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At least 1,171 records · Page 65

A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics

The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.

computational combustion↗

Nanometer-thick ultraflat cantilever resonators

Nanomechanical devices made from ultrathin materials are transforming diverse fields, including sensing, signal processing, and quantum technologies. However, as these materials become thinner, their low bending rigidity poses significant fabrication challenges, and achieving nanometer-thick flat cantilevers with consistent and predictable mechanical responses has remained elusive despite decades of research. Here we present nanometer-thick, ultraflat cantilever resonators fabricated using atomic layer deposition. By effectively mitigating the effects of uncontrollable built-in strain and geometric disorder, the ultraflat nanocantilevers exhibit resonance frequencies closely aligned with thin-plate theory predictions and display low sample-to-sample variability. These cantilevers maintain mechanical stability in both vacuum and air environments, even at large length-to-thickness ratios of up to 3000. The ultraflat nanocantilevers are approaching the thickness limit, beyond which thermal fluctuations at room temperature can spontaneously induce random ripples in otherwise flat films.

nanofabrication↗

Quantitative phase retrieval and characterization of magnetic nanostructures via Lorentz (scanning) transmission electron microscopy

Magnetic materials phase reconstruction using Lorentz transmission electron microscopy (LTEM) measurements have traditionally been achieved using longstanding methods such as off-axis holography (OAH) fast-Fourier transform technique and the transport-of-intensity equation (TIE). The increase in access to processing power alongside the development of advanced algorithms have allowed for phase retrieval of nanoscale magnetic materials with greater efficacy and resolution. Specifically, reverse-mode automatic differentiation (RMAD) and the extended electron ptychography iterative engine (ePIE) are two recent developments of phase retrieval that can be applied to analyzing micro-to-nano- scale magnetic materials. This work evaluates phase retrieval using TIE, RMAD, and ePIE in simulations of Permalloy (Ni 80 Fe 20 ) nanoscale islands, or nanomagnets. Extending beyond simulations, we demonstrate total phase retrieval and image reconstructions of a NiFe nanowire using OAH and RMAD in LTEM and ePIE in Lorentz-mode-4D scanning transmission electron microscopy experiments and determine the saturation magnetization through corroborations with micromagnetic modeling. Finally, we demonstrate the efficacy of these methods in retrieving the total phase and highlight its use in characterizing and analyzing the proximity effect of the magnetic nanostructures.

Lorentz transmission electron microscopy↗

Spatiotemporal forecasting of the edge localized modes in tokamak plasmas using neural networks

Artificial intelligence techniques have been increasingly adopted by the plasma and fusion science to address problems like plasma reconstruction, surrogate modeling, and tokamak/stellarator optimization. A key focus in sustained fusion research is the prediction and mitigation of edge-localized-modes (ELMs), instabilities that occur in short, periodic bursts and can cause erosion to the tokamak vessel wall. Recent research has demonstrated the power of neural networks in approximating continuous functions. In this work, we build spatiotemporal forecasting models that can predict the onset of ELMs and their evolution at early stages. We leverage recent advances in generative modeling, sequence-to-sequence modeling, and Fourier neural operators to propose architectures and training strategies that can learn to forecast short to long term dynamics of the noisy signals due to ELMs. We benchmark the developed model against a state-of-the-art foundation model using the beam emission spectroscopy (BES) data that captures the plasma fluctuations due to ELMs over a 8 x 8 spatial grid. Our models demonstrate high accuracy, outperforming the baselines, in predicting the evolution of BES signals during ELM events. Furthermore, the developed models exhibit high accuracy in predicting the rapid rise and relaxation of the signals due to ELMs within 30–80 µs.

