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At least 199 records · Page 11

Stellar Neutrino Emission across the Mass–Metallicity Plane

We explore neutrino emission from nonrotating, single-star models across six initial metallicities and 70 initial masses from the zero-age main sequence to the final fate. Overall, across the mass spectrum, we find metal-poor stellar models tend to have denser, hotter, and more massive cores with lower envelope opacities, larger surface luminosities, and larger effective temperatures than their metal-rich counterparts. Across the mass–metallicity plane we identify the sequence (initial CNO → 14 N → 22 Ne → 25 Mg → 26 Al → 26 Mg → 30 P → 30 Si) as making primary contributions to the neutrino luminosity at different phases of evolution. For the low-mass models we find neutrino emission from the nitrogen flash and thermal pulse phases of evolution depend strongly on the initial metallicity. For the high-mass models, neutrino emission at He-core ignition and He-shell burning depends strongly on the initial metallicity. Antineutrino emission during C, Ne, and O burning shows a strong metallicity dependence with 22 Ne(α, n) 25 Mg providing much of the neutron excess available for inverse-β decays. We integrate the stellar tracks over an initial mass function and time to investigate the neutrino emission from a simple stellar population. We find average neutrino emission from simple stellar populations to be 0.5–1.2 MeV electron neutrinos. Lower metallicity stellar populations produce slightly larger neutrino luminosities and average β decay energies. This study can provide targets for neutrino detectors from individual stars and stellar populations. We provide convenient fitting formulae and open access to the photon and neutrino tracks for more sophisticated population synthesis models.

79 ASTRONOMY AND ASTROPHYSICS↗

Exact and Model Exchange-Correlation Potentials for Open-Shell Systems

The conventional approaches to the inverse density functional theory problem typically assume nondegeneracy of the Kohn–Sham (KS) eigenvalues, greatly hindering their use in open-shell systems. Here, we present a generalization of the inverse density functional theory problem that can seamlessly admit degenerate KS eigenvalues. Additionally, we allow for fractional occupancy of the Kohn–Sham orbitals to also handle noninteracting ensemble-v-representable densities, as opposed to just noninteracting pure-v-representable densities. We present the exact exchange-correlation (XC) potentials for six open-shell systems–four atoms (Li, C, N, and O) and two molecules (CN and CH 2 )–using accurate ground-state densities from configuration interaction calculations. We compare these exact XC potentials with model XC potentials obtained using nonlocal (B3LYP, SCAN0) and local/semilocal (SCAN, PBE, PW92) XC functionals. Although the relative errors in the densities obtained from these DFT functionals are of $O$(10 –3 to 10 –2 ), the relative errors in the model XC potentials remain substantially large–$O$(10 –1 to 10 0 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic Structure, Optical Properties, and Photoelectrochemical Activity of Sn-Doped Fe 2 O 3 Thin Films

Hematite (Fe 2 O 3 ) is a well-known oxide semiconductor suitable for photoelectrochemical (PEC) water splitting and industry gas sensing. It is widely known that Sn doping of Fe 2 O 3 can enhance the device performance, yet the underlying mechanism remains elusive. In this work, we determine the relationship between electronic structure, optical properties and PEC activity of Sn doped Fe 2 O 3 by studying highly crystalline, well-controlled thin films prepared by pulsed laser deposition (PLD). We show that Sn doping substantially increases the n-type conductivity of Fe 2 O 3 , and the conduction mechanism is better described by small-polaron hoping (SPH) model. Only 0.2% Sn doping significantly reduce the activation energy barrier for SPH conduction from at least 0.5 eV for undoped Fe 2 O 3 to 0.14 eV for doped ones. A combination of X-ray photoemission, X-ray absorption spectroscopy and DFT calculations reveals the Fermi level gradually shifts toward the conduction band minimum with Sn doping. A localized Fe 2+ like gap state is observed at the top of valence band, accounting for the SPH conduction. Interestingly, in contrast to the literature, we find that only 0.2% Sn doping in Fe 2 O 3 significantly improves the PEC activity, while more Sn decreases it. The improved PEC activity is partially attributed to an increased band bending potential which facilitates the charge separation at space charge region. The reduced activation energy barrier for SPH will facilitate the transport of photo-excited carriers for the enhanced PEC, which is of interest for further carrier dynamics study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

