outperforms traditional algorithms, including the seagull optimization algorithm, hunger games search optimization algorithm, seahorse optimizer, and GWO algorithm, across all test cases. In addition, IGWO is applied to optimize three time-modulation models, particularly those that optimize both connection durations and inter-element spacing simultaneously. Despite higher second harmonic distortion than the differential evolution with wavelet mutation algorithm in some cases, IGWO consistently excels in minimizing fundamental sidelobes, first harmonics, and second harmonics. Experimental results validate the algorithm’s fast convergence and high optimization accuracy in optimizing the radiation pattern of antenna arrays, showcasing its effectiveness and practicality in addressing electromagnetic problems.
On the build-up of effective hyperuniformity from large globular colloidal aggregates
Authors: Díaz-Pozuelo Antonio , González-Salgado Diego , Lomba Enrique
Published: February 2025

A simple three-dimensional model of a fluid whose constituent particles interact via a short range attractive and long range repulsive potential is used to model the aggregation into large spherical-like clusters made up of hundreds of particles. The model can be thought of as a straightforward rendition of colloid flocculation into large spherical aggregates. We illustrate how temperature and particle density influence the cluster size distribution and affect inter- and intra-cluster dynamics. The system is shown to exhibit two well separated length and time scales, which can be tuned by the balance between repulsive and attractive forces. Interestingly, cluster aggregates at moderate/low temperatures approach a cluster glassy phase, whereas cluster particles retain a local liquid-like structure. These states present a strong suppression of density fluctuations for a significant range of relatively large wavelengths, meeting the criterion of effective disordered hyperuniform materials as far as the intercluster structure is concerned.
Large-scale sparse wave function circuit simulator for applications with the variational quantum eigensolver
Authors: Mullinax J. Wayne , Tubman Norm M.
Published: February 2025

The standard paradigm for state preparation on quantum computers for the simulation of physical systems in the near term has been widely explored with different algorithmic methods. One such approach is the optimization of parameterized circuits, but this becomes increasingly challenging with circuit size. As a consequence, the utility of large-scale circuit optimization is relatively unknown. In this work we demonstrate that purely classical resources can be used to optimize quantum circuits in an approximate but robust manner such that we can bridge the resources that we have from high performance computing and see a direct transition to quantum advantage. We show this through the sparse wave function circuit solvers, which we detail here, and demonstrate a region of efficient classic simulation. With such tools, we can avoid the many problems that plague circuit optimization for circuits with hundreds of qubits using only practical and reasonable classical computing resources. These tools allow us to probe the true benefit of variational optimization approaches on quantum computers, thus opening the window to what can be expected with near term hardware for physical systems. We demonstrate this with a unitary coupled cluster ansatz on various molecules up to 64 qubits with tens of thousands of variational parameters.
Computational fluid dynamics−discrete element method simulation and experimental study of particle transport mechanism in a centrifugal pump
Authors: Zhao Zhenjiang , Bai Ling , Su Xianghui , Chen Jie , Qu Bing , Zhou Ling
Published: February 2025

Pumps are one of the most important equipment in deep-sea mining system, which transport particles continuously from the seafloor. In this paper, the computational fluid dynamics−discrete element method (CFD−DEM) numerical simulation was used to analyze the effect of particle volume fraction (PVF) on the particle transport mechanism in the pump. The reliability of the CFD−DEM numerical simulation was verified by high-speed photography experiments. The results show that the particles mainly move along the blade pressure surface (BPS) in the impeller, and the particles can suppress the formation of low-velocity vortices on the BPS. The translational velocity of the particles is less affected by the PVF, but has a significant effect on the rotational velocity. The flow pattern of particles inside the volute is categorized into wake flow, cutting flow, and near wall flow. With the increase in PVF, the particles are subjected to pressure gradient force, drag force, and virtual mass force in the pump gradually increase, but the lift force on the particles gradually decreases. The tangential force and normal force between particles increased with increasing PVF, and the increase in PVF from 2% to 10% was 462.55% and 148.17%, respectively. The collision frequency per unit time of particles with volute is the largest, but the collision frequency per unit time and per unit area is the largest for impeller. The most significant impact work of particles with volute and particles with blades is 371.08% and 505.66% when PVF increases from 2% to 10%. This study can provide theoretical guidance for the optimal design of solid−liquid two-phase pumps.
Acoustic monitoring and structural damage evaluation of tensile fracture in various materials using optical fiber sensing
Authors: Zhou Xin , Liu Xiaofei , Wang Xiaoran , Zhang Siqing , Zhang Huajie , Gu Zhoujie , Zhang Yuqi , Wei Xinyu
Published: February 2025

