bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of laser polarization on the laser-induced damage threshold: Comparison with photoionization theory
Authors: Nuter R. , Karimbana Kandy A. , Gallais L. , Grosjean S. , Lamaignère L. , Wagner F. , Natoli J.-Y.
Published: January 2025

The influence of laser polarization on the laser-induced damage threshold of fused silica is presented. Measurements were performed using femtosecond and nanosecond laser pulse durations. The impact of laser polarization on the laser damage varies with laser wavelength. While no difference in UV laser damage was observed between linear and circular polarizations, circular polarization improved the damage resistance of fused silica to infrared and visible laser radiation in comparison with linear polarization. By measuring the femtosecond laser damage of a SiO2 thin film deposited onto a substrate, we show that the ratio between the bandgap of the sample and the photon energy causes the polarization dependent laser damage to change. These experimental findings are explained by considering the photoionization theory for solids.
Phase boundaries promote chemical reactions through localized fluxes
Authors: Shelest Alexandra , Le Roy Hugo , Busiello Daniel M. , De Los Rios Paolo
Published: January 2025

One of the hypothesized functions of biomolecular condensates is to act as chemical reactors, where chemical reactions can be modulated, i.e., accelerated or slowed down, while substrate molecules enter and products exit from the condensate. Similarly, the components themselves that take part in the architectural integrity of condensates might be modified by active (energy consuming, non-equilibrium) processes, e.g., by ATPase chaperones or by kinases and phosphatases. In this work, we study how the presence of spatial inhomogeneities, such as in the case of liquid–liquid phase separation, affects active chemical reactions and results in the presence of directional flows of matter, which are one of the hallmarks of non-equilibrium processes. We establish the minimal conditions for the existence of such spatial currents, and we furthermore find that these fluxes are maximal at the condensate interface. These results propose that some condensates might be most efficient as chemical factories due to their interfaces rather than their volumes and could suggest a possible biological reason for the observed abundance of small non-fusing condensates inside the cell, thus maximizing their surface and the associated fluxes.
PyLRO: A Python calculator for analyzing long-range structural order
Authors: Parrish Kevin , Hu Qingyang , Zhu Qiang
Published: January 2025

We present PyLRO, an open-source Python calculator designed to detect, quantify, and display long-range order in periodic structures. The program’s design methodology, workflow, and approach to order quantification are described and demonstrated using a simple toy model. Additionally, we apply PyLRO to a series of metastable AlPO4 structural intermediates from a prior high-pressure study, demonstrating how to compute and visualize structural order in all directions on a Miller sphere. We further highlight the program’s capabilities through a high-throughput analysis of structural patterns in the pressure-induced amorphization of AlPO4, revealing atomistic insights into specific energy regions of massive amorphous structures. These results suggest that PyLRO can be a valuable tool for investigating crystal–amorphous transition in materials research.
Construction and validation of a model for asphalt foaming behavior
Authors: Cheng Haiying , Wu Wenxia , Li Nanxi , Wang Xuebin , Danilov Roman Gennadievich
Published: January 2025

Asphalt and water produce foamed asphalt through contact collision, turbulent mixing, heat and mass transfer. In this process, the viscosity change of asphalt affects the flow characteristics and heat transfer of the fluid, and the gas content in foamed asphalt is determined by the transformation rate of water from liquid state to gas state. The standard volume of fluid (VOF) model can capture the flow characteristics of phase interfaces and interactions between phases in asphalt foaming behavior but cannot characterize the viscosity changes and water state changes of asphalt. This article introduced the functions of asphalt viscosity change and water state change in the standard VOF model. Furthermore, a control model for asphalt foaming behavior was constructed. This model, the standard VOF model, and the relevant data from the asphalt foaming test were compared. The results show that the numerical simulation results of the two models are consistent with the change trend of the asphalt foaming test results in terms of foaming cavity pressure. The root mean square (RMS) error of pressure values between the standard VOF model and asphalt foaming test results is 2.2%. The RMS error between the asphalt foaming behavior model constructed in this article and the pressure values obtained from asphalt foaming tests is 1.3%. This further validates the accuracy of the asphalt foaming model constructed in this article.
Further assessments of a “return to equilibrium” anisotropy model for non-equilibrium Reynolds stress closures
Authors: Brereton G. J.
Published: January 2025

The “return to equilibrium” closure to the Reynolds-averaged Navier–Stokes equations is a model for the Reynolds stress anisotropy bij, proposed to enable more accurate predictions of flows with temporal and spatial unsteadiness. It is based on the premise that the response of turbulence to imposed rates of fluid deformation can be bounded by the extremes of equilibrium behavior when dbij/dt=0 and rapid distortion behavior when |dbij/dt|≫0, with a model bij transport equation to blend the response between these extremes. It was shown to describe quite accurately the behavior of the primary Reynolds stresses in homogeneous turbulent flows undergoing time-dependent shear and plane strains [G. J. Brereton, Phys. Fluids 36, 035121 (2024)]. In this paper, the model bij transport equation is derived for both primary and secondary Reynolds stresses, for homogeneous turbulence in any two-dimensional, time-dependent mean flow, in a stationary or rotating reference frame. Model predictions for the Reynolds stresses were in good agreement with simulation data for homogeneous turbulence undergoing a step change in shear in a reference frame rotating at different rates, and oscillatory shear in an inertial frame.
Numerical analysis of energy loss in electric submersible pump under stall conditions based on entropy production theory
Authors: Gao Yang , Han Yong , Wang Yuqiang , Jia Deli , Yang Qinghai , Zhao Xiaojie , Liu He , Zhou Ling
Published: January 2025

