bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of thermophoresis and transpiration impacts on electromagnetic convective non-Darcy radiative flow past a rotating cone
Authors: V Shobha. , P Baskar. , Varma S. V. K. , Kumar B. Rushi
Published: December 2024

This study presents a comprehensive mathematical model to investigate the intricate transport processes involving transpiration, thermal radiation, and a magnetic field in a viscous, incompressible fluid around a rotating vertical cone. By applying suitable transformations, the governing equations were non-dimensionalized and then solved numerically using the bvp4c method. The resulting velocity, temperature, and concentration profiles were examined under practical boundary conditions, and the findings were found to be in excellent agreement with the existing literature, validating the model's accuracy. The study further explores the influence of various factors, including the thermophoretic coefficient, magnetic field, thermal radiation, transpiration, Forchheimer parameters, and relative differences in temperature and concentration, on the flow characteristics. Additionally, the impact of these parameters on mass and heat transfer rates, represented by the Sherwood and Nusselt numbers with thermophoretic particle deposition velocity Vd* and local Stanton number Str was analyzed. Notably, the study highlights the sensitivity of the wall thermophoretic velocity to changes in physical parameters, which significantly affects the flow behavior under different transpiration parameter values. The findings of this study provide valuable insights into the complex interplay between the governing physical phenomena and offer a robust numerical framework for understanding and predicting the transport processes in rotating vertical cone systems with practical applications in various fields, such as engineering, geophysics, and astrophysics.
Transport of a solute in primary and secondary flows through a rotating channel with an absorbing wall
Authors: A Aruna , Barik Swarup , Poddar Nanda
Published: December 2024

This study uses a multi-scale homogenization technique to provide an analytical solution for solute transport in a viscous fluid flowing between rotating parallel plates. The analytical solutions for the mean and vertical concentration distributions of the solute are derived up to second-order approximations. The channel undergoes rotation around an axis perpendicular to its walls with uniform angular velocity, resulting in a secondary flow. Most previous literature focused on determining the dispersion coefficient for the primary flow. Apart from the dispersion coefficient, we also found the mean and vertical concentration distributions for both primary and secondary flows. The effects of a dimensionless rotation parameter (α) and boundary absorption parameters on solute mean and vertical concentration distributions in both flow directions are discussed. Results reveal that, for the primary flow, the peak of the mean concentration distribution of the solute increases until α=2.2, then becomes flat with higher α. This phenomenon is due to the emergence of the Coriolis force, which shifts the maximum velocity toward the walls, thereby increasing velocity variation across the channel, whereas for secondary flow, the mean concentration increases with increasing α. However, in the secondary flow direction, the vertical concentration distribution reaches uniformity over significantly longer timescales (e.g., dimensionless τ∼105, for α = 2) than the primary flow (dimensionless τ∼10).
Computational thrombosis modeling based on multiphase porous media theory for prognostic evaluation of aortic dissection after stenting
Authors: Li Xiaofan , Zhang Shuaitong , Zhang Xuehuan , Zhang Xuyang , Yang Yuting , Xu Yao , Xie Chiyu , Xiong Jiang , Chen Duanduan
Published: December 2024

Accurately and rapidly predicting the occurrence and progression of false lumen thrombosis in patients undergoing thoracic endovascular aortic repair (TEVAR) is crucial for optimizing patient recovery. Traditional models for predicting false lumen thrombosis often lack the ability to capture phase interface changes, and their complex parameters and algorithms result in a long computation time. This study introduces a multiphase porous media approach that can accurately and rapidly predict thrombus formation in aortic dissection patients at different postoperative stages. The approach employed the Darcy–Brinkman–Stokes equation to model the interaction between the thrombotic and fluid phases and incorporated a novel porosity equation to explicitly capture phase interface dynamics. Additionally, the hemodynamic parameters associated with thrombus formation were updated to enhance the physical accuracy of the algorithm while reducing its computational complexity. Using patient-specific models derived from computed tomography angiography datasets, our algorithm demonstrated excellent predictive performance in real patients. The predicted thrombus morphology in the third and sixth months postoperatively closely matched the actual imaging data, with discrepancies in thrombus volume remaining within a ±10% range at each postoperative stage. Moreover, the algorithm significantly improved computational convergence, reducing the computation time to 30 minutes and enhancing the computational efficiency by 80% compared to traditional methods. By integrating the porous media framework, this approach offers a valuable tool for rapid clinical diagnosis and the prediction of post-TEVAR recovery.
Numerical analysis of flow-induced vibrations and heat transfer in a triangular arrangement of circular cylinders
Authors: Maali Mohammad Ebrahim , Poshtiri Amin Haghighi , Jamshidi Saeed
Published: December 2024