Acoustic emission (AE) technology is a crucial approach for ensuring the safe operation and maintenance of underground spaces. Traditional mechanical and piezoelectric AE sensors often fail to meet the monitoring requirements of complex underground environments. In this paper, a novel AE monitoring system based on a Michelson interferometer is designed and applied to monitor the tensile fracture processes of common materials (coal, concrete, quartzite, and granite) in various underground engineering projects. Signal noise reduction and feature parameter extraction of the waveform data collected by the optical fiber AE sensor are performed. The time series, frequency domain characteristics, and crack fracture modes of the optical fiber AE signals were analyzed, and the precursor characteristics of tensile fractures were extracted. The results indicate that the optical fiber AE system possesses high sensitivity, a wide frequency band response, and a large dynamic range, enabling it to effectively identify AE waveform characteristics and primary frequency differences generated in various rock fracture experiments. The AE count and energy evolution patterns are in good agreement with the material stress curves, effectively quantifying the material damage evolution processes. The proportional distribution of tensile and shear cracks in different materials was successfully classified using fiber AE waveforms. Based on the changing trends of the b-value, variance, and autocorrelation coefficient, a failure early warning mechanism was constructed, categorizing failure early warnings into three time levels: trend early warning, initial early warning, and critical early warning. This study provides a new and effective monitoring method for the safety development of deep engineering.
Continuous bending fatigue test of cantilever hinge for digital micromirror devices
Authors: Tong Xinlei , Xu Linyan
Published: February 2025

This study investigates the fatigue life of cantilever-style hinges in digital micromirror devices (DMD), which are critical for their optical switching function. The hinges, which facilitate the rotation of reflective mirrors, are subjected to significant mechanical stress due to repetitive flexing, posing a risk of device failure. Prior to the main continuous bending fatigue test, a preliminary resonance-based fatigue experiment was conducted using microscopic laser Doppler vibrometry. The amplitude-frequency response of the cantilever-hinged micromirrors was measured, identifying a resonant frequency through Gaussian curve fitting. Operating at this resonant frequency, the micromirrors achieved stable performance more than 2×10¹⁰ oscillation cycles, with frequency stability throughout, affirming the reliability of the hinge structure under low-stress, high-cycle fatigue conditions. To further assess fatigue resistance, atomic force microscopy (AFM) was subsequently employed to conduct continuous bending fatigue tests, in which cyclic stress loading was applied to induce continuous bending in the cantilever hinges. Force-displacement curves obtained during the loading process were analyzed to determine the deflection and spring constants of the hinges at different stages of bending. Experimental results reveal that after 5×10⁵ continuous bending cycles, plastic deformation occurred in the hinges along the bending axis, with the end morphology of the hinge exhibiting a significant residual plastic deformation of 417.18 nm compared to its initial state. This research provides valuable insights into the high-stress, low-cycle fatigue behavior of nanoscale devices, contributing to the understanding and improvement of DMD reliability.
Antiferromagnetic Skyrmion based Energy-Efficient Leaky Integrate and Fire Neuron Device
Authors: Bindal Namita , Rajib Md Mahadi , Raj Ravish Kumar , Atulasimha Jayasimha , Kaushik Brajesh Kumar
Published: February 2025

The development of energy-efficient neuromorphic hardware using spintronic devices based on antiferromagnetic (AFM) skyrmion motion on nanotracks has gained considerable interest. Owing to their properties such as robustness against external magnetic fields, negligible stray fields, and zero net topological charge, AFM skyrmions follow straight trajectories that prevent their annihilation at nanoscale racetrack edges. This makes the AFM skyrmions a more favorable candidate over the ferromagnetic (FM) skyrmions for future spintronic applications. This work proposes an AFM skyrmion-based neuron device exhibiting the leaky-integrate-fire (LIF) functionality by exploiting either a thermal gradient or alternatively a perpendicular magnetic anisotropy (PMA) gradient in the nanotrack for leaky behavior by moving the skyrmion in the hotter or lower PMA region, respectively to minimize the system energy. Furthermore, it is shown that the AFM skyrmion couples efficiently to the soft FM layer of a magnetic tunnel junction (MTJ) enabling efficient read-out of the skyrmion. The maximum change of 9.2% in tunnel magnetoresistance (TMR) is estimated while detecting the AFM skyrmion. Moreover, the proposed neuron device has an energy dissipation of 4.32 fJ per LIF operation thus, paving the path for developing energy-efficient devices in AFM spintronics for neuromorphic computing.
High-Yield Synthesis of FeNC as Support of PtFe Nanoparticles for the Oxygen Reduction Reaction by a Green Ball Milling Method
Authors: Jin Huihui , Jiang Nannan , Chen Yujia , Feng Zhijie , Cheng Haoying , Guan Lunhui
Published: February 2025