Studying the energy loss characteristics of the electrical submersible pump (ESP) under stalling conditions is beneficial for reducing the global carbon emissions. By combining steady and unsteady numerical simulations with entropy production (EP) theory, the evolution of internal vortices in the ESP under stalling conditions is analyzed, and a theoretical model for predicting energy loss based on EP is established. The results show that turbulent dissipation entropy production inside the ESP is the main component of total entropy production. Under critical stall conditions, the stability of vortices inside the impeller of a single-stage ESP is higher. However, in the first-stage impeller of a multi-stage ESP, the periodic shedding and breakdown of vortices lead to a turbulent flow field at the inlet of the diffuser, resulting in increased impact losses. Under deep stall conditions, the inlet recirculation vortices in the impeller of a single-stage ESP exhibit a symmetric distribution. In multi-stage pumps, the evolution period of inlet recirculation vortices is asynchronous with the impeller rotation period. There are differences in the shedding period of vortices in each flow channel, resulting in nonsymmetrical distributions of vortices in the circumferential and radial directions. The interaction between the outlet vortices of the diffuser and the passage vortices leads to the formation of multiple high-energy, small-scale vortex structures at the entrance to the next-stage impeller. It will further lead to fluid separation and cause the next-stage impeller to enter a stall condition. The research results offer valuable insights that can be utilized as references for optimizing design and field application of ESPs.
Atomistic dynamics of elimination and substitution driven by entrance channel
Authors: Yang Li , Zhao Siwei , Wang Hongyi , Fu Gang , Zhen Wenqing , Bai Xiang , Zhang Jiaxu
Published: January 2025

E2 elimination and SN2 substitution reactions are of central importance in preparative organic synthesis due to their stereospecificity. Herein, atomistic dynamics of a prototype reaction of ethyl chloride with hydroxide ion are uncovered that show strikingly distinct features from the case with fluoride anion. Chemical dynamics simulations reproduce the experimental reaction rate and reveal that the E2 proceeding through a direct elimination mechanism dominates over SN2 for the hydroxide ion reaction. This unexpected finding of a pronounced contribution of direct reaction dynamics, even at a near-thermal energy, is in strong contrast to the complex-mediated indirect mechanism for the fluoride case that characterizes the low-energy ion–molecule reactions. The entrance channel structures are found to be crucial and the differences are attributed to subtle changes in the hydrogen-bonding interaction of the approaching reactants. This effect presents in E2/SN2 reactions of different bases and alkyl halides and might play a role in complex chemical networks and environments.
Research on mechanical analysis and optimal design of electromagnetic variable pre-pressure ultrasonic motor
Authors: Niu Ruikun , Guo Yong , Wu Guanqi , Liu Jun
Published: January 2025

Ultrasonic motors have been widely applied and promoted due to their advantages, such as low-speed high torque, fast response, and self-locking upon power loss. However, their working principle relies on contact friction drive, and the magnitude of the applied pre-pressure directly affects their performance output. Traditionally, the magnitude of pre-pressure applied to ultrasonic motors is mainly set during manufacturing and assembly and cannot be adjusted during operation, which also affects the maximization of their performance. To address the above issues, this paper proposes the design of an electromagnet-type variable pre-pressure ultrasonic motor that adjusts the pre-pressure by controlling the driving voltage of the coil. The force and motion analysis of the core components is conducted, and the basic parameters of the electromagnetic mechanism are calculated according to design requirements. An electromagnetic-type variable pre-pressure ultrasonic motor control circuit based on speed feedback is designed, and a control method for the variable pre-pressure motor is proposed. Magnetic circuit simulation is conducted, and internal structural size parameters are optimized. Finally, experiments are conducted on the processed prototype. The results show that using the electromagnet-type variable pre-pressure ultrasonic motor can achieve speed adjustment through pre-pressure adjustment, maintaining a wide adjustment range under heavy load conditions, which is conducive to achieving a better low-speed high-torque output.
The characteristics of coarse particle solid–liquid two-phase flow and wear properties in deep-sea multistage mining pumps
Authors: Jin Yuzhen , Cai Zhaoxiang , Cui Jinyu
Published: January 2025

This paper designs flow-through components based on empirical formulas. It examines the solid–liquid two-phase flow characteristics of coarse particles in a novel deep-sea multistage mining pump using a Computational Fluid Dynamics-Discrete Element Method model. The flow characteristics and variation patterns of the cascade end faces between different stages under various particle sizes are investigated, along with the local flow and particle motion characteristics within the flow channels. Additionally, the effect of varying coarse particle sizes on the wear behavior of the flow-through components is examined. This study contributes to reducing wear during particle transport, improving the efficiency and stability of coarse particle transport, and supporting the development of solid–liquid two-phase flow theory for coarse particles.
Pair approximating the action for molecular rotations in path integral Monte Carlo
Authors: Moeed Muhammad Shaeer , Serwatka Tobias , Roy Pierre-Nicholas
Published: January 2025