Abstract Atomistic simulation has a broad range of applications from drug design to materials discovery. Machine learning interatomic potentials (MLIPs) have become an efficient alternative to computationally expensive ab initio simulations. For this reason, chemistry and materials science would greatly benefit from a general reactive MLIP, that is, an MLIP that is applicable to a broad range of reactive chemistry without the need for refitting. Here we develop a general reactive MLIP (ANI-1xnr) through automated sampling of condensed-phase reactions. ANI-1xnr is then applied to study five distinct systems: carbon solid-phase nucleation, graphene ring formation from acetylene, biofuel additives, combustion of methane and the spontaneous formation of glycine from early earth small molecules. In all studies, ANI-1xnr closely matches experiment (when available) and/or previous studies using traditional model chemistry methods. As such, ANI-1xnr proves to be a highly general reactive MLIP for C, H, N and O elements in the condensed phase, enabling high-throughput in silico reactive chemistry experimentation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of frequency detuning on Brillouin lasing in microcavities

We have theoretically investigated Brillouin lasing in microcavities in the case when the Brillouin shift and the intermode spacing of the microcavity do not coincide. It is shown that, despite the rise of the lasing threshold, a significant increase in the Brillouin signal intensity can be achieved in this case compared to the resonance one. A necessary condition for this effect is to select an optimal value of detuning of the pump radiation frequency from the frequency of the corresponding microcavity mode. The result of increasing the lasing threshold is also a narrowing of the Brillouin signal lasing range in the nonresonant case, which leads to a decrease in the signal noise level provided the detuning value is optimally selected. Analytical calculations are confirmed by the results of numerical modelling. (paper)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

Formation kinetics and thermodynamic stability of the Aurivillius compounds in Bi 4 Ti 3 O 12 –BiFeO 3 system

Abstract The Aurivillius compounds in the Bi 2 O 3 –Fe 2 O 3 –TiO 2 system, combining ferroelectric, semiconducting, and ferromagnetic properties, have attracted particular interest. Formation kinetics and thermodynamic stability are the fundamental knowledge needed for modeling and predicting the temporal microstructure and property evolution during materials processing but have not yet been addressed by quantitative experimental measurement. This article focuses on the Bi n +1 Fe n –3 Ti 3 O 3 n +3 Aurivillius compounds on the Bi 4 Ti 3 O 12 –BiFeO 3 tie‐line to elucidate the mechanisms and thermodynamic controls responsible for phase formation of compounds with various perovskite‐like layers. Five high‐purity Aurivillius compounds Bi 4 Ti 3 O 12 , Bi 5 FeTi 3 O 15 , Bi 6 Fe 2 Ti 3 O 18 , Bi 7 Fe 3 Ti 3 O 21 , and Bi 8 Fe 4 Ti 3 O 24 with integer n = 3–7 values were synthesized and their phase transformation properties and enthalpies of formation were studied by X‐ray diffraction in situ, high temperature differential scanning calorimetry, and high temperature oxide melt solution calorimetry. Thermodynamic stability of the compounds decreases with increasing n , and formation kinetics gradually slow down, demonstrating the inherent difficulty to synthesize pure Aurivillius compounds with n larger than 8. This difficulty was confirmed by an impurity phase coexisting with Bi 9 Fe 5 Ti 3 O 27 .

Gong, Weiping↗

RF surface resistance tuning of superconducting niobium via thermal diffusion of native oxide

Recently, Nb superconducting radio frequency cavities vacuum heat treated between 300 and 400°C for a few hours have exhibited very high quality factors (~5 × 10 10 at 2.0 K). Secondary ion mass spectrometry measurements of O, N, and C show that this enhancement in RF surface conductivity is primarily associated with interstitial O alloying via dissolution and diffusion of the native oxide. We use a theory of oxide decomposition and O diffusion to quantify previously unknown parameters crucial in modeling this process. RF measurements of a vacuum heat-treated Nb superconducting radio frequency cavity confirm the minimized surface resistance (higher Q 0 ) previously expected only from 800 °C diffusive alloying with N.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic phase diagram of a two-orbital model for bilayer nickelates with varying doping

