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At least 109 records · Page 6

Flavor-dependent radiative corrections in coherent elastic neutrino-nucleus scattering

We calculate coherent elastic neutrino-nucleus scattering cross sections on spin-0 nuclei (e.g. 40 Ar and 28 Si) at energies below 100 MeV within the Standard Model and account for all effects of permille size. We provide a complete error budget including uncertainties at nuclear, nucleon, hadronic, and quark levels separately as well as perturbative error. Our calculation starts from the four-fermion effective field theory to explicitly separate heavy-particle mediated corrections (which are absorbed by Wilson coefficients) from light-particle contributions. Electrons and muons running in loops introduce a non- trivial dependence on the momentum transfer due to their relatively light masses. These same loops, and those mediated by tau leptons, break the flavor universality because of mass-dependent electromagnetic radiative corrections. Nuclear physics uncertainties significantly cancel in flavor asymmetries resulting in subpercent relative errors. We find that for low neutrino energies, the cross section can be predicted with a relative precision that is competitive with neutrino-electron scattering. We highlight potentially useful applications of such a precise cross section prediction ranging from precision tests of the Standard Model, to searches for new physics and to the monitoring of nuclear reactors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Direct Imaging of Asymmetric Interfaces and Electrostatic Potentials inside a Hafnia–Zirconia Ferroelectric Nanocapacitor

In hafnia-based thin-film ferroelectric devices, chemical phenomena during growth and processing, such as oxygen vacancy formation and interfacial reactions, appear to strongly affect device performance. However, the correlation between the structure, chemistry, and electrical potentials at the nanoscale in these devices is not fully known, making it difficult to understand their influence on device properties. Here, we directly image the composition and electrostatic potential with nanometer resolution in the cross section of a nanocrystalline W/Hf 0.5 Zr 0.5 O 2−δ (HZO)/W ferroelectric capacitor using multimodal electron microscopy. This reveals a 1.4 nm wide tungsten suboxide interfacial layer formed at the bottom interface during fabrication, which introduces a potential dip and leads to asymmetric switching fields. Additionally, we compare the measured potentials to DFT calculations and find it is nearly 3 V lower than expected in the HZO, which appears to be caused by oxygen vacancies and a resulting negative built-in potential. In conclusion, these chemical and electrostatic details are important to characterize and tune to achieve high-performance ferroelectric devices.

Defects in solids↗

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Gibson, Luke D. [Oak Ridge National Laboratory (OR↗

5. Cross-Sectioning

Now that an object has been transformed to an STL representation, the first major step of the slicing process can begin: cross-sectioning. This step converts a 3D object into a stack of polygons. Polygons are closed, 2D shapes composed of straight edges. These polygons are typically the result of intersecting a plane with an object at various heights along the z-axis. These stacked polygons create the “layers” that are characteristic of the 3D-printing process. In addition to the cross-section operation itself, several details need to be addressed. These details include necessary preprocessing and potential stitching, smoothing, and simplification of the cross-sections.