Typical path integral Monte Carlo approaches use the primitive approximation to compute the probability density for a given path. In this work, we develop the pair discrete variable representation (pair-DVR) approach to study molecular rotations. The pair propagator, which was initially introduced to study superfluidity in condensed helium, is naturally well-suited for systems interacting with a pairwise potential. Consequently, paths sampled using the pair action tend to be closer to the exact paths (compared to primitive Trotter paths) for such systems leading to convergence with less imaginary time steps. Our approach relies on using the pair factorization approach in conjunction with a discretized path integral ground state paradigm to study a chain of planar rotors interacting with a pairwise dipole interaction. We first use the Wigner–Kirkwood density expansion to analyze the asymptotics of the pair propagator in imaginary time. Then, we exhibit the utility of the pair factorization scheme via convergence studies comparing the pair and primitive propagators. Finally, we compute energetic and structural properties of this system including the correlation function and Binder ratio as functions of the coupling strength to examine the behavior of the pair-DVR method near criticality. The density matrix renormalization group results are used for benchmarking throughout.
High-performance desulfurizer via simultaneous grinding and hydration using a steam jet mill
Authors: Fu Yu , Huang Shenglong , Leng Yuanjian , Lin Longyuan , Chen Haiyan , Lǖ Juan
Published: January 2025

The low desulfurization efficiency notably restricts the wide application of dry desulfurization technology, although it is characterized by its cost-effectiveness and simple processes in the desulfurization domain. Consequently, the development of high-performance desulfurizers has become an increasingly pressing task to increase desulfurization efficiency. In this study, we strived to improve the desulfurization performance of calcium-based sorbents by using a steam jet mill to process quicklime and then evaluate its desulfurization capacity. According to the results, under the influence of different rotational speeds of the classifiers, instantaneous crushing and hydration could be simultaneously achieved at steam temperatures ranging from 150 to 260 °C, and the hydration rate of calcium oxide in quicklime could reach 100%. With the rise in temperature and rotational speed, the absorbent exhibited larger specific surface areas, narrower particle sizes, and enhanced activity. The optimized parameters for preparing the absorbent are a relative humidity of 10%, a steam temperature of 260 °C, and a rotational speed of 1350 r·min−1. Under such circumstances, the operating time with 100% desulfurization efficiency could extend to 420 min. The preparation of the high-performance desulfurizer in this study addresses the technical bottleneck of the relatively low efficiency of dry desulfurization, thereby significantly advancing the application of dry flue gas desulfurization technology.
Fluid identification in geological exploration using transformer models and deep reinforcement learning
Authors: Yin Wenjing , Li Hengxiao , Zhao Zhiyuan , Qiao Sibo
Published: January 2025

In geological exploration, identifying fluids is essential for assessing the potential of oil and gas reservoirs. This research presents a refined method for fluid detection using log data by integrating advanced transformer models with deep reinforcement learning, aiming to enhance the precision and efficiency of fluid identification. We use traditional well-logging data as input, with transformer models employed for feature extraction. These models excel at processing sequential data and capturing long-range dependencies within logging sequences, which leads to a more accurate depiction of geological formations. Furthermore, the self-attention mechanisms within transformers enhance their flexibility and precision in analyzing complex geological structures. We incorporate deep reinforcement learning (DRL) strategies to improve fluid identification further. The DRL framework establishes an environment where an agent learns to maximize fluid identification accuracy by dynamically selecting and adjusting model parameters in response to different geological conditions. This integration increases the model's adaptability and bolsters its robustness when encountering unfamiliar or variable geological settings. We validated the effectiveness of this approach using well-logging datasets from the Tarim Oilfield. The experimental results indicate significant improvements in accuracy and operational efficiency compared to traditional methods. Specifically, the proposed approach excels in handling complex geological structures, significantly reducing misidentification rates and enhancing overall identification accuracy.
A neural network model to study factors impacting the selection of hazardous fuel treatment types in Colorado’s national forests
Authors: Magstadt Shayne , Wei Yu
Published: January 2025