This numerical study explores the flow characteristics and heat transfer performance of three isothermal circular cylinders arranged in a triangular configuration at angles of attack of 45° and 60°. The impact of one-degree-of-freedom (1DOF) flow-induced vibrations (FIV) in the cross-flow direction on forced convective heat transfer is analyzed using ANSYS FLUENT, considering reduced velocities from 4 to 8 at a constant Reynolds number of 100. Comparative simulations are conducted for both stationary and vibrating cylinders. Results indicate that, when stationary, the cylinders at a 45° angle exhibit lower heat transfer rates compared to those at 60°, with a 2.66% reduction in overall heat transfer. The study also examines the nuanced effects of 1DOF FIV in the cross-flow direction on heat transfer: while the upstream cylinder generally experiences increased heat transfer during vibrations, the downstream cylinders often show reduced rates. Specifically, at a 45° angle, the most significant reduction in heat transfer from downstream cylinders, nearly 9.99%, occurs at reduced velocities of 5 and 6. For the stationary tube bundle at 45°, the average Nusselt number is 11.77, but it decreases by approximately 5.21% at a reduced velocity of 5 under vibration. Conversely, at a 60° angle, the average Nusselt number generally increases at higher reduced velocities, except at Ur = 4, where it drops by 2.89% from the stationary state. These findings highlight the complex interplay between 1DOF vibration and heat transfer in triangular cylinder arrangements.
Enhanced afterglow blue emissions from atomically confined excitons in Pb(II)-doped cadmium-based metal halides
Authors: Ge Shuaigang , Wei Qilin , Huang Chaowei , Yang Chengzhi , Huang Kaihuang , Zou Bingsuo
Published: December 2024

All-inorganic metal halide perovskites possess significant potentiality in lighting, bioimaging, and optical anti-counterfeiting due to their exceptional and unique properties. However, the exploration of efficient, robustly stable, and long-persistent luminescent blue light-emitting materials poses huge challenges, especially in understanding their electronic structure and photophysical processes. In this work, high-purity Pb2+-doped CsCdCl3 crystals were synthesized using a straightforward hydrothermal method. Parts of Pb2+ ions replaced partial Cd2+ sites in the face-sharing octahedra and formed atomically confined excitons around the Pb(II) octahedra. This exciton could emit blue light (423 nm) at room temperature with an enhanced radiation transition probability at a nearly 90% quantum yield. The incorporation of Pb2+ and confined exciton formation not only shifted the emission color region from weak orange to strong blue but also exhibited intrinsic afterglow behavior as CsCdCl3 perovskite. The Raman spectra and TL spectra indicated their polaronic states corresponding to the A1g 244 cm−1 phonon mode coupling to electron, which dominated their afterglow processes in undoped and doped CsCdCl3. These findings could not only facilitate the understanding of atomically confined excitons around dopant ions as dominant emission centers to tune emission color in halide semiconductors, unveiling the nature of afterglow phenomena in this halide material, but could also find unique applications in optical devices.
PDMS—A simple and effective platform for determining Young's modulus of ultrathin 2D materials
Authors: de Avila Luana , Plutnar Jan , Sofer Zdenek , Neves Bernardo R. A.
Published: December 2024

Young's modulus plays a crucial role in determining the suitability of materials for various applications, including two-dimensional (2D) materials like graphene and transition metal dichalcogenides. Traditional indentation methods struggle with ultrathin 2D materials due to substrate effects. To overcome this, we propose using polydimethylsiloxane (PDMS) as a compliant substrate for atomic force microscopy force curves. This method, building on a 1950s analytical model, allows for accurate Young's modulus estimates by measuring flake thickness, applied force, and deformation. The results from our approach aligns well with existing literature for various 2D materials. PDMS, commonly used for mechanical exfoliation and transfer, offers an easily measurable Young's modulus, facilitating more efficient determinations. As the range of ultrathin materials grows, this platform enhances accessibility and efficiency in measuring Young's modulus, significantly contributing to the advancement of applications for these innovative materials.
Characteristic evolution and energy variation during the generation of water droplet
Authors: Pan Gaochao , Jiang Bingyou , Zheng Chunshan , Wang Xiao-Han , Zhang Yi , Yin Jianqiang , Zhu Hongzheng
Published: December 2024

Understanding water droplet characteristic is an important prerequisite for improving wet dust removal efficiency. Using the high-speed camera system, the process of water droplet generation under the different Ca2+ concentrations and injecting velocities was studied. The width and length of water droplet increased, whereas the ratio of droplet width and length decreased with generation time. The water droplet generation time decreased with injecting velocity increasing, whereas kept almost unchanged with Ca2+ concentration. The equivalent diameter of droplet decreased with injecting velocity, whereas presented first a slight decrease and then a slight increase with Ca2+ concentration. This result suggested that the injecting velocity effect was stronger than the Ca2+ effect on the water droplet generation time and size. Furthermore, the effective injecting force and capillary force were mainly forces to influence the droplet generation in force analysis. RF (ratio of capillary force and effective pressure force) was first used to evaluate the synergistic effect of capillary force and effective injecting force. The greater RF, the water droplet generation time was longer and water droplet diameter was larger. Furthermore, the relationship between surface energy per unit (E/S) of water droplet and RF was a negative correlation. Those results can provide valuable suggestions to the development theory of dust removal.
Numerical assessment of hydrodynamic behavior and energy dissipation during high-head Francis turbine shutdown
Authors: Sun Longgang , Wen Meng , Ding Xiaoyi , Wang Zhaoning , Guo Pengcheng
Published: December 2024

