Chemical Physics
Modeling formation and transport of clusters at high temperature and pressure gradients by implying partial chemical equilibrium
Eugene V. Stepanov and Alexander F. Gutsol
A theoretical approach to describing transport of an entire ensemble of clusters with different sizes as a single species in gas has been developed. The major assumption is an existence of local partial chemical
equilibrium between the clusters. It is shown that thermal
diffusion emerges in the collective description as a significant factor even if it is negligible when transport of the original molecular species is considered. Analytical expressions for the effective
diffusion and thermal
diffusion coefficients at temperature, pressure, and chemical composition gradients have been derived. The theory has been applied to a technology of H2S conversion in a centrifugal
plasma-chemical reactor and has made it possible to account for sulfur clusters in numerical process modeling.
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Plasma Physics
Cold atmospheric microplasma jet-water interactions: physicochemical analysis and growth effects in flowering plants
Syon Bhattacharjee, Deepika Behmani and Sudeep Bhattacharjee
Cold atmospheric pressure
plasma jets (APPJs) are non-
equilibrium plasmas, that are capable of producing reactive oxygen and nitrogen species (RONS) at near-room temperature. Their interaction with water leads to the formation of
plasma-activated water (PAW), whose chemical activity depends on discharge conditions. In this work, a helium-air (14:1) micro-
plasma jet operated in a ring-to-ring electrode configuration is used to generate PAW and study its influence on the growth of Chrysanthemum saplings. Optical emission spectroscopy (OES) confirms the presence of $N_2$ bands and He lines, with the He-air mixture providing more chemically active discharge (in terms of favoring the generation of nitrates in PAW) as compared to pure helium. The physicochemical characteristics of PAW such as pH, electrical conductivity (EC), oxidation-reduction potential (ORP), and total dissolved solids (TDS) are analyzed as a function of
plasma treatment time and water volume. The optimum condition for PAW generation is found to be 12 ml of de-ionized (DI) water treated for 40 minutes, which yields the highest ORP and nitrate concentration with a reduced pH. Comparative growth experiments over two weeks show that PAW-treated Chrysanthemum saplings exhibit significantly greater height (10.2 cm) and soil fertility (2580 $\mu$S/cm) than those watered with same amount of DI water or tap water. The results highlight the potential of PAW for sustainable enhancement of growth of flowering plants.
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Instrumentation and Detectors
Data sorting modes of phoswich detector array
R. Li, D. Verney, C. Delafosse et al. (+31 more)
The different data-sorting modes of the phoswich detector array PARIS used for detecting high-energy (4$-$10 MeV) $\gamma$ rays are investigated. The characteristics including time resolution, energy resolution and detection efficiency under various modes are studied. The present study shows that PARIS has capabilities of rejecting escape and pileup events when used for decay spectroscopy. Notably, the methods presented in this work refer specifically to the $\beta$-decay experiment of $^{80g+m}$Ga conducted with three PARIS clusters comprising 27 phoswich detectors, rather than to a general report on the PARIS array or its overall performance for in-beam spectroscopy. Compared with the 2"$\times$2"$\times$2" LaBr$_3$(Ce) detector (Ciemała et al., 2009), even in individual mode, PARIS provides significant suppression of single- and double-escape peaks and reduces background via vetoing function of the outer-volume NaI(Tl)
crystals. In contrast to the common approach of adding back the energies in LaBr$_3$(Ce) and NaI(Tl) to increase the detection efficiency of the full-energy peak, using NaI(Tl) as a veto shield provides a superior trade-off for applications where spectral purity is essential. Employing add-back analysis within each cluster of nine phoswiches or between all phoswiches could enhance full-energy peak efficiency and further suppress escape peaks and background. Applying a multiplicity condition provides a further suppression but simultaneously lowers the statistics of full-energy peaks.