Background Selecting suitable fuel treatment locations and types is important for reducing wildfire risks in Colorado’s national forests. Understanding factors influencing these decisions is needed for effective management. Aims This study analyses land management data from 2015 to 2024 using a single multiclass neural network model to understand the drivers influencing fuel treatment decisions in 11 Colorado national forests. Methods We utilise Forest Activity Tracking System data, incorporating variables such as wildfire risk, landscape features and human influences. The model employs a feed-forward backpropagation technique to train a neural network model on the spatial dataset. Key results The model identifies significant factors associated with past fuel treatment decisions, including burn probability, wildfire hazard potential, conditional flame length and proximity to structures. Analysis reveals the importance of these variables in shaping treatment selection strategies, the model AUC (area under curve) of 0.91 indicating strong predictive performance across the six treatment categories. Conclusions Neural networks provide a robust method for analysing past fuel treatment choices. Accurately identifying key factors, this approach provides suggestions to improve future fuel treatment decisions. Implications This approach can enhance wildfire mitigation planning across Colorado’s national forests. The findings support more informed wildfire mitigation strategies, with potential applications extending to broader forest management practices.
Modelling and mapping burn severity of prescribed and wildfires across the southeastern United States (2000–2022)
Authors: Vanderhoof Melanie K. , Menick Casey E. , Picotte Joshua J. , Robertson Kevin M. , Nowell Holly K. , Matechik Chris , Hawbaker Todd J.
Published: January 2025

Background The southeastern United States (‘Southeast’) experiences high levels of fire activity, but the preponderance of small and prescribed fires means that existing burn severity products are incomplete across the region. Aims We developed and applied a burn severity model across the Southeast to enhance our understanding of regional burn severity patterns. Methods We used Composite Burn Index (CBI) plot data from across the conterminous US (CONUS) to train a gradient-boosted decision tree model. The model was optimised for the Southeast and applied to the annual Landsat Burned Area product for 2000–2022 across the region. Key results The burn severity model had a root mean square error (RMSE) of 0.48 (R2 = 0.70) and 0.50 (R2 = 0.37) for the CONUS and Southeast, respectively. The Southeast, relative to CONUS, had lower mean absolute residuals in low and moderate burn severity categories. Burn severity was consistently lower in areas affected by prescribed burns relative to wildfires. Conclusions Although regional performance was limited by a lack of high burn severity CBI plots, the burn severity dataset demonstrated patterns consistent with low-severity, frequent fire regimes characteristic of Southeastern ecosystems. Implications More complete data on burn severity will enhance regional management of fire-dependent ecosystems and improve estimates of fuels and fire emissions.
The Small Bang
Authors: Hantgan Abbie
Published: January 2025

Language isolates, often viewed as remnants of past linguistic diversity, are predominantly spoken
at the edges of dominant linguistic areas. This study explores the origins of the Bangime isolate and its Bangande
speakers. By correlating loan words associated with agriculture with interdisciplinary data, the paper focuses on West
African crops like millet and sorghum to suggest a Bangande migration timeline. This research contributes to a study
on the origins of loan words for plants and animals linked to their domestication in West Africa. Preliminary results
indicate a link between early Bangime speakers and Mande communities, especially the Soninke-Bozo. It is yet to be
determined if the Bangande originally farmed in their present territories or elsewhere.
Combining disparate lines of evidence in the study of the history of language isolates, exemplified with
Mochica from Northern Peru
Authors: Urban Matthias
Published: January 2025

This article provides a synthesizing discussion of different lines of evidence for the linguistic
history of the Mochica language (Northern Peru). Among the topics discussed are the inference of the former geographic
extension through toponymic study; the study of indigenous personal names as a fertile source of information on
grammatical structure, particularly the genesis and nature of an unusual numeral classifier system; internal
reconstruction; local as well as rather spectacular cases of long-distance language contact; areal typology;
sociolinguistic typology; the reconstruction of outlines of the social ecology of the language in its pre-Columbian
context; and the interdisciplinary contextualization of linguistic data with that of other disciplines that study
human prehistory. Thus, the article provides an exemplary case study of the richly textured picture which a
multi-pronged approach can paint on the history of isolates.
Introduction
Authors: Salaberri Iker , Krajewska Dorota , Santazilia Ekaitz , Zuloaga Eneko
Published: January 2025

This paper discusses the issues faced by linguists analyzing language isolates, namely their
definition, recovering their histories, and commonly used methods that implicitly rely on non-isolate status. This is
followed by a critical review of recent approaches meant to overcome these issues. We argue that the techniques used
to retrieve the history of non-isolate languages are also valid for isolates, including the comparative method applied
to dialects, internal reconstruction, the philological study of texts, the study of past and present situations of
language contact, and typological comparison. Nevertheless, we contend that new methodologies should be developed and
combined with the already existing ones. We conclude by summarizing how the papers included in this volume contribute
to the study of isolates.
Exploring null geodesic of Finslerian hairy black hole
Authors: Nekouee Z , Narasimhamurthy S K , Yashwanth B R , Sanjay T
Published: January 2025

The study of hairy black holes within Finsler space-time is performed based on a fundamental set of criteria. These requirements include the presence of a clearly defined event horizon and compliance with the strong energy condition for the characteristics outside the horizon. This examination is conducted through the gravitational decoupling method to describe the deformation of a Finslerian Schwarzschild (FSch) black hole due to the inclusion of additional arbitrary sources (scalar field, tensor field, fluidlike dark matter, etc). So, it is characterized by the primary hair (