Motivated by the recently discovered high-T c bilayer nickelate superconductor La 3⁢ Ni 2 ⁢O 7 , we comprehensively research a bilayer 2×2×2 cluster for different electronic densities n by using the Lanczos method. We also employ the random-phase approximation to quantify the first magnetic instability with increasing Hubbard coupling strength, also varying n. Based on the spin structure factor S(q), we have obtained a rich magnetic phase diagram in the plane defined by n and U/W, at fixed Hund coupling, where U is the Hubbard strength and W the bandwidth. We have observed numerous states, such as A-AFM, Stripes, G-AFM, and C-AFM. At half-filling, n=2 (two electrons per Ni site, corresponding to N=16 electrons), the canonical superexchange interaction leads to a robust G-AFM state (π,π,π) with antiferromagnetic couplings both in-plane and between layers. By increasing or decreasing electronic densities, ferromagnetic tendencies emerge from the “half-empty” and “half-full” mechanisms, leading to many other interesting magnetic tendencies. In addition, the spin-spin correlations become weaker both in the hole or electron doping regions compared with half-filling. At n=1.5 (or N=12), density corresponding to La 3 ⁢Ni 2 ⁢O 7 , we obtained the “Stripe 2” ground state (antiferromagnetic coupling in one in-plane direction, ferromagnetic coupling in the other, and antiferromagnetic coupling along the z axis) in the 2×2×2 cluster. In addition, we obtained a much stronger AFM coupling along the z axis than the magnetic coupling in the xy plane. The random-phase approximation calculations with varying n give very similar results as Lanczos, even though both techniques are based on quite different procedures. Additionally, a state with q/π=(0.6,0.6,1) close to the E-phase wavevector is found in our RPA calculations by slightly reducing the filling to n=1.25, possibly responsible for the E-phase SDW recently observed in experiments. In conclusion, our predictions can be tested by chemically doping La 3 ⁢Ni 2 ⁢O 7 .

36 MATERIALS SCIENCE↗

Exploring the Impact of Active Site Structure on the Conversion of Methane to Methanol in Cu‐Exchanged Zeolites

Abstract In the past, Cu‐oxo or ‐hydroxy clusters hosted in zeolites have been suggested to enable the selective conversion of methane to methanol, but the impact of the active site's stoichiometry and structure on methanol production is still poorly understood. Herein, we apply theoretical modeling in conjunction with experiments to study the impact of these two factors on partial methane oxidation in the Cu‐exchanged zeolite SSZ‐13. Phase diagrams developed from first‐principles suggest that Cu‐hydroxy or Cu‐oxo dimers are stabilized when O 2 or N 2 O are used to activate the catalyst, respectively. We confirm these predictions experimentally and determine that in a stepwise conversion process, Cu‐oxo dimers can convert twice as much methane to methanol compared to Cu‐hydroxyl dimers. Our theoretical models rationalize how Cu‐di‐oxo dimers can convert up to two methane molecules to methanol, while Cu‐di‐hydroxyl dimers can convert only one methane molecule to methanol per catalytic cycle. These findings imply that in Cu clusters, at least one oxo group or two hydroxyl groups are needed to convert one methane molecule to methanol per cycle. This simple structure–activity relationship allows to intuitively understand the potential of small oxygenated or hydroxylated transition metal clusters to convert methane to methanol.

Chemistry↗

Underlying simplicity of 5f unoccupied electronic structure

Using a simple empirical model based upon the bremsstrahlung isochromat spectroscopy of elemental Th, it is possible to explain the recent high energy resolution fluorescence detection measurements of UF 4 (n = 2) and UCd 11 (n = 3) as well as the new inverse photoelectron spectroscopy of Pu 2 O 3 (n = 5), where n is the 5f occupation number. Furthermore, a critical issue in this analysis is the assumption that the Th 5f states are essentially empty, which will be confirmed both experimentally and computationally. Thus, for 5f systems, this simple model provides a unified and consistent picture of 5f unoccupied density of states in simple, localized systems, as the 5f occupation varies in the early part of the series, for n = 0, 2, 3, and 5.