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All authors R. Li, D. Verney, C. Delafosse, M. N. Harakeh, A. Maj, F. Didierjean, L. Al Ayoubi, H. Al Falou, P. Bednarczyk, G. Benzoni, F. Le Blanc, V. Bozkurt, M. Ciemała, F. C. L. Crespi, I. Deloncle, C. Gaulard, A. Gottardo, V. Guadilla, J. Guillot, K. Hadyńska-Klek, F. Ibrahim, N. Jovancevic, A. Kankainen, M. Kmiecik, M. Lebois, T. Martínez, P. Napiorkowski, B. Roussiere, Yu. G. Sobolev, M. Stanoiu, I. Stefan, S. Stukalov, D. Thisse, G. Tocabens
Instrumentation and Detectors · Cross-listed from cs.LG
Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging
Aaron Wang, Zihan Zhao, Subash Katel et al. (+6 more)
Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughput environments, such as the CERN LHC. The quadratic complexity of
transformer models demands substantial resources and increases latency during inference. In order to address these issues, we introduce the Spatially Aware Linear
Transformer (SAL-T), a physics-inspired enhancement of the linformer architecture that maintains linear
attention. Our method incorporates spatially aware partitioning of particles based on kinematic features, thereby computing
attention between regions of physical significance. Additionally, we employ convolutional layers to capture local correlations, informed by insights from jet physics. In addition to outperforming the standard linformer in jet classification tasks, SAL-T also achieves classification results comparable to full-
attention transformers, while using considerably fewer resources with lower latency during inference. Experiments on a generic point cloud classification
dataset (ModelNet10) further confirm this trend. Our code is available at https://github.com/aaronw5/SAL-T4HEP.
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All authors Aaron Wang, Zihan Zhao, Subash Katel, Vivekanand Gyanchand Sahu, Elham E Khoda, Abhijith Gandrakota, Jennifer Ngadiuba, Richard Cavanaugh, Javier Duarte
Physics and Society
Matchings Under Biased and Correlated Evaluations
Amit Kumar and Nisheeth K. Vishnoi
We study a two-institution stable matching model in which candidates from two distinct groups are evaluated using partially correlated signals that are group-biased. This extends prior work (which assumes institutions evaluate candidates in an identical manner) to a more realistic setting in which institutions rely on overlapping, but independently processed, criteria. These evaluations could consist of a variety of informative tools such as standardized tests, shared recommendation systems, or AI-based assessments with local noise. Two key parameters govern evaluations: the bias parameter $\beta \in (0,1]$, which models systematic disadvantage faced by one group, and the correlation parameter $\gamma \in [0,1]$, which captures the
alignment between institutional rankings. We study the representation ratio, i.e., the ratio of disadvantaged to advantaged candidates selected by the matching process in this setting. Focusing on a regime in which all candidates prefer the same institution, we characterize the large-
market equilibrium and derive a closed-form expression for the resulting representation ratio. Prior work shows that when $\gamma = 1$, this ratio scales linearly with $\beta$. In contrast, we show that the representation ratio increases nonlinearly with $\gamma$ and even modest losses in correlation can cause sharp drops in the representation ratio. Our analysis identifies critical $\gamma$-thresholds where institutional selection behavior undergoes discrete transitions, and reveals structural conditions under which evaluator
alignment or bias mitigation are most effective. Finally, we show how this framework and results enable interventions for
fairness-aware design in decentralized selection systems.
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Fluid Dynamics · Cross-listed from cond-mat.soft
Reciprocal swimming in granular media: the role of jamming and swimmer inertia
Amir Nazemi and Hongyi Xiao
We use particle simulations to reveal two distinct propulsion mechanisms for a scallop-like swimmer to propel itself in granular media by reciprocally flapping its wings. Based on the discrete element method, we examine the structure, kinematics, and contact forces of particles near the swimmer to quantify how jamming manifests as stagnant zones near the swimmer in a frictional granular medium, which are less intense during the opening stroke than the closing. This broken
symmetry is quantified by the difference in the number of strong particle contact forces formed during opening and closing, which shows a linear relation with the swimmer's net displacement across various swimmer and medium configurations, all favoring the opening stroke. We identify a secondary propulsion mechanism in a dynamic regime with significant swimmer inertia, as the flapping period approaches the coasting time for a moving swimmer to come to rest under the medium resistance. In this case, the swimmer's net displacement is correlated to the ratio between these two time scales, and the swimming direction favors the closing stroke due to the smaller medium resistance as the swimmer coasts with closed wings.