This paper examines the instability and energy dissipation of a high-head Francis turbine during shutdown using improved delayed detached eddy simulation, which involves linearly reducing the guide vane opening from 9.84° (best efficiency point) to 0.8° [Spin-No-Load (SNL)]. The results demonstrate a linear increase in water head, with hydraulic efficiency dropping from 93% to 30%. Pressure fluctuations in the vaneless space are mainly due to blade passing frequency and low-frequency components at SNL. High-amplitude pressure fluctuations occur below 37.4% opening in the draft tube, with the dominant frequency under 0.32 times the blade passing frequency. Three vortex structures are identified within the draft tube, a columnar vortex rope in the first stage, multiple helical vortex ropes in the second stage, and discrete vortex structures in the third stage. The most significant axial and radial velocity fluctuations are evident during the second and third stages. Turbulent kinetic energy generation and work done by Reynolds stress are the main sources of power loss. Energy dissipation primarily occurs at the outlet of the runner blades, while it corresponds to the positions of the vortex structures in the draft tube, suggesting that vortex flow structures are the primary mechanism of energy dissipation in the turbine. This study introduces a numerical shutdown model using the dynamic mesh technique, clarifies the relationship between guide vane opening and performance parameters, and identifies the three-stage vortex evolution and energy dissipation mechanisms, offering novel insights into transient instabilities in high-head Francis turbines.
Alignment impact of three unequal-sized square cylinders on the wake flow pattern and fluid forces
Authors: Fezai Salwa , Oueslati Fakher
Published: December 2024

A finite volume method and a full multi-grid technique are implemented to analyze the influence of alignment type of three unequal-sized square cylinders on the characteristics of wake flow pattern and fluid forces of the flow. Three-square cylinders with different dimensions C1, C2, and C3 are arranged for three main combinations, namely, in-line arrangement, side-by-side arrangement, and staggered arrangement. Analysis of flow patterns in different regimes is performed for the different arrangement type and for Reynolds number (Re) varied in range (1, 200). The second parameter is the arrangement type. The wake flow patterns including vortex shedding and the evolution of vortices, and force coefficients are predicted and analyzed for the three unequal-sized square arrangements in terms of streamlines, iso-vortices, and drag (CD) and lift (CL) coefficient evolutions for steady and unsteady regimes. Of great interest is the analysis of the combined effect of the Reynolds number and the adopted arrangements on the bifurcation emergence phenomenon and the CL and CD evolutions profiles while predicting the critical Reynolds number for each configuration. The numerical outcomes demonstrate that Re values and the different three-square cylinders arrangements have a prominent influence on the flow characteristics. The study reveals that the unsteady regime of the flow appears in the side-by-side arrangement at (Rec = 63), in the staggered arrangement (Rec = 76), and finally in the in-line arrangement for the specific value (Rec = 146). Furthermore, the effect of different arrangements on time averaged drag and lift is explored and discussed. It is found that the in-line alignment causes a strong reduction in drag values, while highest values are obtained for the side-by-side combination.
Comparison of chlorophyll content estimation using chlorophyll meters and leaf chloroplast pigments extracted from Eucalyptus urophylla and Khaya senegalensis seedlings
Authors: Silva Leandro Dias da , Bonfim Raul Antonio Araújo do , Barbosa Mateus Pires , Sá Milton Carriço , Oliveira Leonardo Santos de , Almeida Matheus Ferreira , Cairo Paulo Araquém Ramos
Published: December 2024

Context Estimating chloroplast pigment content by using chlorophyll meters is faster and cheaper than by using traditional pigment-extraction protocols. However, the reliability of chlorophyll meters requires a preliminary test of the relationship between the estimated and actual concentrations. Aims To establish an optimized protocol for extracting leaf chloroplast pigments from Eucalyptus urophylla and Khaya senegalensis seedlings. Moreover, we evaluated the relationship between chlorophyll-content estimation by using chlorophyll meters with the SPAD index by using SPAD-502 and with Falker chlorophyll index (FCI) by using ClorofiLOG, and that by using the optimal chloroplast pigment-extraction protocol. Methods The effectiveness of dimethylsulfoxide (DMSO) saturated with CaCO3 at 25°C and 65°C and 80% acetone (v/v) was assessed as extractors, by using different incubation times. Chlorophyll-content estimation was assessed using chlorophyll meters with the SPAD index by using SPAD-502 and with Falker chlorophyll index (FCI) by using ClorofiLOG. Key results For both Eucalyptus urophylla and Khaya senegalensis seedlings, the optimal protocol for extracting pigments from chloroplasts was incubation for 4 h by using DMSO saturated with CaCO3 at 65°C. Chlorophyll-content estimation using SPAD-502 and ClorofiLOG showed a strong positive correlation with measurements from the optimized pigment-extraction protocol. Furthermore, the regression equations of the chlorophyll-content estimation with chlorophyll meters allowed predicting the real content, because the values were very close to those measured using traditional extraction protocols. Conclusions The SPAD index and the FCI were reliable methods for estimating chlorophyll content in seedlings of both species. This could make measuring the chloroplast pigments faster and cheaper, especially regarding experimentation under field conditions.
Meeting standards: (Re)colonial and subversive potential of AI modification
Authors: Tankosić Ana , Milak Eldin , Steele Carly , Dobinson Toni
Published: December 2024