edge localized modes↗

Latent Twins

Over the past decade, scientific machine learning has transformed the development of mathematical and computational frameworks for analyzing, modeling, and predicting complex systems. From inverse problems to numerical partial differential equations (PDEs), dynamical systems, and model reduction, these advances have pushed the boundaries of what can be simulated. Yet they have often progressed in parallel, with representation learning and algorithmic solution methods evolving largely as separate pipelines. With Latent Twins, we propose a unifying mathematical framework that creates a hidden surrogate in latent space for the underlying equations. Whereas digital twins mirror physical systems in the digital world, Latent Twins mirror mathematical systems in a learned latent space governed by operators. Through this lens, classical modeling, inversion, model reduction, and operator approximation all emerge as special cases of a single principle. We establish the fundamental approximation properties of Latent Twins for both ordinary differential equations (ODEs) and PDEs and demonstrate the framework across three representative settings: (i) canonical ODEs, capturing diverse dynamical regimes; (ii) a PDE benchmark using the shallow-water equations, contrasting Latent Twin simulations with deep operator network and forecasts with a four-dimensional variational method baseline; and (iii) a challenging real-data geopotential reanalysis dataset, reconstructing and forecasting from sparse, noisy observations. Latent Twins provide a compact, interpretable surrogate for solution operators that evaluate across arbitrary time gaps in a single-shot, while remaining compatible with scientific pipelines such as assimilation, control, and uncertainty quantification. Looking forward, this framework offers scalable, theory-grounded surrogates that bridge data-driven representation learning and classical scientific modeling across disciplines.

Latent Twins↗

Quantum chemically calculated Abraham parameters for quantifying and predicting polymer hydrophobicity

The leakage and accumulation of plastic in the environment is a significant and growing problem with numerous detrimental impacts and has led to a push toward the design and development of more environmentally benign materials. To this end, we have developed a quantum chemistry-based model for predicting the mobility of polymer materials from molecular structure. Hydrophobicity is used as a surrogate for mobility given that hydrophobic interactions drive much of the partitioning of contaminants in and out of various environmentally relevant compartments. To model polymer hydrophobicity, we adjusted a previously developed Quantum Chemically Calculated Abraham Parameter model to calculate Abraham parameters of small molecules from molecular structure information. The resulting model predicted the octanol-water partition coefficient (K OW ) of polymer repeating units with a root mean square error (RMSE) of 0.48 (log scale). Additionally, the hydrophobicity of high molecular weight polymer materials was captured through solubility parameters and Nile red staining experiments from the literature and predicted with RMSEs of 1.21 (J/cc) 0.5 and 3.42 nm, respectively. Finally, to test the environmental applicability of the model, the relative adsorption capacity of three polymers was predicted and used to unify sorption isotherms across multiple sorbates and polymer sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Backward-Angle Electroproduction of η′ Mesons off Protons at W = 2.13 GeV and Q 2 = 0.46 (GeV/ c ) 2

The electroproduction of $\eta ^{\prime }$ mesons from a $\mathrm{^{1}H}$ target at $W=\mathrm{2.13~GeV}$, $Q^{2} = 0.46~\left( \mathrm{GeV/}c\right)^{2}$, and $\cos \theta ^{\mathrm{CM}}_{\gamma ^{*}\eta ^{\prime }} \approx -1$ has been experimentally measured. The differential cross section of virtual photoproduction has been obtained as $4.4 \pm 0.8 ~\left( \mathrm{stat.} \right) \pm 0.4 ~\left( \mathrm{sys.} \right)~ \mathrm{nb/sr}$ in the One-Photon-Exchange Approximation. This value is one-sixth of that of real photoproduction at backward angles. A comparison with newly developed isobar model calculations not only shows the validity of the theoretical framewark employed, but also imposes new constraints on coupling strength between the $\eta ^{\prime }p$ final state and nucleon resonances.

Nuclear Physics↗

Genomic reconstruction of Bacillus anthracis from complex environmental samples enables high-throughput identification and lineage assignment in Pakistan

Bacillus anthracis, the causative agent of anthrax, is a highly virulent zoonotic pathogen primarily affecting domesticated and wild herbivores. Human exposure to B. anthracis is primarily through contact with infected animals or contaminated animal products. In Pakistan, where livestock vaccines are largely unavailable and infected carcasses are often disposed of improperly, the risk to humans, wildlife and livestock is significant. Currently, the diagnosis of anthrax infections and outbreak tracing necessitates the isolation and culturing of B. anthracis, a process that requires BSL-3 facilities. In this study, we show that positive identification, genome reconstruction and lineage assignment can be accomplished using bioinformatic analysis of DNA extracted directly from environmental samples that would otherwise provide the starting material for isolation and culturing. This approach does not require laboratory target enrichment as is necessary for other pathogens, due in part to the extremely high bacterial load in the bloodstream in the deceased animals. Using these methods, we greatly expand the knowledge of endemic B. anthracis in Pakistan. We provide the first reference B. anthracis genomes from Pakistan since the 1970s and identify A.Br.014 Aust94 as a minor circulating sublineage alongside the dominant A.Br.047 Vollum. Future work will focus on the limits of detection and will determine if this bioinformatic method can be expanded more broadly for B. anthracis or other pathogens to replace typical culture-based methods.