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Computational Physics · Cross-listed from math.NA
Preconditioning and Reduced-Order Modeling of Navier-Stokes Equations in Complex Porous Microstructures
Kangan Li and Yashar Mehmani
We aim to solve the incompressible Navier-Stokes equations within the complex microstructure of a porous material. Discretizing the equations on a fine grid using a staggered (e.g., marker-and-
cell, mixed FEM) scheme results in a nonlinear residual. Adopting the Newton method, a linear system must be solved at each iteration, which is large, ill-conditioned, and has a saddle-point structure. This demands an iterative (e.g., Krylov) solver, that requires preconditioning to ensure rapid convergence. We propose two monolithic algebraic preconditioners, $a\mathrm{PLMM_{NS}}$ and $a\mathrm{PNM_{NS}}$, that are generalizations of previously proposed forms by the authors for the Stokes equations ($a\mathrm{PLMM_{S}}$ and $a\mathrm{PNM_{S}}$). The former is based on the pore-level multiscale method (PLMM) and the latter on the pore network model (PNM), both successful approximate solvers. We also formulate faster-converging
geometric preconditioners $g\mathrm{PLMM}$ and $g\mathrm{PNM}$, which impose $\partial_n\boldsymbol{u}\!=\!0$ (zero normal-gradient of velocity) exactly at subdomain interfaces. Finally, we propose an accurate coarse-scale solver for the steady-state Navier-Stokes equations based on $g\mathrm{PLMM}$, capable of computing approximate solutions orders of magnitude faster. We
benchmark our preconditioners against state-of-the-art block preconditioners and show $g\mathrm{PLMM}$ is the best-performing one, followed closely by $a\mathrm{PLMM_{S}}$ for steady-state flow and $a\mathrm{PLMM_{NS}}$ for transient flow. All preconditioners can be built and applied on parallel machines.
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Optics
Semiconductor Wannier equations: a real-time, real-space approach to the nonlinear optical response in crystals (ATATA)
Eduardo B. Molinero, Bruno Amorim, Misha Ivanov et al. (+6 more)
We develop the
semiconductor Wannier equations (SWEs), a real-time, real-space formulation of ultrafast light-matter dynamics in
crystals, by deriving the equations of motion for the electronic reduced density
matrix in a localized Wannier basis. Working in real space removes the structure-gauge ambiguities that hinder reciprocal-space
semiconductor Bloch equations. Electron–electron interactions are included at the time-dependent Hartree plus static screened-exchange (TD-HSEX) level. Decoherence is modeled with three complementary channels: pure dephasing, population relaxation, and distance-dependent real-space dephasing; providing physically grounded damping for strong-field phenomena such as high-harmonic generation. Conceptually, the SWEs bridge real-space semiclassical intuition with many-body solid-state optics, offering a numerically robust and gauge-clean alternative to reciprocal-space approaches for nonlinear optical response and attosecond spectroscopy in solids.
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All authors Eduardo B. Molinero, Bruno Amorim, Misha Ivanov, Graham G. Brown, Giovanni Cistaro, João M. Viana Parente Lopes, Álvaro Jiménez-Galán, Pablo San-Jose, Rui E. F. Silva
Plasma Physics · Cross-listed from astro-ph.SR
Quasi-Biennial Oscillations and Rieger-type Periodicities in a Babcock-Leighton Solar Dynamo
Pawan Kumar, Belur Ravindra, Partha Chowdhury et al. (+1 more)
The Sun's
magnetic field shows the 11-year
solar cycle and shorter periodicities, popularly known as the quasi-biennial oscillations (QBOs) and Rieger-type periods, or “season of the Sun." Although several theories have been proposed to explain the origin of QBOs and Rieger-type periods, no single theory has widespread acceptance. We explore whether the \bl\ dynamo can produce Rieger-type periodicity and QBOs and investigate their underlying physical mechanisms. We use the observationally guided three-dimensional kinematic \bl\ dynamo model, which has emerged as a successful model for reproducing many characteristic features of the
solar cycle. We use Morlet wavelet and global wavelet power spectrum techniques to analyze the data obtained from the model. In our model, we report QBOs and Rieger-type periods for the first time. Further, we investigate the individual \bl\ parameters (fluctuations in flux, latitude, time delay and tilt scatter) role in the occurrence of QBOs and Rieger-type periods. We find that while fluctuations in the individual parameters of the \bl\ process can produce QBOs and Rieger-type periodicity, their occurrence probability is enhanced when we consider combined fluctuations of all parameters in the \bl\ process. Finally, we find that with the increase of dynamo supercriticality, the model tends to suppress the generation of Rieger-type periodicity. Thus, this result supports earlier studies that suggest the
solar dynamo is not highly supercritical.