Enhancing catalytic activity, durability and reducing costs are major challenges in commercialization of proton exchange membrane fuel cells (PEMFCs). Non-precious metal catalysts face durability challenges when applied to PEMFCs, while platinum (Pt)-based catalysts are hampered by their high costs and weak interactions with carbon supports, limiting their application in PEMFCs. Combining Pt-based catalysts with iron-nitrogen-carbon (FeNC) supports can improve the oxygen reduction reaction (ORR) performance. However, traditional preparation methods for FeNC supports, such as liquid-phase and hydrothermal synthesis, are cumbersome and have low yield. Here, we introduce a simple ball-milling method to synthesize FeNC with high yield that achieves a high-surface-area and uniform dispersion of Fe atoms. The FeNC support anchors PtFe nanoparticles at FeNₓ sites. This enhances support-alloy interactions and suppresses particle aggregation. The obtained catalyst denoted as PtFe/B-FeNC exhibits an exceptional mass activity of 2.57 A mgPt-1 at 0.9 V, representing a 12.2-fold increase compared to the commercial Pt/C. There is only 30 mV degradation for the catalyst after 120k cycles, indicating outstanding stability. This research paves the way for the green synthesis of PtFe/B-FeNC with high yield, facilitating the development of commercial materials for other electrochemical devices.
A review of ultra-wide-bandgap semiconductor radiation detector for high-energy particles and photons
Authors: Cheng Wenzheng , Zhao Feiyang , Zhang Tianyi , He Yongjie , Zhu Hao
Published: February 2025

Radiation detectors have gained significant attention due to their extensive applications in high-energy physics, medical diagnostics, aerospace, and nuclear radiation protection. Advances in relevant technologies have made the drawbacks of traditional semiconductor detectors, including high leakage currents and instability, increasingly apparent. Ga₂O₃, diamond, and BN represent a new generation of semiconductor materials following GaN and SiC, offering wide bandgaps of around 5 eV. These ultra-wide bandgap (UWBG) semiconductors demonstrate excellent properties, including ultra-low dark current, high breakdown fields, and superior radiation tolerance, underscoring their promising potential in radiation detection. In this review, we first discuss the materials and electrical properties of Ga₂O₃, diamond, and BN, along with the general performance metrics relevant to radiation detectors. Subsequently, the review provides a comprehensive overview of the research progress in X-ray detection, charged particle detection (e.g., α particles and carbon ions), as well as fast neutron and thermal neutron detection, focusing on aspects such as chip fabrication processes, device architectures, and testing results for radiation detectors based on these three materials.
The experiment that does not work: a discussion about the glass electrification in history and in physics textbooks
Authors: Silva Daniel dos Anjos , Rinaudo Marta , Leone Matteo
Published: February 2025

Since the beginnings of electricity research in the late XVI century, it was discovered that rubbing a glass object with a suitable substance causes this object to attract light bodies that are nearby. Over time, it was understood that glass is electrified by friction and the small bodies are electrified by induction at a distance. This simple experiment was later incorporated into the first electrostatic machines and soon became one of the classic electrostatic experiments in physics textbooks. In this article, we show that there may be more to this historical demonstration experiment than meets the eye, and that repeating this experiment in a school laboratory could be a terribly complicated affair.
Numerical Investigation on the Interaction between Droplets and Vacuum Arc Plasma Considering Ablation Cloud
Authors: Yang Ze , Lu wuxin , Cai Dongsheng , Huang Qi , Xing Yankai , Wang Lijun
Published: February 2025

Droplets in vacuum arc can have significant influence on the plasma characteristics and be harmful to devices such as vacuum ion sources and vacuum interrupters. Especially for the droplets with a diameter of the order of magnitude of 100 μm, the plasma parameters can be significantly affected by the ablation cloud. However, this physical mechanism is still unclear due to the lack of self-consistent theoretical research. This study established a self-consistent model to simulate the interaction between droplets and vacuum arc plasma. Dynamic meshing is used to study droplet movement. The simulation results revealed that the ablation cloud of the droplet with a diameter of the order of magnitude of 100 μm can considerably affect vacuum arc parameters. An increase in the droplet temperature increases the droplet vapor density, which increases friction between the ablation cloud and the plasma from the cathode side. Therefore, the deceleration and temperature rise of the droplet decrease. With the increase of the initial droplet diameter, the ablation cloud area increases, which decreases the electron temperature. However, the droplet temperature and droplet velocity are not proportional to the droplet diameter, which indicates the critical role of ablation cloud.
An image encryption algorithm based on a novel 4D hyperchaotic system and improved Knight’s Tour scrambling algorithm
Authors: Deng Xuan , Chen Zhong , Long Bofeng , Liu Tongzhe , Wu Ximei , Zheng Zhiwen , Zou Shuanglong , Cao Can
Published: February 2025