36 MATERIALS SCIENCE↗

High pressure ammonia/methanol oxidation up to 100 atm

Here, high pressure ammonia/methanol oxidation and NOx formations were investigated using a recently developed supercritical pressure jet-stirred reactor (SP-JSR) at 20 and 100 atm with temperatures between 550 and 950 K and equivalence ratios of 0.138 and 1.15. The experimental results show that NH 3 oxidation at high pressure is significantly accelerated by the active OH radicals produced from CH 3 OH oxidation. Furthermore, the kinetic interactions between NH 3 and CH 3 OH are governed mainly by the reactions CH 3 OH + NH 2 = CH 2 OH + NH 3 , CH 3 OH + NH 2 = CH 3 O + NH 3 , and CH 2 O + NH 2 = HCO + NH 3 . A HP-Mech model for high-pressure NH 3 /CH 3 OH oxidation was developed in this study. It consists of the most recent NH 3 and CH 3 OH models including some new reactions and updated rate constants from the literature as well as NH 3 -CH 3 OH interactions where rate constants of CH 3 OH + NH 2 = CH 2 OH + NH 3 , CH 3 OH + NH 2 = CH 3 O + NH 3 , NH 2 + CH 2 O = NH 3 + HCO, and NH 2 + CH 2 O = NH 2 CHO + H were theoretically calculated in this study. Our model with these updates improves the prediction for the measured N 2 O/NO x temperature dependence at 100 atm. In addition, the reaction pathway and sensitivity analysis show that N 2 O/NO x /HONO interactions with HO 2 are very important, especially for a fuel-lean mixture at 100 atm. The HONO mole fraction for the fuel-lean mixture at 100 atm was then measured by off-axis integrated cavity output spectroscopy (ICOS) at wavenumber of 6638.26 cm -1 . The experimental data show a significant HONO formation at intermediate temperature that is strongly underpredicted by numerical simulation at 100 atm. Therefore, the HONO related reactions with notable uncertainty at high pressure such as NO + OH (+M) = HONO (+M) and H 2 NO + NO 2 = HONO + HNO need deeper exploration in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of three-body forces on elastic nucleon-nucleus scattering observables

In a previous series of papers we investigated the domain of applicability of chiral potentials to the construction of a microscopic optical potential (OP) for elastic nucleon-nucleus scattering. The OP was derived at the first order of the spectator expansion of the Watson multiple scattering theory and its final expression was a folding integral between the nucleon-nucleon ( N N ) t matrix and the nuclear density of the target. In the calculations N N and three-nucleon ( 3 N ) chiral interactions were used for the target density and only the N N interaction for the N N t matrix. The purpose of this study is to achieve another step towards the calculation of a more consistent OP introducing the 3 N force also in the dynamic part of the OP. The full treatment of the 3 N interaction is beyond our present capabilities. Thus, here it is approximated with a density dependent N N interaction obtained after the averaging over the Fermi sphere. In practice, in our model the 3 N force acts as a medium correction of the bare N N interaction used to calculate the t matrix. Even if the 3 N force is treated in an approximate way, this method naturally extends our previous model of the OP and allows a direct comparison of our present and previous results. We consider as case studies the elastic scattering of nucleons off C 12 and O 16 . We present results for the differential cross section and the spin observables for different values of the projectile energy. From the comparison with the experimental data and with the results of our previous model we assess the importance of the 3 N interaction in the dynamic part of the OP. Conclusions: Our analysis indicates that the contribution of the 3 N force in the t matrix is small for the differential cross section and it is sizable for the spin observables, in particular, for the analyzing power. We find that the two-pion exchange term is the major contributor to the 3 N force. A chiral expansion order-by-order analysis of the scattering observables confirms the convergence of our results at the next-to-next-to-next-to-leading-order, as already established in our previous work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Muon capture on Li 6 , C 12 , and O 16 from ab initio nuclear theory