AI potential to recolonise language practices by reproducing existing marginalisations in novel ways has already
instilled fears of a ‘contemporary dystopia’ (Miras et al., 2022) — a space of cultural
and linguistic erasure. Accents represent a distinctive aspect of language practice associated with one’s sociocultural, and
ethno-racial characteristics. They account for one’s social identity, status, and proficiency (De Klerk & Bosch, 1995). This makes practices of artificially modifying accents particularly concerning, since
they play into the ‘zero’ accent ideology. As a result, any deviation from the norm is marked as abnormal or deficient, and in
need of, artificial correction. Using AI accent generators, therefore, has the capacity to further aggravate power inequalities
between the linguistically privileged and underprivileged, and to encourage changes in self-representation towards what is
perceived as the normative Standard.

Artificial modification of self to match a desired representation is not new, given the long-standing discussions
on digital image alterations and their negative relationships to self-perceived attractiveness (Ozimek et al., 2023). This conceptual paper explores the (re)colonial and subversive linguistic potential
of AI accent generators through the lens of the social tendency of individuals to strive to meet a given Standard. Using the
notion of ‘technologies of the self’ (Foucault, 1988), we draw a parallel between
self-perceived attractiveness of bodies and accents, to explain how artificial modifications do not straightforwardly support
diversities, but instead encourage ‘self-corrections’ in line with those standardized sets of features which seem to promise a
‘better’ socioeconomic and educational standing within neoliberal societies.
Immersion teachers’ perspective on grammar instruction in language immersion in Finland
Authors: Nyqvist Eeva-Liisa , Åberg Anne-Maj , Björklund Siv
Published: December 2024

Previous studies have shown that grammar is a central source of difficulty for immersion students and that their
teachers often lack knowledge of how to integrate linguistic aims with content teaching. This descriptive, enquiry-based study
reports on Finnish immersion teachers’ (n = 54) perspectives on grammar instruction in language immersion in
Finland — a theme under-researched in Finland thus far. Our online questionnaire consists of 18 questions comprising three
sections: the informants’ professional background, their views on the role of grammar in immersion and their views on correcting
grammatical inaccuracies. We analyse our data using quantitative and statistical methods (Pearson’s χ² as a statistical test). Our
findings show that most of our informants are experienced immersion teachers teaching languages to 13–15-year-old immersion
students. They do not prioritise grammatical accuracy when planning their instruction, although they consider it an important
aspect of second language proficiency. They also discuss grammatical accuracy to a greater extent with their students than with
their colleagues and are more tolerant of inaccuracies in spoken output. Implications are discussed regarding the necessity of
improving grammar instruction in immersion and immersion students’ grammatical accuracy.
Exact regular black hole solutions with de Sitter cores and Hagedorn fluid
Authors: Vertogradov Vitalii , Övgün Ali
Published: December 2024

In this paper, we present three exact solutions to the Einstein field equations, each illustrating different black hole models. The first solution introduces a black hole with a variable equation of state,

P
=
k
(
r
)
ρ

, which can represent both singular and regular black holes depending on the parameters M
0 and w
0. The second solution features a black hole with Hagedorn fluid, relevant to the late stages of black hole formation, and reveals similarities to the first solution by also describing both singular and regular black holes in a specific case. Furthermore, we investigate the shadows cast by these black hole solutions to constrain their parameters. Recognizing that real astrophysical black holes are dynamic, we developed a third, dynamical solution that addresses gravitational collapse and suggests the potential formation of naked singularities. This indicates that a black hole can transition from regular to singular and back to regular during its evolution.
Physics-guided machine-learning enhanced electrostatic actuated method for in-situ measurement of Young’s modulus
Authors: Liang Zhi-peng , Zhao Lin-Feng , Zhou Zai-Fa , Huang Qing-An
Published: December 2024

Young’s modulus of polysilicon is a vital mechanical parameter highly dependent on sample preparation and growth techniques. In-situ measurement of this property is essential for effective process control monitoring in microelectromechanical systems (MEMS) fabrication. In this work, an innovative electrostatic actuated method without pull-in instability for in-situ test is proposed. Based on the behavior simulated through finite element method, physics-guided neural networks, which integrate the advantages of both data science models and physics-guided ones, are utilized to extract the Young’s modulus and assess the probability of pull-in instability. Moreover, the performance of the structure is evaluated and optimized through Pareto analysis based on genetic algorithms. It is found that the mapping relationship between systematic parameters, excitation, and response of the structure can be modeled accurately by a physics-guided neural network, and the optimization of design facilities convenience of measurement. Moreover, the error of this method is within 5% under most circumstances, and the measured Young’s modulus through this method is close to that by nanoindentation test. This work explores potential applications of machine learning in MEMS design, testing, and optimization.
Investigating the excitation function of HBT radii for Lévy-stable sources
Authors: Csanád Máté , Kincses Dániel
Published: December 2024