In this paper, we propose an advanced image encryption algorithm that integrates a novel 4D hyperchaotic system and an improved Knight’s Tour algorithm for enhanced security. The 4D hyperchaotic system, characterized by its complex dynamics and multiple positive Lyapunov exponents, generates pseudo-random sequences with high sensitivity to initial conditions. These sequences are utilized in both pixel-level scrambling and bit-level diffusion processes, ensuring robust encryption. The Knight’s Tour, a classical pathfinding algorithm, is enhanced through chaotic sequence-based randomization, improving path randomness and addressing traditional limitations like deadlock issues. Additionally, a nonlinear diffusion process, inspired by the Josephus ring algorithm, further strengthens the encryption scheme by introducing dynamic scrambling of pixel values. Security analysis and experimental results demonstrate that the proposed algorithm offers a large key space, excellent resistance to cryptanalysis, and robustness against various attacks such as noise and cropping. Especially in image encryption, resistance to differential attacks is a crucial performance metric, typically evaluated using NPCR and UACI. The expected values are NPCRE = 99.6094% and UACIE = 33.4635%. The NPCR and UACI values obtained from the experimental images encrypted by the proposed algorithm are close to these expected values. This work highlights the potential of integrating hyperchaotic systems in image encryption for applications requiring high levels of security, such as military communications, cloud storage, and digital healthcare systems.
Resonant tunneling diode cellular neural network with memristor coupling and its application in police forensic digital image protection
Authors: Yu Fei , Su Dan , He Shaoqi , Wu Yiya , Zhang Shankou , Yin Huige
Published: February 2025

Due to their biological interpretability, memristors are widely used to simulate synapses between artificial neural networks. As a type of neural network whose dynamic behavior can be explained, the coupling of resonant tunneling diode-based cellular neural network (RTD-CNN) with memristors has rarely been reported in the literature. Therefore, this paper designs a coupled RTD-CNN model with memristors (RTD-MCNN), investigating and analyzing the dynamic behavior of the RTD-MCNN. Based on this model, a simple encryption scheme for the protection of digital images in police forensic applications is proposed. The results show that the RTD-MCNN can have two positive Lyapunov exponents, and its output is influenced by initial values, exhibiting multistability. Furthermore, a set of amplitudes in its output sequence is affected by the internal parameters of the memristor, leading to nonlinear variations. Undoubtedly, the rich dynamic behaviors described above make the RTD-MCNN highly suitable for chaos-based encryption scheme design in the field of privacy protection. Encryption tests and security analysis validate the effectiveness of this scheme.
A Novel Non-autonomous Hyperchaotic Map Based on Discrete Memristor Parallel Connection
Authors: Wu Weiping , Wang Mengjiao , Yang Qigui
Published: February 2025

Since the method of discretizing memristors was proposed, discrete memristors (DMs) have become a very important topic in recent years. However, there has been little research on non-autonomous discrete memristors (NDMs) and their applications. Therefore, in this paper, a new NDM is constructed, and a non-autonomous hyperchaotic map is proposed by connecting this non-autonomous memristor in parallel with an autonomous memristor. This map exhibits complex dynamical behaviors, including infinitely many fixed points, initial-boosted attractors, initial-boosted bifurcations, and the size of the attractors being controlled by the initial value. In addition, a simple pseudo-random number generator (PRNG) was designed using the non-autonomous hyperchaotic map, and the pseudo-random numbers (PRNs) generated by it were tested using the National Institute of Standards and Technology (NIST) SP800-22 test suite. Finally, the non-autonomous hyperchaotic map is implemented on the STM32 hardware experimental platform.
Analyzing students’ drawings of the greenhouse effect: common features associated to the understanding of the phenomenon
Authors: Fiorello Camilla , Di Mauro Marco , Malgieri Massimiliano , Rosi Tommaso , Toffaletti Stefano , Onorato Pasquale , Oss Stefano
Published: February 2025