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All authors Pawan Kumar, Belur Ravindra, Partha Chowdhury, Bidya Binay Karak
Fluid Dynamics
Mirror states enable lower viscosity lattice gases
Noah Seekins and Alexander J. Wagner
We developed a method for significantly lowering the viscosity achievable for a hydrodynamic
lattice gas method. The key advance is the derivation of a mirror state that allows for a reduction of viscosity by more than an order of magnitude over existing
lattice gas methods.
Computational Physics · Cross-listed from eess.SY
High-Performance Rotor Cooling with Ducted Liquid in Completely Cold-Formed Modular Motor Shaft
Rezvan Alamian, Sören Müller, Uwe Steinmetz et al. (+2 more)
This paper suggests a novel rotor-cooling shaft concept for high-performance electric motors that increases the effectiveness of cooling and is yet simple and cost-effective to manufacture. We investigate the thermal performance of four shaft geometries for rotor cooling in automotive applications. The proposed tooth-guided
liquid-cooling shaft design aims to solve the high churning loss of conventional cooled rotor shafts due to internal
vortex formation and their still limited heat transfer. Therefore, we optimize heat transfer efficiency and pressure management by incorporating cold-formed internal channels that restrict
vortex formation beyond a degree that improves heat transfer. We evaluated key performance metrics, including heat transfer rate, outlet temperature, pressure drop, and velocity profiles, under varying rotational speeds, inlet flow rates, and coolant temperatures. Computational fluid analysis demonstrates that the tooth-guided design outperforms conventional hollow shafts and achieves up to 110% higher cooling efficiency at low rotational speeds, while it maintains comparable pressure levels. These findings provide practical insight into geometry-driven thermal optimization and offer a path toward improving the performance and durability of electric motors.
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All authors Rezvan Alamian, Sören Müller, Uwe Steinmetz, Christian Henrich, Stefan Goetz
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Highly Tunable Phonon Polaritons via Metal Intercalation
Mariia Stepanova, Minh Ngo, Mashnoon Alam Sakib et al. (+5 more)
Phonon polaritons in van der Waals
crystals offer mid-infrared light confinement deep below the diffraction limit, making them promising for nanophotonics applications. However, the practical use of
phonon polaritons remains limited, in part due to the lack of precise control over the
phonon polariton dispersion, as
crystal lattice vibrations are often inert to external stimuli. Here, we address this challenge by zerovalent metal intercalation of $\alpha$-MoO$_3$. Photo-induced force microscopy shows that introducing tin into the van der Waals gap modulates the
phonon polariton dispersion by up to $38.5\pm0.5\%$, which is the highest amount of tunability among non-mechanical modulation approaches, to the best of our knowledge. Intercalation with various metal species preserves the
phonon polariton lifetimes, while modulating the dielectric permittivity in agreement with the density functional theory and analytical calculations. Our results establish metal intercalation as a practical route to reconfigurable mid-infrared nanophotonics.
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All authors Mariia Stepanova, Minh Ngo, Mashnoon Alam Sakib, Wills Harris, Joshua Bocanegra, Ruqian Wu, Kristie J. Koski, Maxim R. Shcherbakov
Computational Physics · Cross-listed from cond-mat.mtrl-sci
First-principles study of phase stability and magnetic properties of B2 AlCr, AlMn, AlFe, AlCo and AlNi aluminides
Haireguli Aihemaiti, Esmat Dastanpour, Anders Bergman et al. (+1 more)
Using ab initio Density Functional Theory (DFT) calculations, we investigate the electronic structure, phase stability, and
magnetic properties of equiatomic binary
alloys between Al and 3d
magnetic transition elements (Cr, Mn, Fe, Co, and Ni). Thermodynamically, all five binary aluminides are more stable in the ordered B2 phase than in the disordered body centered cubic phase, and Co is found to be the strongest B2 forming element with Al. The AlCo and AlNi compounds with B2 structure are verified to be non-
magnetic, whereas AlFe turns out to be weakly
magnetic, which is consistent with other DFT calculations employing similar exchange-correlation approximations.