L

0

=
α

l

) where the parameter

l

is linked to gauge transformations of the seed FSch metric and α is the deformation factor apart from flag curvature (λ) and mass (M). This study focuses on determining the black hole’s temperature and heat capacity, which are crucial for understanding its thermodynamic properties. Additionally, we examine how the hairy parameters influence these thermodynamic characteristics, providing a deeper understanding of the interplay between the black hole’s structure and its thermal behavior. Moreover, this paper investigates the null geodesics around the Finslerian hairy Schwarzschild black hole, where we obtain the physical parameters associated with these geodesics, including the effective potential, the photon sphere radius, and the impact parameter and investigate the effects of Finslerian parameter ε and hairy parameters (

α
,

l

) on these values. This study aims to enhance our understanding of the structure of space-time and the behavior of light in proximity to black holes.
Inhibition of Pt-InGaAs chemical reaction by Al incorporation: towards stable Pt Schottky barriers on GaAs-based alloys and compounds
Authors: Xiong Jianming , Chen Zheng , Gong Tao , Dong Jiawei , Hu Wenyu , Ma Zhenyu , Deng Yong , Zheng Jiawei , Zhang Xin , Ma Jian , Chen Longqing , Li Jinfeng , Wang Xiaoyi , Qiu Yang , Dang Manyu , Deng Huiwen , Tang Mingchu , Liu Huiyun , Zhu Jun , Ruterana Pierre
Published: January 2025

Platinum and Gallium Arsenide reaction is a common issue for the stability of Pt-GaAs contacts, where the formation of different alloys during the fabrication and operation degrades the performance of the devices. In this work, we have carried out in situ deposition of Pt on GaAs and InAlGaAs in the focused ion beam machine and carried out annealing in the high-resolution transmission electron microscope. The local strains were then determined using the geometrical phase analysis technique and the various phases were obtained by digital extraction of lattice fringes. They are mainly Pt3InGa and Pt3InGaAl metallic nanoparticles and it is shown that the occupancy of In/Ga sites by Al atoms shrinks the Pt3InGa local lattice. This strong compression of the (001) and (110) atomic plane narrows the dimer row and thus hinders the diffusion of large atoms such as In/Ga. Therefore, the Schottky barrier is stabilized as further chemical reaction of Pt-InGaAs is blocked. The highest degree of electron localization between Pt and Al atoms is further confirmed by electron localization function calculations.
High-performance microchannel plates based on atomic layer deposition for the preparation of functional layers
Authors: Lian Zhuoxi , Wang Dan , Zhu Xiangping , He Yongning
Published: January 2025

Microchannel plates (MCPs) are critical devices used in electron multiplication for applications such as night vision, mass spectrometry, and particle detection. Traditional MCP fabrication using lead silicate glass faces challenges in meeting the increasing demands for high gain, long lifespan, and low noise. In this study, pursuing MCP with excellent performance, atomic layer deposition (ALD) technology was employed to prepare Ru/Al2O3 composite film and Al2O3 film as the conductive layer and secondary electron emission (SEE) layer respectively in microchannels. By optimizing the ALD cycle ratio of Ru and Al2O3, process parameters that satisfy the MCP bulk resistance requirements were obtained. As the number of ALD cycles for Ru increases, the bulk resistance decreases, enabling the regulation of bulk resistance within the range of tens to hundreds of megaohms. The variation of the secondary electron yield of Al2O3 film with increasing thickness was investigated, and a preferable thickness of 5–7 nm was obtained. When the ALD cycle ratio of Ru to Al2O3 in the conductive layer is 29:10 and the thickness of the Al2O3 film in the SEE layer is 7 nm, the gain of the fabricated MCP exceeds 3 × 105 at a bias voltage of 1500 V. As well as the fabricated MCP also exhibits excellent uniformity and stability in electron multiplication. Additionally, a GaAs image intensifier utilizing the prepared MCP exhibited superior performance in field-of-view uniformity, low-light imaging, and resolution. This study makes significant engineering sense for enhancing MCP performance and expanding its applications in imaging and related fields.
Toward the first gluon parton distribution from the LaMET
Authors: Good William , Hasan Kinza , Lin Huey-Wen
Published: January 2025

We present progress towards the first unpolarized gluon quasi-parton distribution function (PDF) from lattice quantum chromodynamics using high-statistics measurements for hadrons at two valence pion masses M

π
 ≈ 310 and 690 MeV computed on an a ≈ 0.12 fm ensemble with 2 + 1 + 1-flavors of highly improved staggered quark generated by the MILC collaboration. In this study, we consider two gluon operators for which the hybrid-ratio renormalization matching kernels have been recently derived and a third operator that has been used in prior pseudo-PDF studies of the gluon PDFs. We compare the matrix elements for each operator for both the nucleon and pion, at both pion masses, and using two gauge-smearing techniques. Focusing on the more phenomenologically studied nucleon gluon PDF, we compare the ratio and hybrid-ratio renormalized matrix elements at both pion masses and both smearings to those reconstructed from the nucleon gluon PDF from the CT18 global analysis. We identify the best choice of operator to study the gluon PDF and present the first gluon quasi-PDF under some caveats. Additionally, we explore the recent idea of Coulomb gauge fixing to improve signal at large Wilson-line displacement and find it could be a major help in improving the signal in the gluon matrix elements. This work helps identify the best operator for studying the gluon quasi-PDF, shows higher hadron boost momentum is needed to implement hybrid-ratio renormalization reliably, and suggests the need to study more diverse set of operators with their corresponding perturbative calculations for hybrid-ratio renormalization to further gluon quasi-PDF study.
Near-infrared confocal laser scanning microscope system with InGaAs focal plane array
Authors: Li Haotian , Liu Junliang , Dong Yakui , Fei Cheng , Li Yongfu , Yang Shuolin , Fan Shuzhen , Liu Yunxia , Zhao Xian
Published: January 2025