Contemporary heavy-ion physics research aims to explore the phase diagram of strongly interacting matter and search for signs of the possible critical endpoint on the Quantum Chromodynamics phase diagram. Femtoscopy is among the important tools used for this endeavor; there have been indications that combinations of femtoscopic radii parameters (referred to as HBT radii for identical boson pairs) can be related to the system's emission duration. An apparent non-monotonic behavior in their excitation function thus might signal the location of the critical point. In this paper, we show that conclusions drawn from the results obtained with a Gaussian approximation for the pion source shape might be altered if one utilizes a more general Lévy-stable source description. We find that the characteristic size of the pion source function is strongly connected to the shape of the source and its possible power-law behavior. Taking this into account properly changes the observed behavior of the excitation function.
Effects of nonmagnetic Cr substitution for Mn on kagome magnet DyMn6Sn6
Authors: Liu Xiangqi , Tao Zicheng , Xia Wei , Guo Yanfeng
Published: December 2024

RMn6Sn6 (R = rare-earth) kagome magnets have been one of the research focuses in condensed matter physics, primarily due to their exotic physical properties rooted in the interplay between magnetism and nontrivial topological band structures. We reported herein the crystal growth of Cr substituted DyMn4Cr2Sn6 and investigations on their magnetotransport properties. It is unveiled that the Mn kagome layer is destroyed and the in-plane ferromagnetic exchange is consequently weakened by the substituted nonmagnetic Cr. Furthermore, the substitution apparently benefits reorientations of the Mn spins under external magnetic field. Besides, the Cr substitution results in a significantly enhanced large intrinsic anomalous Hall conductivity, reaching 600 S cm−1 at 240 K. The anomaly observed in the anomalous Hall conductivity as well as in the Hall coefficient might indicate a topological magnetic structure formed during the spin reorientation process. These findings pave the way for manipulating magnetism and electronic structures in magnetic kagome topological phases and offer a fertile ground for discovering exotic topological properties.
Design of a computer vision system for accurate measurement of mango skin defects by surface image slicing
Authors: Nguyen Phuoc-Loc , Dam Chi-Linh , Nguyen Xuan-Thinh , Tran Nhut-Thanh , Fukuzawa Masayuki , Nguyen Chi-Ngon , Nguyen Chanh-Nghiem
Published: December 2024

External features such as color, size, weight, and defect area are among the critical parameters for grading mangoes for export purposes. This paper describes a novel computer vision system (CVS) for the accurate measurement of mango skin defects. A novel algorithm called mango skin image slicing (MSIS) was developed to generate mango slices, each of which includes points of pseudo-equidistance from the camera to accurately calculate the defect area. Based on images captured from 360-degree views, defects on the entire mango surface can be detected. For the first time, a strategy for preventing multiple considerations of the same defects from 360-degree images was introduced based on MSIS. The experimental results revealed that recalculations of the same defects were avoided, and negligible minor defects were excluded, complying with the guidance of the mango exporting firms. The measurement accuracy was evaluated with artificial defects of 100 mm2, yielding a mean error of 6.0 ± 1.4 mm2, which was suitable for defect area measurement considering the mango grading standard. The CVS throughput of approximately 644 mangoes per hour was also a reasonable trade-off for the achieved accuracy and great potential of extending the CVS for more sophisticated classification of non-negligible defects based on the advantages of mango images captured at closer camera–object distances.
AlGaN/AlN/GaN MOS-HEMTs with biomolecule cavities: a promising approach for SARS-CoV-2 biosensors
Authors: Sufiyan Nudrat , Sharma Anup Kumar
Published: December 2024

In this work, AlGaN/AlN/GaN MOS-HEMTs were investigated with a biomolecule cavity between two oxide layers under the gate region to determine their sensitivity and viability as biosensors. The area between the two oxide layers located below the gate electrode was used to detect the SARS-CoV-2 virus through DNA proteins. Threshold voltage and drain current analyses were carried out by modulating the dielectric of DNA filled in the cavity region to simulate the presence of the virus. The sensitivity of the device was analysed using the ATLAS SILVACO simulation tool, focusing on various configurations. This includes the impact of AlGaN composition (both thickness and Al mole fraction) and cavity configuration (length and thickness of the cavity). The simulation results revealed that a device with a barrier layer thickness of 15 nm and Al mole fraction of 0.2 demonstrates a maximum threshold voltage sensitivity SV

th (%) of 86% and a drain current sensitivity SI

ds (%) of 75%. The device with a cavity length of 500 nm and cavity thickness 15 nm shows maximum sensitivity. This study suggests that the proposed structure has potential applications in the detection of SARS-COV-2 virus.
Preparation of quantum correlated states via fission of chirped vector solitons
Authors: Konyukhov Andrey I , Konyukhova Julia G , Melnikov Leonid A
Published: December 2024