Magnetic simulations based on the Heisenberg
Hamiltonian predict an
antiferromagnetic ground state for the hypothetical B2 AlCr, which is also confirmed by direct DFT calculations. Doping AlCr with Co leads to an
antiferromagnetic to
ferromagnetic transition, where ferromagnetism is to a large extent attributed to Cr atoms. The phase stability and
magnetic trends are explained using electronic structure arguments. The present findings contribute to a deeper understanding of the phase stability and
magnetic properties of AlX binary
alloys, providing insights into the formation mechanisms of the B2 structure with 3d
magnetic transition metals.
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All authors Haireguli Aihemaiti, Esmat Dastanpour, Anders Bergman, Levente Vitos
Chemical Physics
Tracking Microhydration of the NaCl Rocksalt Molecule in Helium Nanodroplets by Penning Ionization Electron Spectroscopy
Ltaief Ben Ltaief, Keshav Sishodia, Robert Richter et al. (+6 more)
The microhydration of rock salt (NaCl) molecules was investigated using high-resolution Penning ionization electron spectroscopy (PIES) in helium nanodroplets. Although model calculations predict that NaCl molecules are fully submerged inside the droplets, PIES of NaCl are highly resolved, in stark contrast to other molecular species. Co-doping the droplets with a controlled number of $n=5$–10 water molecules leads to efficient quenching of the NaCl Penning ionization signal and to its full suppression for $n\gtrsim 30$. Accompanying density-functional theory (DFT) and force field calculations reveal a transition from contact ion pair structures to solvent-separated ion pairs at $n=12$–15. However, it takes $n\approx 17$ water molecules to form a complete solvation shell around the Cl$^-$ anion and as many as $n\approx 34$ to fully hydrate the Na$^+$ cation, thus the entire NaCl molecule, which rationalizes the experimental findings.
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All authors Ltaief Ben Ltaief, Keshav Sishodia, Robert Richter, Martí Pi, Manuel Barranco, Jussi Eloranta, Sivarama Krishnan, Florent Calvo, Marcel Mudrich
Computational Physics · Cross-listed from cs.SE
FeaGPT: an End-to-End agentic-AI for Finite Element Analysis
Yupeng Qi, Ran Xu and Xu Chu
Large
language models (LLMs) are establishing new paradigms for engineering applications by enabling natural
language control of complex computational workflows. This paper introduces FeaGPT, the first framework to achieve complete geometry-mesh-simulation workflows through conversational interfaces. Unlike existing tools that automate individual FEA components, FeaGPT implements a fully integrated Geometry-Mesh-Simulation-Analysis (GMSA) pipeline that transforms engineering specifications into validated computational results without manual intervention. The system interprets engineering intent, automatically generates physics-aware adaptive meshes, configures complete FEA simulations with proper boundary condition inference, and performs multi-objective analysis through closed-loop iteration. Experimental validation confirms complete end-to-end automation capability. Industrial turbocharger cases (7-blade compressor and 12-blade turbine at \SI{110000}{rpm}) demonstrate the system successfully transforms natural
language specifications into validated CalculiX simulations, producing physically realistic results for rotating machinery analysis. Additional validation through 432 NACA airfoil configurations confirms scalability for parametric design exploration. These results demonstrate that natural
language interfaces can effectively democratize access to advanced computational engineering tools while preserving analytical rigor.