Today, more and more silicon-based chips apply new flip-chip packages to accommodate the high density and power consumption requirements of electronic products. In this case, defect detection in the flip-chip package is essential. However, silicon-based materials are opaque to visible wavelengths, making it difficult to identify defects within the chip or wafer. By utilizing the property that near-infrared (NIR) light can pass through silicon, NIR confocal imaging is a promising non-destructive method to detect defects inside silicon chips. In this study, we report an integrated NIR confocal scanning microscope system consisting of a NIR microscope and a NIR confocal scanning system, which uses an InGaAs focal plane array as a detector instead of the conventional combination of a small pinhole and a photo-multiplier tube or an avalanche photodiode. The proposed confocal scanner can detect devices of different sizes in the field of view, obtain high-contrast and three-dimensional images of the internal structure, and can be effectively employed as an in-line inspection system for detecting surface and internal defects during chip manufacturing.
Comparison of PPP-RTK performance under different regional ionospheric models
Authors: Li Bingqing , Zeng Ran , Wen Qiang , Li Guangcai , Geng Jianghui
Published: January 2025

Establishing a regional ionospheric model to provide precise ionospheric products is a prerequisite for rapid real-time kinematic precise point positioning (PPP-RTK). Thus, a stochastic model for these real-time ionospheric products is also crucial. In this study, we use a Wuhan regional network (average inter-station distance of about 30 km) to comparatively analyze four regional ionospheric modeling methods with commonly-used stochastic models: the inverse distance weighting model (IDW), the quasi-four-dimension ionospheric modeling (Q4DIM), the first-order polynomial function model with internal validation (POLY), and the first-order polynomial function model with external validation (POLY-EV). Our results show that, the POLY/POLY-EV model has the smallest ionospheric delay interpolation root mean square (RMS) error, regardless of whether for inside or peripheral stations of the regional network, during both quiet and active ionospheric conditions. For 4024 and 4314 one-hour samples, the PPP-RTK results show that at inside stations, all four models converge to a horizontal precision of 10 cm within two epochs, with the POLY-EV model having the highest horizontal positioning precision (a mean RMS of 0.83 cm). At the peripheral station, PPP-RTK with the POLY/POLY-EV model achieves a horizontal precision of 10 cm within two epochs, while the IDW and Q4DIM models need 4 and 43 epochs, respectively. The horizontal positioning precision of PPP-RTK using the POLY-EV model is the highest, with a mean RMS of 1.59 cm.
Stochastic model of accelerated cooling of eutectoid steel rails
Authors: Szeliga Danuta , Foryś Jakub , Jażdżewski Tomasz , Kusiak Jan , Kuziak Roman , Nadolski Rafał , Oprocha Piotr , Pietrzyk Maciej , Potorski Paweł , Rauch Łukasz , Zalecki Władysław
Published: January 2025

The paper proposes a methodology for incorporating uncertainties of material behaviours in the microstructure evolution model for eutectoid steels. The stochastic model of phase transformations was developed. The model accounts for a random character of the nucleation of pearlite and bainite and the differential growth equations for these structural components are solved for the stochastic variables. The coefficients in the model were identified using inverse analysis for the results of dilatometric tests. The model was applied to simulations of the cooling of rails by subsequent immersions of the rail head in the polymer solution. Johnson–Mehl–Avrami–Kolmogorow phase transformations model was used to design the optimal cooling cycle. Histograms of the microstructural parameters for this optimal cycle were calculated using the developed stochastic model. It was shown that the probability distributions of the pearlite colony size, the nodule size, the interlamellar spacing and the hardness are asymmetric. The model predicted deviations of microstructural parameters and hardness from the mean values.
Microwave welding with SiCNW/PMMA nanocomposite thin films: enhanced joint strength and performance
Authors: Foong Phey Yee , Voon Chun Hong , Lim Bee Ying , Teh Pei Leng , Yeoh Cheow Keat , Parmin Nor Azizah , Gopinath Subash C B , Low Foo Wah , Abdul Rahim Nor Azura , Perumal Veeradasan
Published: January 2025