We propose a new approach to generate quantum-correlated pulse pairs using fission of chirped Manakov solitons. Quantum correlations are studied using linearized quantum fluctuation theory. The fission of chirped solitons produces both intra-pulse and inter-pulse high-level correlations. We found that the collision of vector solitons induces nonzero correlations in orthogonal polarization components of the pulse field. The fission of solitons and subsequent collision of the resulting pulses allow a pulse train with complex correlation pattern to be produced. The generation of pulses with correlated quantum fluctuations offers the possibility of engineering new entangled sources for continuous-variable quantum communication and computation.
Excitation threshold of solitons in anharmonic chains
Authors: Ming 明 Yi 燚
Published: December 2024

This study numerically estimates the momentum threshold required to excite solitons in anharmonic chains. For both Fermi–Pasta–Ulam–Tsingou (FPUT)-αβ and FPUT-β chains, regardless of whether the interatomic interaction potential is symmetric, the required excitation momentum converges to the momentum of the soliton center (i.e., the peak momentum of the soliton) as the number of initially excited atoms increases. As the amplitude of the soliton approaches zero, the momentum threshold decreases to nearly zero, allowing soliton being excited with infinitesimal initial excitation momentum. These findings enhance the understanding of soliton dynamics and offer insights for optimizing soliton excitation methods, with potential applications in straintronics and nonlinear wave control technologies.
Study on the One-year Accuracy of Pulsar Time-scale
Authors: Wang Linlin , Zhang Zhehao , Zhao Chengshi , Li Zongke , Tong Minglei
Published: December 2024

Determining accurate pulsar timing model parameters is essential for establishing TT(PT), a realization of Terrestrial Time (TT) based on a pulsar timescale (PT). This study discusses the impact of different data spans on the accuracy of pulsar timing model parameters when determining pulsar timing model parameters. Using observations of PSR J0437-4715, J1909-3744, J1713+0747, and J1744-1134 from the second data release of the International Pulsar Timing Array (IPTA II, Version A), we compare the accuracy of the timing model parameters determined by these observations with different data spans. The results show for PSR J0437-4715, J1713+0747, and J1909-3744, the amplitude fluctuations of rotational frequency remain within 10−15, 10−14, and 10−14 Hz, respectively, when the data spans for determining pulsar timing model parameters exceed 13, 14, and 6 yr. Additionally, the one-year accuracy of TT(PT) is crucial for its application in timekeeping. By comparing the frequency deviations of TT(PT) relative to TT(BIPM) under both ideal (k

r
) and actual (k

p
) conditions across different data spans, we find that when the data span reaches the duration above, the accuracy of TT(PT) surpasses that of TT(TAI) under ideal conditions, slightly inferior under actual conditions. This suggests with improved observational technologies, the accuracy of TT(PT) can be further enhanced.
Cross-code comparison of the edge codes SOLPS-ITER, SOLEDGE2D and UEDGE in modelling a high-power neon-seeded scenario in the DTT
Authors: Moscheni M. , Wigram M. , Wu H. , Meineri C. , Carati C. , De Marchi E. , Greenwald M. , Innocente P. , LaBombard B. , Subba F. , Zanino R.
Published: December 2024

In this work, we cross-compare the state-of-the-art edge plasma codes SOLPS-ITER, SOLEDGE2D, and UEDGE in a reactor-relevant neon-seeded Divertor Tokamak Test scenario at nominal power, extending the simplified test-bed of Moscheni et al (2022 Nucl. Fusion
62 056009). Converged solutions targeting the same separatrix density and radiated power are obtained by adjusting the pumping albedo and the neon puffing rate. This higher-power scenario is generally characterised by substantial disagreement between the three codes, up to 78%–178% in peak heat fluxes. Discrepancies found in Moscheni et al (2022 Nucl. Fusion
62 056009) are indeed exacerbated, and new ones arise. Underlying causes include the over-penetration of neutrals implied by the unified ion-neutral temperature of UEDGE (observed in Moscheni et al (2022 Nucl. Fusion
62 056009)), here resulting in a 38%–114% over-estimation of core plasma densities. The particular set of EIRENE atomic-molecular reactions adopted is found to stiffly restrict the achievable code solutions, which results in the predicted effective charge Z
eff changing from

∼

5

to

∼

8

at the outer mid-plane separatrix. The strong link between Z
eff, main ion density and unified ion temperature emphasises the need of proper assessments of impurity cross-field transport, with its implications on core contamination and wall erosion. The advantages of extended plasma meshes are found to come with associated modelling intricacies, yet to be fully characterised but seemingly impacting on the activity around the secondary X-point of single-null magnetic topologies. An appreciable impurity particle imbalance, generated by the neon ion density floor, is noted—speculatively contributing to SOLEDGE2D’s different radiation emission distribution, and expected to be even more deleterious for high-Z impurities in all the codes. Potential drivers of further discrepancies are the different Braginskii formulations of collision times and momentum sources in presence of impurities, and the SOLPS-ITER extra terms gaining importance around the detachment front. Outstanding questions unanswered in this work prompt further investigations.
Interface engineering of van der Waals heterostructures towards energy-efficient quantum devices operating at high temperatures
Authors: Doan Manh-Ha , Bøggild Peter
Published: December 2024