A.Br.047 Vollum↗

Comment on “Hermitian stochastic methodology for x-ray superfluorescence”

This comment critically examines the paper “Hermitian stochastic methodology for x-ray superfluorescence” by Chuchurka, Sukharnikov, and Rohringer [Phys. Rev. A 109, 063705 (2024)]. Here, the paper proposes a Hermitian framework based on the positive-𝑃 stochastic equations (PPSEs), claimed to be derived “from first principles,” through a redefinition of physical variables without a clear rationale. However, because the original PPSEs cannot satisfy Hermiticity under any stochastic-diffusion-gauge transformation, the framework necessarily employs representations beyond this gauge freedom, thereby contradicting the original PPSEs and their ensemble-average predictions. The resulting equations have close structural similarities with the previously established Hermitian formalism of stochastic Maxwell-Bloch equations [arXiv:2305.04653 and Phys. Rev. A 110, 023724 (2024)].

Park, Jeong-Wan [Argonne National Laboratory (ANL)↗

Spin pumping driven by magnon-polaritons in a ferromagnet–coplanar superconducting resonator hybrid system

We demonstrate spin pumping driven by a strongly coupled magnon-photon system using a ferromagnet-coplanar superconducting resonator hybrid system at 1.4 K. Electrical readout via the inverse spin-Hall effect reveals characteristic coupling features, including mode splitting and linewidth broadening, demonstrating the electrical detection of strongly coupled microwave photons and magnons. The microwave magnon-photon coupling strength obtained by combined spin pumping and inverse spin-Hall effect measurements is compared to microwave transmission experiments. Here, microwave power-dependent measurements reveal a decrease in the coupling strength with increasing microwave power alongside the onset of nonlinearities of the superconducting resonator above a critical microwave power threshold.

Wagle, Dinesh [University of Delaware, Newark, DE ↗

𝛾-ray spectroscopy of 140 La decay for nuclear forensics applications

140 La is an important isotope in nuclear forensics. It is typically paired with 140 Ba as a chronometer for dating nuclear events. Here, in this work, we report the results of two measurements performed to fully characterize the decay scheme of 140 La. The experiments were performed using the Gammasphere array at Argonne National Laboratory and the CLARION2 array at Florida State University. Sources of 140 La were produced through neutron irradiation of natural lanthanum (99.9% 139 La) in the University of Massachusetts Lowell research reactor. We identify a total of 40 transitions, three of which were not previously reported. An angular correlation analysis was conducted confirming current literature 𝐽 assignments and mixing ratios. By considering all data available in the literature, we provide new recommended values for the intensities of the strongest transitions commonly used in applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impact of structural distortions on the correlated electronic structure of orbital-selective Mott insulating Na 3 ⁢Co 2 ⁢SbO 6 under strain

Na 3 Co 2 SbO 6 is a promising candidate to realize the Kitaev spin liquid phase since the large Kitaev spin exchange interaction is tunable via the change in electronic structure, such as the trigonal crystal field splitting (Δ TCF ). Here, in this study, we show that the uncorrelated electronic structure of Na 3 Co 2 SbO 6 is rather insensitive to the strain effect due to the low crystal symmetry accompanied by oxygen displacements and the presence of Sb s orbitals. Using density functional theory plus dynamical mean field theory, we find that the correlated electronic structure of Na 3 Co 2 SbO 6 is an orbital-selective Mott insulating state where the trigonal a 1g orbital is insulating due to the nearly full occupation, while other d orbitals behave as typical Mott insulators, resulting in the effective tunability of Δ TCF under the strain effect. The sign change of Δ TCF can occur as the in-plane tensile strain is applied, and the Kitaev spin liquid phase could possibly be realized due to the strongly suppressed Δ TCF under tensile strain. Our results show that the local Co-site symmetry and dynamical correlation effects will play an important role in engineering the novel magnetic phase in this and related materials.