Most previously reported susceptors for microwave welding are in powder form. In this study, a thin-film susceptor was employed due to its uniform heating rate and ease of handling. Silicon carbide nanowhisker (SiCNW) were incorporated into a poly(methyl methacrylate) (PMMA) matrix to create a nanocomposite thin film, which served as the susceptor. The microwave welding process involved three straightforward steps: fabrication of the PMMA/SiCNW nanocomposite thin film, application of the nanocomposite film to the target area, and subsequent microwave heating. Upon cooling, a robust microwave-welded joint was formed. The mechanical properties and microstructure of the welded joints were characterized using single-lap shear tests, three-point bending tests, and scanning electron microscopy. Results demonstrated that the shear strength and elastic modulus of the welded joints were optimized with increased heating time and SiCNW filler loading. This optimization is attributed to the formation of a SiCNW-filled polypropylene (PP) nanocomposite layer of increasing thickness at the welded joint interface. However, the incorporation of SiCNW also constrained the mobility of the PP chains, reducing the joint’s flexibility. Furthermore, the welded joint formed with the PMMA/SiCNW nanocomposite thin-film susceptor exhibited an 18.82% improvement in shear strength compared to joints formed with a powdered SiCNW susceptor. This study not only demonstrates the potential of PMMA/SiCNW nanocomposite thin films as efficient susceptors for microwave welding but also paves the way for developing high-performance polymer-based composite joints with improved mechanical properties for applications in the automotive, aerospace, and construction industries.
A solvable leaning ladder problem
Authors: Cross Rod
Published: January 2025

Measurements are presented on the vertical force at the bottom end of a leaning metal ruler. The force can be calculated directly if the upper end of the ruler is supported by a length of string, unlike the usual leaning ladder problem.
Gyrokinetic analysis of core turbulent transport in high-β scenarios in the EHL-2 spherical torus
Authors: Tan M Z , Xu J Q , Xu C Z , Wu X H , Dong J Q , Xie H S , Wang X Y , Du H R , Jiang X C , Wang Y M , Gu X , Liu B , Shi Y J , Liang Y F
Published: January 2025

ENN is dedicated to exploring the commercialization of fusion energy by utilizing the EHL-2 spherical device as a next-generation platform. This research focuses on evaluating turbulent transport in the core ion transport barrier region of EHL-2, specifically investigating the effects of plasma β on transport features. Gyrokinetic simulation results indicate that under the typical operation scenario, transport is predominantly driven by electrostatic ion temperature gradient modes and trapped electron modes. Nevertheless, as the total β approaches 20%, nonlinear excitation of the electromagnetic mode is discovered, leading to an explosive increase in transport as well as zonal flow erosion due to enhanced magnetic fluctuations. It is also found that the external E × B rotational shear is only effective in suppressing the turbulence when the electromagnetic modes are linearly stable or nonlinearly unstable.
Obtaining highly homogeneous Nb3Al superconductor with improved critical current density by understanding the phase evolution sequence of mono-core and multifilamentary wires
Authors: Yu Zhou , Sun Xiaguang , Zhang Yuyao , Tang Xuan , Gu Xiaojiao , Liu Lian , Wang Wentao , Zhao Yong
Published: January 2025

Mono-core and multifilamentary (MF) Nb–Al precursor wires were obtained by a rapid heating, quenching and transformation (RHQT) process to investigate the phase evolution sequence, in order to find a way to fabricate highly homogeneous Nb3Al superconductor. The microstructure and composition distribution of the Nb3Al superconductor is the same as that of quenched wires. Phase evolution (1) in mono-core wire is as follows: Nb + Al→ eutectic phase +Nb2Al + Nb3Al→ grid-shape Nb(Al)ss→ band-like Nb(Al)ss, where nonuniform microstructure is formed in the transformed Nb3Al because the Nb layer is too thick; (2) in MF wire is as follows: Nb + Al→ Nb2Al + Nb3Al→solid Nb(Al)ss→ two-phase-segregation→ liquid Nb(Al)ss, where much thinner Nb layers completely react to Nb3Al and Nb2Al, but the Al content of Nb3Al phase is still inhomogeneous. Restricted by the precursor wire fabrication ability, further decreasing the Nb layer thickness fails to improve the homogeneity of Nb3Al phase. Therefore, the author’s route of afresh heating of the quenched Nb2Al + Nb3Al wire was carried out to increase the atomic diffusion coefficient due to the non-equilibrium crystal defects present in the quenched wires. As a result, a highly composition homogeneous Nb3Al phase was realized in the whole superconducting filament with a scale of about ∼100 μm. The magnetic critical current density (J
c) of the afresh heated Nb3Al superconductor reached 2066 A mm−2@12 T, 4.2 K, showing an improvement of about 60% compared to the best J
c result for the MF RHQT Nb3Al wire.
Macroproperties vs. microstates in the classical simulation of critical phenomena in quench dynamics of 1D Ising models
Authors: Mitra Anupam , Albash Tameem , Blocher Philip Daniel , Takahashi Jun , Miyake Akimasa , Biedermann Grant , Deutsch Ivan H
Published: January 2025