Borish, Michael↗

Quantum and anharmonic effects in non-adiabatic transition state theory

Quantitative descriptions of non-adiabatic transition rates at intermediate temperatures are challenging due to the simultaneous importance of quantum and anharmonic effects. Here, in this paper, the interplay between quantum effects—for motion across or along the seam of crossing—and anharmonicity in the seam potential is considered within the weak coupling limit. The well-known expression for quantized 1-D motion across the seam (i.e., tunneling) in the linear terms approximation is derived in the thermal domain using the Lagrangian formalism, which is then applied to the case when tunneling is distributed along the seam of crossing (treating motion along the seam classically). For high-frequency quantum modes, a vibrationally adiabatic (VA) approach is developed that introduces to the non-adiabatic rate constant a factor associated with high-frequency wavefunction overlap; this approach treats the high-frequency motion along the seam quantum mechanically. To test these methodologies, the reaction N 2 O ↔ N 2 + O( 3 P) was chosen. CCSD(T)-F12b/cc-pVTZ-F12 explorations of the 3 A'- 1 A' seam of N 2 O revealed that seam anharmonicity has a strong effect on the rate constant (a factor of ~20 at 2000 K). Several quantum effects were found to be significant at intermediate/lower temperatures, including the quantum N–N vibration that was coupled with seam anharmonicity using the VA approach. Finally, a 1-D approximation to non-adiabatic instanton theory is presented to estimate the validity limit of the linear terms model at low temperatures (⁠~ 250 K for N 2 O). We recommend that the assumptions built into many statistical theories for non-adiabatic reactions—harmonic behavior, classical motion, linear terms, and weak coupling—should be verified on a case-by-case basis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vaccine Advances against Venezuelan, Eastern, and Western Equine Encephalitis Viruses

Vaccinations are a crucial intervention in combating infectious diseases. The three neurotropic Alphaviruses, Eastern (EEEV), Venezuelan (VEEV), and Western (WEEV) equine encephalitis viruses, are pathogens of interest for animal health, public health, and biological defense. In both equines and humans, these viruses can cause febrile illness that may progress to encephalitis. Currently, there are no licensed treatments or vaccines available for these viruses in humans. Experimental vaccines have shown variable efficacy and may cause severe adverse effects. Here, we outline recent strategies used to generate vaccines against EEEV, VEEV, and WEEV with an emphasis on virus-vectored and plasmid DNA delivery. Despite candidate vaccines protecting against one of the three viruses, few studies have demonstrated an effective trivalent vaccine. We evaluated the potential of published vaccines to generate cross-reactive protective responses by comparing DNA vaccine sequences to a set of EEEV, VEEV, and WEEV genomes and determining the vaccine coverages of potential epitopes. Finally, we discuss future directions in the development of vaccines to combat EEEV, VEEV, and WEEV.

59 BASIC BIOLOGICAL SCIENCES↗

Cross-kingdom expression of synthetic genetic elements promotes discovery of metabolites in the human microbiome

Small molecules encoded by biosynthetic pathways mediate cross-species interactions and harbor untapped potential, which has provided valuable compounds for medicine and biotechnology. Since studying biosynthetic gene clusters in their native context is often difficult, alternative efforts rely on heterologous expression, which is limited by host-specific metabolic capacity and regulation. Here, in this work, we describe a computational-experimental technology to redesign genes and their regulatory regions with hybrid elements for cross-species expression in Gram-negative and -positive bacteria and eukaryotes, decoupling biosynthetic capacity from host-range constraints to activate silenced pathways. These synthetic genetic elements enabled the discovery of a class of microbiome-derived nucleotide metabolites—tyrocitabines—from Lactobacillus iners. Tyrocitabines feature a remarkable orthoester-phosphate, inhibit translational activity, and invoke unexpected biosynthetic machinery, including a class of “Amadori synthases” and “abortive” tRNA synthetases. Our approach establishes a general strategy for the redesign, expression, mobilization, and characterization of genetic elements in diverse organisms and communities.

59 BASIC BIOLOGICAL SCIENCES↗

Learning nuclear cross sections across the chart of nuclides with graph neural networks

We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.

Machine learning↗

Signatures of Cooper pair dynamics and quantum-critical superconductivity in tunable carrier bands