Quantum devices, which rely on quantum mechanical effects for their operation, may offer advantages, such as reduced dimensions, increased speed, and energy efficiency, compared to conventional devices. However, quantum phenomena are typically observed only at cryogenic temperatures, which limits their practical applications. Two-dimensional materials and their van der Waals (vdW) heterostructures provide a promising platform for high-temperature quantum devices owing to their strong Coulomb interactions and/or spin–orbit coupling. In this review, we summarise recent research on emergent quantum phenomena in vdW heterostructures based on interlayer tunnelling and the coupling of charged particles and spins, including negative differential resistance, Josephson tunnelling, exciton condensation, and topological superconductivity. These are the underlying mechanisms of energy-efficient devices, including tunnel field-effect transistors, topological/superconducting transistors, and quantum computers. The natural homojunction within vdW layered materials offers clean interfaces and perfectly aligned structures for enhanced interlayer coupling. Twisted bilayers with small angles may also give rise to novel quantum effects. In addition, we highlight several proposed structures for achieving high-temperature Majorana zero modes, which are critical elements of topological quantum computing. This review is helpful for researchers working on interface engineering of vdW heterostructures towards energy-efficient quantum devices operating above liquid nitrogen temperature.
Conditions for a quadratic quantum speedup in nonlinear transforms with applications to energy contract pricing
Authors: Agliardi Gabriele , O’Meara Corey , Yogaraj Kavitha , Ghosh Kumar , Sabino Piergiacomo , Fernández-Campoamor Marina , Cortiana Giorgio , Bernabé-Moreno Juan , Tacchino Francesco , Mezzacapo Antonio , Shehab Omar
Published: December 2024

Computing nonlinear functions over multilinear forms is a general problem with applications in risk analysis. For instance in the domain of energy economics, accurate and timely risk management demands for efficient simulation of millions of scenarios, largely benefiting from computational speedups. We develop a novel hybrid quantum–classical algorithm based on polynomial approximation of nonlinear functions, computed through Quantum Hadamard Products, and we rigorously assess the conditions for its end-to-end speedup for different implementation variants against classical algorithms. In our setting, a quadratic quantum speedup, up to polylogarithmic factors, can be proven only when forms are bilinear and approximating polynomials have second degree, if efficient loading unitaries are available for the input data sets. We also enhance the bidirectional encoding, that allows tuning the balance between circuit depth and width, proposing an improved version that can be exploited for the calculation of inner products. Lastly, we exploit the dynamic circuit capabilities, recently introduced on IBM Quantum devices, to reduce the average depth of the Quantum Hadamard Product circuit. A proof of principle is implemented and validated on IBM Quantum systems.
Efficient quantum algorithm for lattice protein folding
Authors: Wang Youle , Zhou Xiangzhen
Published: December 2024

Predicting a protein’s three-dimensional structure from its primary amino acid sequence constitutes the protein folding problem, a pivotal challenge within computational biology. This task has been identified as a fitting domain for applying quantum annealing, an algorithmic technique posited to be faster than its classical counterparts. Nevertheless, the utility of quantum annealing is intrinsically contingent upon the spectral gap associated with the Hamiltonian of lattice proteins. This critical dependence introduces a limitation to the efficacy of these techniques, particularly in the context of simulating the intricate folding processes of proteins. In this paper, we address lattice protein folding as a polynomial unconstrained binary optimization problem, devising a hybrid quantum–classical algorithm to determine the minimum energy conformation effectively. Our method is distinguished by its logarithmic scaling with the spectral gap, conferring a significant edge over the conventional quantum annealing algorithms. The present findings indicate that the folding of lattice proteins can be achieved with a resource consumption that is polynomial in the lattice protein length, provided an ansatz state that encodes the target conformation is utilized. We also provide a simple and scalable method for preparing such states and further explore the adaptation of our method for extension to off-lattice protein models. This work paves a new avenue for surmounting complex computational biology problems via the utilization of quantum computers.
A comprehensive review and future perspectives of simulation approaches in wire arc additive manufacturing (WAAM)
Authors: Chen Zhonghao , Yuan Lei , Pan Zengxi , Zhu Hongtao , Ma Ninshu , Ding Donghong , Li Huijun
Published: December 2024