Nguyen, Nam [Univ. of Illinois, Chicago, IL (Unite↗

Emergence of pseudoresonance in high-intensity resonant inelastic x-ray scattering

We report resonant inelastic x-ray scattering (RIXS) spectra of neon atoms interacting with intense x-ray pulses generated using an x-ray free-electron laser (XFEL). We find that an unexpected peak emerges near the 𝐾⁢𝛼 line of Ne, which does not coincide with any physical resonances of neon ions. We perform theoretical calculations based on a quantum-state-resolved rate-equation approach with x-ray-induced processes including possible resonant excitations. Our dynamics simulations demonstrate that a sequence of multiple resonant photoabsorption events are involved and the interplay of those multiple resonances in combination with the relatively large spectral bandwidth of XFEL radiation leads to the emergent resonance-like structure at a position where no resonances exist. Our finding offers critical guidance for future applications of high-intensity RIXS at XFEL facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗

Pervasive symmetry-lowering nanoscale structural fluctuations in the cuprate La 2−𝑥 ⁢Sr 𝑥 ⁢Cu⁢O 4

The cuprate superconductors are among the most widely studied quantum materials, yet there remain fundamental open questions regarding their electronic properties and the role of structural degrees of freedom. Recent neutron and x-ray scattering measurements uncovered exponential scaling with temperature of the strength of orthorhombic fluctuations in the tetragonal phase of La 2−𝑥⁢ Sr 𝑥 ⁢Cu⁢O 4 and Tl 2 ⁢Ba 2 ⁢Cu⁢O 6+𝛿 , unusual behavior that closely resembles prior results for the emergence of superconducting fluctuations, and that points to a common origin rooted in inherent correlated structural inhomogeneity. Here, in this study, we use neutron and x-ray diffuse scattering to provide further insight into structural fluctuations in La 2−𝑥 ⁢Sr 𝑥 ⁢Cu⁢O 4 . We perform measurements up to temperatures that approach the melting point of the undoped parent compound, and we investigate the effects of in situ in-plane uniaxial elastic stress and plastic deformation. Our neutron scattering results for the parent compound La 2 ⁢Cu⁢O 4 reveal that short-range orthorhombic fluctuations persist to the maximum experimental temperature of nearly 1000 K, i.e., to a significant fraction of the crystallization temperature. At this temperature, the spatial characteristic length extracted from the momentum-space data is still about three lattice constants. The neutron scattering experiment enables quasistatic discrimination and reveals that the response is increasingly dynamic at higher temperatures. We also find that neither compressive elastic stress along the tetragonal [110] direction nor irreversible plastic deformation activating the ⟨100⟩⁢[001] slip system significantly alter the robust orthorhombic fluctuations. Overall, these results support the notion that these fluctuations couple to subtle, underlying inhomogeneity that underpins the cuprate phase diagram. Finally, in La 1.8⁢ Sr 0.2⁢ Cu⁢O 4 , we uncover low-energy structural fluctuations at a nominally forbidden reflection that are distinct from the orthorhombic distortions. While the origin of these fluctuations is not clear, they might be related to the presence of extended defects such as dislocations or stacking faults.

Spieker, R. J. [Univ. of Minnesota, Minneapolis, M↗

Large-momentum effective theory’s asymptotic extrapolation vs the inverse problem

Large-momentum effective theory is a physics-guided systematic expansion to calculate light-cone parton distributions, including collinear (PDFs) and transverse-momentum-dependent ones, at any fixed momentum fraction 𝑥 within a range of [𝑥 min , 𝑥 max ]. It theoretically solves the ill-posed inverse problem that afflicts other theoretical approaches to collinear PDFs, such as short-distance factorizations. Recently, Dutrieux et al. raised practical concerns about whether current or even future lattice data will have sufficient precision in the subasymptotic correlation region to support an error-controlled extrapolation—and if not, whether it becomes an inverse problem where the relevant uncertainties cannot be properly quantified. While we agree that not all current lattice data have the desired precision to qualify for an asymptotic extrapolation, some calculations do, and more are expected in the future. We comment on the analysis and results in Dutrieux et al. and argue that a physics-based systematic extrapolation still provides the most reliable error estimates, even when the data quality is not ideal. In contrast, reframing the long-distance asymptotic extrapolation as a data-driven-only inverse problem with ad hoc mathematical conditioning could lead to unnecessarily conservative errors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