This paper studies the use of students’ drawings to investigate their conceptualizations of the physical mechanisms underlying the greenhouse effect at various levels of education. As a method of investigation, grids were created to investigate key elements of students’ drawings to understand their mental models. The results show a lack of clear distinction between atmosphere and greenhouse gases in a significant portion of the drawings, highlighting common challenges in conceptualization. It is also noted that students’ representations are influenced by external sources, suggesting that the analysis should be extended to textbooks and online content. This study demonstrates, therefore, how students’ drawings can be used as qualitative tools to explore their mental models of greenhouse effect.
Teaching physics through astronomy in secondary school: the Asiago Teachers’ Network on Astrophysics
Authors: Carli Marta , Mattia Leonardi Allesio , Ciroi Stefano , Pantano Ornella
Published: February 2025

We present the development and outcomes of the ATENA – Asiago Teachers’ Network on Astrophysics project. The initiative encompassed a professional development program and learning community for physics teachers, grounded in authentic collaboration and action research. The group’s collective inquiry centred on the integration of Astronomy into the secondary school curriculum, with the goal of fostering a comprehensive understanding of the physics of the Universe. Four physics topics spanning various grades were selected, and teaching-learning sequences informed by Physics and Astronomy Education Research were collaboratively developed by participants. Here, we present the development of the professional development program and highlight the main elements of three out of the four teaching-learning sequences. These results aim to support physics educators in incorporating astronomy into their physics teaching.
Awakening a sense of belonging to the professional community among pre-service physics teachers
Authors: Haverlíková Viera , Velmovská Klára
Published: February 2025

The shortage of physics teachers is nowadays reality in many countries. It leads to the need for changes in pre-service teacher education. To support professional identity and building a professional community, a new experiential camp is offered to pre-service teachers. The contribution presents initial research focused on identifying students’ expectations, relevance of content and applied methods, as well as on satisfaction of participants. Building a sense of belonging to the professional community is a long-term process, nevertheless first effect was observed.
Fostering pre-service physics teachers’ diagnostic skills and readiness through video vignettes and micro-teaching sessions: An exploratory single-case study
Authors: Krumphals Ingrid , Sebastian Feser Markus
Published: February 2025

A primary duty for physics teachers is to provide students with opportunities to engage in subject-specific learning processes. Such processes are always accompanied by students’ (mis)conceptions. Consequently, diagnosing students’ conceptions is a daily, essential, and challenging task for physics teachers. Prospective physics teachers should, therefore, receive appropriate preparation regarding this task during their university-based teacher education. To meet this requirement, we developed a course for Austrian pre-service physics teachers that incorporates the usage of video vignettes and micro-teaching sessions as learning arrangements to enhance participants’ diagnostic skills. Within the present study, we followed a single case study design to explore if and to which extent the self-confidence in diagnosing students’ conceptions of pre-service physics teachers who participated in this course changed over time. Our data analysis revealed mixed findings, as our participants showed increases, decreases, and U-shaped change-patterns regarding their self-confidence in diagnosing students’ conceptions. These findings indicate that participating in our developed course may have highly diverging effects on different pre-service physics teachers.
Research on the Influencing Factors of Carbon Emission in Shaanxi Province Based on the STIRPAT Model
Authors: Wu Mengying , Hou Ke , Ma Wenqing
Published: February 2025

To proactively address the growing environmental challenge of global warming, China has set an ambitious goal of achieving a carbon peak by 2030. As a significant contributor to China’s energy output, the carbon emissions produced in Shaanxi Province are of paramount importance in achieving the country’s overarching objective. By examining the factors that contribute to carbon emissions in Shaanxi Province, providing a scientific foundation for the development of low-carbon economic growth strategies is provided in this paper. Previously, hypothesis analysis based on linear relationships was employed in environmental impact assessment, which has been identified as having shortcomings, including issues with multiple covariance and insufficient model interpretation. A comparison is made between the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model and existing methods. The STIRPAT model offers greater flexibility, scalability, and the capacity to handle nonlinear relationships. When combined with ridge regression, it can also address the issue of multicollinearity and enhance the stability and reliability of the model. The STIRPAT model is particularly well-suited to the study of carbon emission influencing factors in Shaanxi Province, as it allows for the incorporation of several key factors, including population, affluence, and technology. The results of the empirical analysis show that GDP (Gross Domestic Product), urbanization level, population size, industrial structure and technological progress are the main factors affecting carbon emissions in Shaanxi Province, and it is also proved that the model has a very high accuracy, with an R2 value of 0.961, and can accurately fit the carbon emissions in Shaanxi Province. Among them, technological progress is the most crucial factor affecting carbon emissions in Shaanxi Province, and every one percent increase in the level of technological progress reduces carbon emissions by 0.268 per cent while other factors remain unchanged, so the rapid development of renewable energy technologies, such as solar energy, wind energy and hydropower, and the application of new low-carbon materials, such as bio-based materials and biodegradable polymer materials, should be actively promoted.