Muon capture on nuclei is one of the most promising probes of the nuclear electroweak current driving the yet-hypothetical neutrinoless double-beta (0νββ) decay. Both processes involve vector and axial-vector currents at finite momentum transfer, q ~ 100 MeV, as well as the induced pseu doscalar and weak-magnetism currents. Comparing measured muon-capture rates with reliable ab initio nuclear-theory predictions could help us validate these currents. To this end, we compute partial muon-capture rates for 6 Li, 12 C and 16 O, feeding the ground and excited states in 6 He, 12 B and 16 N, using ab initio no-core shell model with two- and three-nucleon chiral interactions. Here, we remove the spurious center-of-mass motion by introducing translationally invariant operators and approximate the effect of hadronic two-body currents by Fermi-gas model. We solve the bound-muon wave function from the Dirac wave equations in the Coulomb field created by a finite nucleus. We find that the computed rates to the low-lying states in the final nuclei are in good agreement with the measured counterparts. We highlight sensitivity of some of the transitions to the sub-leading three-nucleon interaction terms. We also compare summed rates to several tens of final states with the measured total capture rates and note that we slightly underestimate the total rate with this simple approach due to limited range of excitation energies

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Baryonic Content of Galaxies Mapped by MaNGA and the Gas Around Them

We analyze the cool gas in and around 14 nearby galaxies (at z < 0.1) mapped with the Sloan Digital Sky Survey IV MaNGA survey by measuring absorption lines produced by gas in spectra of background quasars/active galactic nuclei at impact parameters of 0–25 effective radii from the galactic centers. Using Hubble Space Telescope/Cosmic Origins Spectrograph, we detect absorption at the galactic redshift and measure or constrain column densities of neutral (H I, N I, O I, and Ar I), low-ionization (Si II, S II, C II, N II, and Fe II), and high-ionization (Si III, Fe III, N v, and O vI) species for 11 galaxies. We derive the ionization parameter and ionization-corrected metallicity using cloudy photoionization models. The H i column density ranges from ~1013 to ~1020 cm-2 and decreases with impact parameter for r ≳ Re. Galaxies with higher stellar mass have weaker H I absorption. Comparing absorption velocities with MaNGA radial velocity maps of ionized gas line emissions in galactic disks, we find that the neutral gas seen in absorption corotates with the disk out to ~10 R e . Sight lines with lower elevation angles show lower metallicities, consistent with the metallicity gradient in the disk derived from MaNGA maps. Higher-elevation angle sight lines show higher ionization, lower H I column density, supersolar metallicity, and velocities consistent with the direction of galactic outflow. Our data offer the first detailed comparisons of circumgalactic medium (CGM) properties (kinematics and metallicity) with extrapolations of detailed galaxy maps from integral field spectroscopy; similar studies for larger samples are needed to more fully understand how galaxies interact with their CGM.

79 ASTRONOMY AND ASTROPHYSICS↗

Uncertainty quantification for Bayesian active learning in rupture life prediction of ferritic steels

Abstract Three probabilistic methodologies are developed for predicting the long-term creep rupture life of 9–12 wt%Cr ferritic-martensitic steels using their chemical and processing parameters. The framework developed in this research strives to simultaneously make efficient inference along with associated risk, i.e., the uncertainty of estimation. The study highlights the limitations of applying probabilistic machine learning to model creep life and provides suggestions as to how this might be alleviated to make an efficient and accurate model with the evaluation of epistemic uncertainty of each prediction. Based on extensive experimentation, Gaussian Process Regression yielded more accurate inference ( $$Pearson\;correlation\;coefficent> 0.95$$ P e a r s o n c o r r e l a t i o n c o e f f i c e n t > 0.95 for the holdout test set) in addition to meaningful uncertainty estimate (i.e., coverage ranges from 94 to 98% for the test set) as compared to quantile regression and natural gradient boosting algorithm. Furthermore, the possibility of an active learning framework to iteratively explore the material space intelligently was demonstrated by simulating the experimental data collection process. This framework can be subsequently deployed to improve model performance or to explore new alloy domains with minimal experimental effort.

20 FOSSIL-FUELED POWER PLANTS↗

The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

Abstract Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based general-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data diversity, we visualize it with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5 M density functional theory calculations, while the ANI-1ccx data set contains 500 k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM calculated properties for the chemical elements C, H, N, and O are provided: energies, atomic forces, multipole moments, atomic charges, etc. We provide this data to the community to aid research and development of ML models for chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