Different superconducting pairing mechanisms are markedly distinct in the underlying Cooper pair kinematics. Quantum-critical soft modes drive pairing interactions in which the pair scattering processes are highly collinear and can be classified into two categories: forward scattering and backscattering. Conversely, in conventional phonon mechanisms, Cooper pair scattering is of a generic noncollinear character. In this study, we present a method to discern the kinematic type by observing the evolution of superconductivity while adjusting the Fermi surface geometry. To demonstrate our approach, we utilize the recently reported phase diagrams of untwisted graphene multilayers. Our analysis connects the emergence of superconductivity at “ghost crossings” of Fermi surfaces in distinct valleys to the pair kinematics of a backscattering type. Together with the observed nonmonotonic behavior of superconductivity near its onset (sharp rise followed by a drop), it lends strong support to a particular quantum-critical superconductivity scenario in which pairing is driven by intervalley coherence fluctuations. These findings offer direct insights into the genesis of pairing in these systems, providing compelling evidence for the electron–electron interactions driving superconductivity. More broadly, our work highlights the potential of tuning bands via ghost crossings as a promising means of boosting superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Linearized Pair-Density Functional Theory for Vertical Excitation Energies

Multiconfiguration pair-density functional theory (MC-PDFT) is a computationally efficient method that computes the energies of electronic states in a state specific or state average framework via an on-top functional. However, MC-PDFT does not include state interaction among these states since the final energies do not come from the diagonalization of an effective model-space Hamiltonian. Recently, multistate extensions such as linearized PDFT (L-PDFT) have been developed to accurately model the potentials near conical intersections and avoided crossings. However, there has not been any systematic study evaluating their performance for predicting vertical excitations at the equilibrium geometry of a molecule, when the excited states are generally well separated. In this paper, we report the performance of L-PDFT on the extensive QUESTDB data set of vertical excitations using a database of automatically selected active spaces. We show that L-PDFT performs well on all these excitations and successfully reproduces the performance of MC-PDFT. These results further demonstrate the potential of L-PDFT, as its scaling is constant with the number of states included in the state-average manifold, whereas MC-PDFT scales linearly in this regard.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Born-Oppenheimer potentials for $SU$(3) gauge theory

We develop parametrizations of eight of the lowest Born-Oppenheimer potentials for quarkonium hybrid mesons as functions of the separation r of the static quark and antiquark sources. The parameters are determined by fitting results calculated using pure SU⁡(3) lattice gauge theory. The parametrizations have the correct limiting behavior at small r, where the potentials form multiplets associated with gluelumps. They have the correct limiting behavior at large r, where the potentials form multiplets associated with excitations of a relativistic string. There is a narrow avoided crossing in the small-r region between two potentials with the same Born-Oppenheimer quantum numbers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Study of reference burnup steps optimization in fuel segment data file generation for NEXUS/ANC9 code system

For any two-step core design code system, the cross-section files are the primary factor to determine the accuracy of the system prediction. For a once-through cross-section system to cover all potential applicable conditions, the system may need to perform tens of thousands state points of lattice calculations. These calculations take a significant amount of CPU times and computing power, especially when a fine or ultra-fine energy group library is used. As computer power increases, so does the calculational complexity. Therefore, it is important to make the lattice calculations effective and efficient. Based on the Westinghouse core design code system NEXUS/ANC9, this work focuses on the reference burnup steps used by the lattice code when performing the calculations. Following the fundamental cross-section methodology and analyzing the contribution of each individual terms, this study provides an applicable solution of the optimized reference burnup steps. The test results show that, with the existing cross-section methodology, it is possible to significantly reduce the lattice calculation cases and cross-section file generation time without sacrificing the accuracy of system prediction. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Measurement of the near-threshold 𝐽/𝜓 photoproduction cross section with the CLAS12 experiment

We present measurements of the total and differential cross sections for near-threshold 𝐽/𝜓 photoproduction obtained with the CLAS12 detector at the Thomas Jefferson National Accelerator Facility. The results are based on data collected during the fall 2018 and spring 2019 running periods, using electron beams with energies of 10.6 and 10.2 GeV, respectively, scattered off a liquid-hydrogen target. Near-threshold 𝐽/𝜓 photoproduction offers a unique sensitivity to the strong interaction in the nonperturbative regime of quantum chromodynamics (QCD). The energy dependence of the cross section constrains the underlying 𝐽/𝜓 production mechanisms, including multigluon exchange and potential baryonic excitations. Additionally, the 𝑡 dependence of the differential cross section can be related to the transverse spatial distribution of gluons in the proton, providing critical input for theoretical descriptions of the gluonic structure of the proton. An interpretation of the results in terms of the gluon content of the proton is presented, providing new experimental constraints on QCD-inspired models of the proton structure and the role of gluonic degrees of freedom in hadronic mass generation.