Wire arc additive manufacturing (WAAM) has emerged as a promising technique for producing large-scale metal components, favoured by high deposition rates, flexibility and low cost. Despite its potential, the complexity of WAAM processes, which involves intricate thermal dynamics, phase transitions, and metallurgical, mechanical, and chemical interactions, presents considerable challenges in final product qualities. Simulation technologies in WAAM have proven invaluable, providing accurate predictions in key areas such as material properties, defect identification, deposit morphology, and residual stress. These predictions play a critical role in optimising manufacturing strategies for the final product. This paper provides a comprehensive review of the simulation techniques applied in WAAM, tracing developments from 2013 to 2023. Initially, it analyses the current challenges faced by simulation methods in three main areas. Subsequently, the review explores the current modelling approaches and the applications of these simulations. Following this, the paper discusses the present state of WAAM simulation, identifying specific issues inherent to WAAM simulation itself. Finally, through a thorough review of existing literature and related analysis, the paper offers future perspectives on potential advancements in WAAM simulation strategies.
A novel hybrid framework for heterogeneous measurement data prediction of cable-stayed bridges using ACMD-PE-BiLSTM
Authors: Zhou Zhenwei , Xiao Liang , Zhuang Haiyang , Zhang Guangcai , Gao Shuai
Published: December 2024

Bridge heterogeneous measurement data prediction is a crucial aspect of structural analysis of bridge engineering, which serves as an important reference for the early warning and decision-making of the bridges. However, the nonlinearity and nonstationarity of the measurement data are common occurrences in daily monitoring operations, which affects the accuracy of the prediction of bridge health. In this context, this paper proposes a hybrid data-driven deep learning approach for predicting bridge multi-source heterogeneous data to tackle the challenges posed by the complexity and nonstationarity of cable-stayed bridge monitoring data and enhance the accuracy and efficiency of predicting measurement data. This approach leverages adaptive chirp mode decomposition (ACMD), permutation entropy (PE), and Bi-directional long short-term memory (BiLSTM). Firstly, the ACMD algorithm decomposes the bridge monitoring data into a discrete number of intrinsic mode functions (IMFs) to produce clearer signals. Then, the PE algorithm is applied to each IMF to optimize the number of IMFs and construct the new components. Finally, a BiLSTM network is present for each component to establish the prediction model, and the final prediction results are obtained by synthesizing the predictions. The effectiveness and feasibility of the proposed method are extensively evaluated using measured wind speed, displacement, and acceleration data from a cable-stayed bridge. Evaluation indicators are used to evaluate the performance, and a comparative analysis with other benchmark models is further conducted to systematically validate the reliability of the proposed approach. The proposed prediction method offers several advantages, with its stability and accuracy particularly noteworthy. The results suggest that the proposed method is superior to the compared models regarding cable-stayed bridge heterogeneous measurement data and can provide reliable results for real-world bridge engineering.
Synthetic graphs for link prediction benchmarking
Authors: Vlaskin Alexey , Altmann Eduardo G
Published: December 2024

Predicting missing links in complex networks requires algorithms that are able to explore statistical regularities in the existing data. Here we investigate the interplay between algorithm efficiency and network structures through the introduction of suitably-designed synthetic graphs. We propose a family of random graphs that incorporates both micro-scale motifs and meso-scale communities, two ubiquitous structures in complex networks. A key contribution is the derivation of theoretical upper bounds for link prediction performance in our synthetic graphs, allowing us to estimate the predictability of the task and obtain an improved assessment of the performance of any method. Our results on the performance of classical methods (e.g. Stochastic Block Models, Node2Vec, GraphSage) show that the performance of all methods correlate with the theoretical predictability, that no single method is universally superior, and that each of the methods exploit different characteristics known to exist in large classes of networks. Our findings underline the need for careful consideration of graph structure when selecting a link prediction method and emphasize the value of comparing performance against synthetic benchmarks. We provide open-source code for generating these synthetic graphs, enabling further research on link prediction methods.
Automation of quantum dot measurement analysis via explainable machine learning
Authors: Schug Daniel , Kovach Tyler J , Wolfe M A , Benson Jared , Park Sanghyeok , Dodson J P , Corrigan J , Eriksson M A , Zwolak Justyna P
Published: December 2024

The rapid development of quantum dot (QD) devices for quantum computing has necessitated more efficient and automated methods for device characterization and tuning. Many of the measurements acquired during the tuning process come in the form of images that need to be properly analyzed to guide the subsequent tuning steps. By design, features present in such images capture certain behaviors or states of the measured QD devices. When considered carefully, such features can aid the control and calibration of QD devices. An important example of such images are so-called triangle plots, which visually represent current flow and reveal characteristics important for QD device calibration. While image-based classification tools, such as convolutional neural networks (CNNs), can be used to verify whether a given measurement is good and thus warrants the initiation of the next phase of tuning, they do not provide any insights into how the device should be adjusted in the case of bad images. This is because CNNs sacrifice prediction and model intelligibility for high accuracy. To ameliorate this trade-off, a recent study introduced an image vectorization approach that relies on the Gabor wavelet transform (Schug et al 2024 Proc. XAI4Sci: Explainable Machine Learning for Sciences Workshop (AAAI 2024) (Vancouver, Canada) pp 1–6). Here we propose an alternative vectorization method that involves mathematical modeling of synthetic triangles to mimic the experimental data. Using explainable boosting machines, we show that this new method offers superior explainability of model prediction without sacrificing accuracy. This work demonstrates the feasibility and advantages of applying explainable machine learning techniques to the analysis of QD measurements, paving the way for further advances in automated and transparent QD device tuning.