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Medical Physics
Cross-Section-Based Scaling Method for Material-Specific Cluster Dose Calculations – A Proof of Concept
Miriam Schwarze, Hui Khee Looe, Björn Poppe et al. (+2 more)
Cross-section data unavailability for non-water materials in track structure simulation software necessitates nanodosimetric quantity transformation from water to other materials. Cluster dose calculation transformation initially employed mass-density-based scaling - an approach resulting in a physically unrealistic material-independence of the cluster dose equation. This study introduces an alternative scaling method based on material-specific ionization cross-sections. The mean free path ratio of the materials for both the primary particles of the track structure simulation and for the secondary electrons served as the scaling factor. The approach was demonstrated through a cluster dose calculation for a carbon ion beam in a realistic head geometry and compared to the previous scaling method. The proposed cross-section-based scaling method resulted in a physically expected increase in cluster dose values for denser materials, which was not visible in the original scaling approach. The introduced scaling approach can be used to determine cluster dose distributions in heterogeneous geometries, a fundamental requirement for its integration into radiotherapy treatment planning frameworks.
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All authors Miriam Schwarze, Hui Khee Looe, Björn Poppe, Leo Thomas, Hans Rabus
Medical Physics
Technical assessment of a novel vertical CT system for upright radiotherapy simulation and treatment planning
Jordan M. Slagowski, Yuhao Yan, Jessica R. Miller et al. (+4 more)
Purpose: To characterize image quality, imaging dose, and dose calculation accuracy for an upright CT scanner with a six-degree-of-freedom patient positioning system. Methods: Imaging dose (CTDIvol) was measured at 120 kVp and 200 mAs. Image quality was evaluated using an ACR-464 phantom. Mean CT number accuracy was assessed within inserts of known material and uniformity as the difference in values at the center and periphery of uniform phantoms. High-contrast resolution was assessed by visible line pairs and modulation transfer function (MTF). Low-contrast performance was quantified by contrast-to-noise-ratio (CNR). Spatial integrity was evaluated between fiducials 100 mm apart. Hounsfield unit to mass density and stopping-power-ratio calibrations were performed.
Proton and
photon treatment plans were optimized on upright CT scans of a thorax phantom in heterogenous and homogeneous regions. Dose was forward computed on a registered recumbent CT scan and agreement evaluated using 3D gamma analysis. Results: CT imaging dose (CTDIvol) was 23.5 mGy for the 16 cm head phantom and 10.1 mGy for the 32 cm body phantom. Mean CT numbers (HU) were within the expected range for water (1.7) and acrylic (120.8). CT numbers were slightly (5-27 HU) out-of-range for air (-950.4), polyethylene (-78.8), and bone (823.0). Image uniformity was 20.2 HU and 35.0 HU for 20 cm and 48 cm diameter phantoms, respectively. Eight high-contrast line pairs were visualized. The MTF equaled 4.4 cm-1 at 50% and 7.1 cm-1 at 10%. The median CNR was 0.93, below the 1.0 tolerance. Spatial integrity was 0.36 mm. Gamma pass rates were 99.8% for
photon and 90.6% for
proton plans with 1%/1mm criteria, and greater than or equal to 98.0% for all plans with 3%/2mm criteria. Conclusion: Upright CT image quality and dose calculation accuracy are acceptable for
photon and
proton radiotherapy.
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All authors Jordan M. Slagowski, Yuhao Yan, Jessica R. Miller, John W. Hayes, Carson A. Hoffman, Minglei Kang, Carri K. Glide-Hurst
Computational Physics · Cross-listed from cond-mat.mtrl-sci
Haireguli Aihemaiti, Esmat Dastanpour, Shashank Chaturvedi et al. (+3 more)
Using Density Functional Theory (DFT) calculations and Monte-Carlo (MC) simulations, we investigate the recently reported
magnetic transition in B2 Al-Cr-Co
alloys. The Cr sublattice is alloyed with different amounts of Co in the
antiferromagnetic (AFM) B2 AlCr binary
alloy and the resulting exchange interactions are analyzed within the Heisenberg
Hamiltonian framework. DFT results reveal that at low Co concentrations the system favors the AFM order, while at high Co contents a transition to the
ferromagnetic (FM) state is observed. Within the FM stability field, the Curie temperature (TC), obtained within the mean-field approximation, is below ~160 K and decreases with Co concentration. The calculated exchange parameters evolve systematically with Co content, and the trends are consistent with the DFT total energies. The
magnetic configurations obtained from MC simulations follow the DFT results at low Cr levels but predict a
spin-glass behavior for
alloys containing more than 40 at.% Co on Cr sublattice. These findings provide a fundamental understanding of how the chemistry-driven changes in exchange interactions affect magnetism in the B2 Al-Cr-Co
alloys.