In-Plane Anisotropy of Charge Density Wave Fluctuations in 1⁢𝑇−TiSe 2

We report measurements of anisotropic triple-𝑞 charge density wave (CDW) fluctuations in the transition metal dichalcogenide 1⁢𝑇−TiSe 2 over a large volume of reciprocal space with x-ray diffuse scattering. Above the transition temperature, 𝑇 CDW , the in-plane diffuse scattering is marked by ellipses which reveal that the in-plane fluctuations are anisotropic. In addition, the out-of-plane diffuse scattering is characterized by rodlike structures which indicate that the CDW fluctuations in neighboring layers are largely decoupled. Furthermore, our analysis of the diffuse scattering line shapes and orientations suggests that the three charge density wave components contain independent phase fluctuations with a hierarchy of length scales, leading to intricate fluctuation patterns that go beyond the conventional 2D-to-3D crossover picture.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Resonant inelastic x-ray scattering investigation of Hund's and spin-orbit coupling in 5 d 2 double perovskites

𝐵 site ordered 5⁢𝑑 2 double perovskites (𝐴 2 ⁢𝐵⁢𝐵′⁢O 6 , 𝐵′ = 5⁢𝑑 2 ) display a remarkable range of physical properties upon variation of the chosen 𝐵 and 𝐵′ site ions. This sensitivity to chemical substitution reflects the delicate balance and profound impact of strong electronic correlation and spin-orbit coupling in such systems. Here, we present rhenium 𝐿 2 and 𝐿 3 resonant inelastic x-ray scattering (RIXS) measurements of two such physically dissimilar materials, Mott-insultating Ba 2⁢ Y⁢Re⁢O 6 and semiconducting Sr 2⁢ Cr⁢Re⁢O 6 . Despite these differences, our RIXS results reveal similar energy scales of Hund's (𝐽 𝐻 ) and spin-orbit coupling (𝜁) in the two materials, with both systems firmly in the intermediate Hund's coupling regime where 𝐽 𝐻 /𝜁∼1. However, there are clear differences in their RIXS spectra. The conductive character of Sr 2⁢ Cr⁢Re⁢O 6 broadens and obfuscates the atomic transitions within an electron-hole continuum, while the insulating character of Ba 2 ⁢Y⁢Re⁢O 6 results in sharp atomic excitations. This contrast in their RIXS spectra despite their similar energy scales reflects a difference in the itinerancy-promoting hopping integral and illustrates the impact of the local crystal environment in double perovskites. Finally, 𝐿 2 and 𝐿 3 edge analyses of the atomic excitations in Ba 2 ⁢Y⁢Re⁢O 6 reveal that the ordering of the low lying excited states is inverted compared to previous reports, such that the appropriate energy scales of Hund's and spin-orbit coupling are significantly modified. We present exact diagonalization calculations of the RIXS spectra at both edges which show good agreement with our results for new energy scales of 𝜁 = 0.290⁢(5)⁢eV and 𝐽 𝐻 = 0.38⁢(2)⁢eV [𝐽 𝐻 /𝜁 = 1.30⁢(5)].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kramers nodal line in the charge density wave state of YTe 3 and the influence of twin domains

Recent studies have focused on the relationship between charge density wave (CDW) collective electronic ground states and nontrivial topological states. YTe 3 , a nonmagnetic quasi-two-dimensional chalcogenide, has been reported to exhibit a CDW state below 334 K. Using angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT), we establish that YTe 3 is a CDW-induced Kramers nodal line (KNL) metal, a recently proposed topological state of matter. Scanning tunneling microscopy and low energy electron diffraction reveal two orthogonal domains, each with a unidirectional CDW and a similar wave vector (𝐪 CDW ). When the influence of twin domains is considered, the effective band structure (EBS) computations that utilize DFT-calculated bands using a noncentrosymmetric structure determined by x-ray crystallography, show excellent agreement with ARPES. The noncentrosymmetry of YTe 3 is established by Raman spectroscopy. The Fermi surface and ARPES intensity plots show weak shadow bands displaced by 𝐪 CDW from the main bands. Furthermore, these are linked to CDW modulation, as the EBS calculation confirms. Bilayer split main and shadow bands suggest the existence of crossings, according to theory and experiment. DFT bands, including spin-orbit coupling, indicate existence of a KNL along the Σ direction from multiple crossings of bands dispersing perpendicular to it. Additionally, doubly degenerate bands are only found along the KNL at all energies, with some bands dispersing through the Fermi level.

Angle-resolved photoemission spectroscopy↗