form factors↗

Cross-correlation of SPT-3G D1 CMB lensing and DES Y3 galaxy lensing

Measurements of the weak lensing of galaxies and of the cosmic microwave background (CMB) provide direct probes of the cosmic matter density field, but the two observables are sensitive to different spatial scales, redshift ranges, and survey systematics. Their cross-correlation thus enables consistency checks of the theoretical model and of potential systematics in either dataset. We present measurements of the cross-correlation between CMB lensing and cosmic shear over $\sim$1,300 deg$^2$ of the sky using the SPT-3G D1 CMB lensing maps and the Dark Energy Survey Year 3 (DES Y3) shear catalogs. For the first time, we measure this cross-correlation at high significance ($\sim 14σ$) when using a polarization-only CMB lensing reconstruction that is expected to be robust against biases induced by extragalactic foregrounds. We test a variety of other CMB lensing estimators that include temperature information and exhibit different tradeoffs between foreground biases and noise, as well as a shear sample that consists of blue, star-forming galaxies and has been shown to be less impacted by galaxy intrinsic alignments. Assuming $Λ$CDM and marginalizing over uncertainties in intrinsic alignments, baryonic feedback, and various nuisance parameters, we obtain a constraint on the amplitude of matter clustering $S_8 \equiv σ_8 \sqrt{Ω_m / 0.3} = 0.833^{+0.047}_{-0.061}$, consistent with both the primary CMB results from Planck and shear-only results from DES Y3. By combining our measurement with Planck, we find mild constraints on the astrophysical processes that impact the cross-correlation. We obtain a constraint on the intrinsic alignment amplitude of the DES sample that is competitive with that from shear-only analyses, and we find a lower limit on the strength of baryonic feedback.

Ouellette, A. [Illinois U., Urbana] (ORCID:0000000↗

Prelithiated SiO x /Graphite-NMC811 Cells: Capacity Loss, Impedance Rise and Hidden Degradation Pathways Revealed Using Three-Electrode Diagnostics

Electrodes containing SiO x /graphite (Gr) materials are attractive as anodes for high-energy lithium-ion batteries. However, their mechanical deformation, electrochemical response, and impedance evolution during long-term cycling are strongly coupled, complicating accurate diagnosis of performance fade mechanisms. In this work, the behavior of electrochemically prelithiated SiO x /Gr anodes paired with NMC811 cathodes is systematically investigated using techniques that include in-situ dilatometry, three-electrode electrochemistry, and multiscale post-cycling microscopy. The SiO x /Gr electrode exhibits a maximum expansion of 49% upon lithiation to 10 mV vs Li + /Li, with 84% of the expansion and 91% of the capacity being reversible. In full cells, relatively stable cycling with only 12% capacity fade over 500 cycles is observed. Three-electrode experiments reveal cell-level impedance growth, which is dominated by the NMC811 cathode: the SiO x /Gr anode exhibits minimal net impedance rise and an initial impedance decrease at low potentials. Despite this apparent electrochemical stability, cross-sectional SEM, PFIB tomography, and cryo-STEM reveal irreversible anode thickening caused by the accumulation of an inorganic-rich solid electrolyte interphase (SEI) permeating the anode bulk. Electrode potential-shift analysis further demonstrates that Li + ions released from lithium reservoirs in the prelithiated anode mask true lithium inventory loss during aging. These results demonstrate that low-expansion SiO x /Gr anodes can simultaneously exhibit favorable cycling and impedance metrics while undergoing substantial, hidden degradation, underscoring the importance of electrode-resolved diagnostics for evaluating prelithiated silicon-based anodes.