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All authors Haireguli Aihemaiti, Esmat Dastanpour, Shashank Chaturvedi, Shuo Huang, Anders Bergman, Levente Vitos
Optics
Zernike Mode Sorting with Vortex Phase Filters: Perfect Coronagraphs and Ideal Wavefront Sensors
Jacob Trzaska and Amit Ashok
Spatial mode sorting has come to prominence as an optical processing modality capable of saturating fundamental limits to numerous sensing tasks including wavefront sensing, coronagraphy, and superresolution imaging. But despite their promising theoretical advantages, contemporary mode sorters often feature large crosstalk, high loss, or sort modes that are poorly adapted to conventional imaging systems (e.g., Hermite- and Laguerre-Gauss). Here, we introduce an alternative architecture that sorts spatial modes natural to circularly symmetric apertures: Zernike
polynomials. Using conventional optics hardware and even-order
vortex phase plates, we show how to assemble a series of
vortex phase filters that can in principle separate the various Zernike
polynomials losslessly and without crosstalk. This idea is demonstrated via application to wavefront sensing and coronagraphy, where we propose an optical system that saturates the
quantum sensitivity limits to both tasks. We expect our work to prove useful for high-contrast imaging of extrasolar
planets, improving both wavefront control and coronagraph performance.
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Fluid Dynamics
Revisiting the phenomenon of bouncing of inertial particles crossing density stratified interfaces
Chen Mortenfeld, Maarten van Reeuwijk, Aviv Littman et al. (+1 more)
Inertial spheres settling through sharp density interfaces can arrest, reverse direction, and resume descent, a phenomenon known as bouncing. Using synchronized particle image velocimetry and tracking in water-salt and water-glycerol stratifications, we demonstrate that bouncing is the dynamic response of a coupled sphere-fluid composite. As the sphere crosses the interface, it entrains a boundary layer of lighter fluid, creating a transient buoyant wake. We formalize this mechanism into a phenomenological dynamic model that couples the momentum of the sphere with the entrainment and detachment of the wake. Evaluating the stationary points of this system yields a criterion that classifies trajectory archetypes (smooth crossing, deep minima, and bouncing) across different fluid regimes. We identify a dual role of viscosity, which is often overlooked by density-only models: it acts kinematically to thicken the boundary layer and increase the entrained wake volume, and dynamically to alter the drag-to-weight balance. Furthermore, we describe the spatial dynamics of the crossing: inertia-dominated spheres penetrate further into the lower fluid before arresting due to a longer wake-detachment length, whereas buoyancy-dominated spheres arrest closer to the interface. Finally, we show that the retention time is governed by the buoyancy-driven detachment of the entrained film. By normalizing the measured retention times with a characteristic detachment timescale, we collapse the data from different viscosity regimes onto a single curve. These physical insights allow the prediction of trajectory archetype, deceleration depth, and retention time from bulk properties.
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All authors Chen Mortenfeld, Maarten van Reeuwijk, Aviv Littman, Alex Liberzon
Physics and Society
MacroEnergy.jl: A large-scale multi-sector energy system framework
Ruaridh Macdonald, Filippo Pecci, Luca Bonaldo et al. (+4 more)
MacroEnergy.jl (aka Macro) is an open-source framework for multi-sector capacity expansion modeling and analysis of macro-energy systems. It is written in Julia and uses the JuMP package to interface with a wide range of mathematical solvers. It enables researchers and practitioners to design and analyze energy and industrial systems that span electricity, fuels, bioenergy, steel, chemicals, and other sectors. The framework is organized around a small set of sector-agnostic components that can be combined into flexible graph structures, making it straightforward to extend to new technologies, policies, and commodities. Its companion packages support decomposition methods and other advanced techniques, allowing users to scale models across fine temporal and spatial resolutions. MacroEnergy.jl provides a versatile platform for studying energy transitions at the detail and scale demanded by modern research and policy.
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All authors Ruaridh Macdonald, Filippo Pecci, Luca Bonaldo, Jun Wen Law, Yu Weng, Dharik Mallapragada, Jesse Jenkins