We study the tractability of classically simulating critical phenomena in the quench dynamics of one-dimensional transverse field Ising models (TFIMs) using highly truncated matrix product states (MPSs). We focus on two paradigmatic examples: a dynamical quantum phase transition (DQPT) that occurs in nonintegrable long-range TFIMs, and the infinite-time correlation length of the integrable nearest-neighbor TFIM when quenched to the critical point, where the quantities of interest involve equal time one- and two- point correlation functions, which we associate with macroproperties. For the DQPT, we show that the order parameters can be efficiently simulated with heavy truncation of the MPS bond dimension. This can be used to reliably extract critical properties of the phase transition, including critical exponents, even when the full many-body state is not simulated with high fidelity. The long-time correlation length near the critical point is more sensitive to the full many-body state fidelity, and generally requires a large bond dimension MPS. Nonetheless, this can still be efficiently simulated with strongly truncated MPS because it can be extracted from the short-time behavior of the dynamics where entanglement is low. Our results provide illustrations of scenarios where accurate calculation of the full many-body state (microstate) is intractable due to the volume-law growth of entanglement, yet a precise specification of an exact microstate may not be required when simulating macroproperties that play a role in phases of matter of many-body systems. We also study the tractability of simulation using truncated MPS based on quantum chaos and equilibration in the models. We find a counterintuitive inverse relationship, whereby local expectation values are most easily approximated for chaotic systems whose exact many-body state is most intractable.
Low-mass constraints on WIMP effective models of inelastic scattering using the Migdal effect
Authors: Kang Sunghyun , Scopel Stefano , Tomar Gaurav
Published: January 2025

We use the Migdal effect to extend to low masses the bounds on each of the effective couplings of the non-relativistic effective field theory of a WIMP of mass mχ
and spin 1/2 that interacts inelastically with nuclei by either upscattering to a heavier state with mass splitting δ > 0 or by downscattering to a lighter state with δ < 0. In order to do so we perform a systematic analysis of the Migdal bounds in the mχ
-δ parameter space comparing them to those from nuclear recoil searches.
The Migdal effect allows to significantly extend to low WIMP masses the nuclear recoil bounds for δ < 0. In this case the bounds are driven by XENON1T, except when δ is vanishing or very small, when, depending on the WIMP-nucleus interaction, in the lower end of the mχ
range either DS50 or SuperCDMS are more constraining. On the other hand, when δ > 0 and the WIMP particle upscatters to a heavier state nuclear recoil bounds are stronger than those from the Migdal effect.
Bayesian technique to combine independently-trained machine-learning models applied to direct dark matter detection
Authors: Cerdeño David , de los Rios Martin , Perez Andres D.
Published: January 2025

We carry out a Bayesian analysis of dark matter (DM) direct detection data to determine
particle model parameters using the Truncated Marginal Neural Ratio Estimation (TMNRE) machine
learning technique. TMNRE avoids an explicit calculation of the likelihood, which instead is
estimated from simulated data, unlike in traditional Markov Chain Monte Carlo (MCMC)
algorithms. This considerably speeds up, by several orders of magnitude, the computation of the
posterior distributions, which allows to perform the Bayesian analysis of an otherwise
computationally prohibitive number of benchmark points. In this article we demonstrate that, in
the TMNRE framework, it is possible to include, combine, and remove different datasets in a
modular fashion, which is fast and simple as there is no need to re-train the machine learning
algorithm or to define a combined likelihood. In order to assess the performance of this method,
we consider the case of WIMP DM with spin-dependent and independent interactions with protons and
neutrons in a xenon experiment. After validating our results with MCMC, we employ the TMNRE
procedure to determine the regions where the DM parameters can be reconstructed. Finally, we
present CADDENA, a Python package that implements the modular Bayesian analysis of direct
detection experiments described in this work.
cp3-bench: a tool for benchmarking symbolic regression algorithms demonstrated with cosmology
Authors: Thing M.E. , Koksbang S.M.
Published: January 2025

We introduce cp3-bench, a tool for comparing/benching symbolic regression algorithms, which we make publicly available at https://github.com/CP3-Origins/cp3-bench. In its current format, cp3-bench includes 12 different symbolic regression algorithms which can be automatically installed as part of cp3-bench. The philosophy behind cp3-bench is that is should be as user-friendly as possible, available in a ready-to-use format, and allow for easy additions of new algorithms and datasets. Our hope is that users of symbolic regression algorithms can use cp3-bench to easily install and compare/bench an array of symbolic regression algorithms to better decide which algorithms to use for their specific tasks at hand.

To introduce and motivate the use of cp3-bench we present a small benchmark of 12 symbolic regression algorithms applied to 28 datasets representing six different cosmological and astroparticle physics setups. Overall, we find that most of the benched algorithms do rather poorly in the benchmark and suggest possible ways to proceed with developing algorithms that will be better at identifying ground truth expressions for cosmological and astroparticle physics datasets. Our demonstration benchmark specifically studies the significance of dimensionality of the feature space and precision of datasets. We find both to be highly important for symbolic regression tasks to be successful. On the other hand, we find no indication that inter-dependence of features in datasets is particularly important, meaning that it is not in general a hindrance for symbolic regression algorithms if datasets e.g. contain both z and H(z) as features. Lastly, we note that we find no indication that performance of algorithms on standardized datasets are good indicators of performance on particular cosmological and astrophysical datasets. This suggests that it is not necessarily prudent to choose symbolic regression algorithms based on their performance on standardized data. Instead, a more robust approach is to consider a variety of algorithms, chosen based on the particular task at hand that one wishes to apply symbolic regression to.