25 ENERGY STORAGE↗

The impact of baryonic potentials on the gravothermal evolution of self-interacting dark matter haloes

The presence of a central baryonic potential can have a significant impact on the gravothermal evolution of self-interacting dark matter (SIDM) haloes. We extend a semi-analytical fluid model to incorporate the influence of a static baryonic potential and calibrate it using controlled N-body simulations. We construct benchmark scenarios with varying baryon concentrations and different SIDM models, including constant and velocity-dependent self-interacting cross-sections. The presence of the baryonic potential induces changes in SIDM halo properties, including central density, core size, and velocity dispersion, and it accelerates the halo’s evolution in both expansion and collapse phases. Furthermore, we observe a quasi-universality in the gravothermal evolution of SIDM haloes with the baryonic potential, resembling a previously known feature in the absence of the baryons. By appropriately rescaling the physical quantities that characterize the SIDM haloes, the evolution of all our benchmark cases exhibits remarkable similarity. In conclusion, our findings offer a framework for testing SIDM predictions using observations of galactic systems where baryons play a significant dynamical role.

79 ASTRONOMY AND ASTROPHYSICS↗

Applying a Template of Expected Uncertainties to Updating 239 Pu(n,f) Cross-section Covariances in the Neutron Data Standards Database

Templates of uncertainties expected in specific measurement types were recently developed. One aim of these templates is to help evaluators in identifying (1) missing or suspiciously low uncertainties and (2) missing correlations between uncertainties of the same and different experiments, when estimating covariances for experimental data employed in their evaluations. These templates also provide realistic estimates of standard deviations and correlations for a particular uncertainty source and measurement type that can be used by evaluators in situations where they are not supplied by the experimenters. This information allows for a more comprehensive uncertainty analysis across all measurements considered in an evaluation and, thus, more realistic evaluated covariances. Here, in this work, we extend a template that is applicable to uncertainties expected in neutron-induced fission, (n,f), cross-section measurements. It is applied to improving covariances of 239 Pu(n,f) cross-section measurements in the database underlying the Neutron Data Standards evaluations. This particular example was chosen since this evaluation is primarily based on experimental information. Also, some uncertainties of individual 239 Pu(n,f) cross-section experiments in this database were suspected to be underestimated. The evaluated uncertainties obtained after updating the covariances in the database by means of the template indeed do increase compared to their original values. Even more importantly, the evaluated mean values change noticeably. These modified cross sections impact application calculations significantly, as is demonstrated by employing them in simulations of the effective neutron multiplication factor for a few selected critical assemblies. However, this updated evaluated 239 Pu(n,f) cross section should not be interpreted as the final one that should replace values of the current Neutron Data Standards project. Evaluations for the Neutron Data Standards of the 239 Pu(n,f) cross section must be linked to many other observables included in the associated database, most notably to cross sections for 235 U(n,f), but also to those for 10 B(n, α ), 6 Li(n,t), 238 U(n,f), and 238 U(n, γ ), because of included measurements of the 239 Pu(n,f) cross section that appear as ratios to these reactions. Some of these other reactions are correlated to further observables in the database. Hence, updating uncertainties of data sets of any of these observables can potentially impact the 239 Pu(n,f) cross section. Uncertainties for all measurements of these linked physical observables have to be updated before a comprehensive evaluation of the 239 Pu(n,f) cross section and its corresponding uncertainties can be provided.

239Pu Neutron-induced fission cross-section↗

High-Precision Characterization of Seismicity from the 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption

The earthquake swarm accompanying the January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate-magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera-forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface-wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate-period Rayleigh- and Love-wave cross-correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time-dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude ($M_w$) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an $M_w$ 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. As a result, our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface-wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

58 GEOSCIENCES↗