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New high-energy cosmic-ray Be data indicate that the ratio Be-7/Be drops by approximately a factor of two between 200 and 1500 MeV/nucleon. This result may provide a severe constraint for theories of cosmic-ray acceleration.
Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory; however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked. Epistemic uncertainties arising from training the same network multiple times for an ensemble of initial weight sets offer a first insight into the confidence of machine learning predictions, but they often come with a high computational cost. Instead, we apply a single-model uncertainty quantification method called Δ-UQ that gives epistemic uncertainties with one-time training. Here, we demonstrate our approach on a two-feature model of nuclear binding energies per nucleon with proton and neutron number pairs as inputs. We show that Δ-UQ can produce reliable and self-consistent epistemic uncertainty estimates and can be used to assess the degree of confidence in predictions made with deep neural networks.
The spin-state energetics of six Fe(II) molecular complexes are computed using the linear-response Hubbard U approach within DFT. The adiabatic energy differences, ΔE H-L , between the high-spin (S = 2) and the low-spin (S = 0) states are computed and compared with accurate-coupled cluster-corrected CASPT2 results. We show that DFT+U fails in correctly capturing the ground state for strong-field ligands yielding ΔE H-L that are almost constant throughout the molecular series. This bias toward high spin together with the metal/ligand charge transfer upon U correction are here quantified and explained using molecular orbital diagrams involving both σ- and π-bonding interactions. Furthermore, with increasing ligand-field strengths this bias also increases owing to the stronger molecular character of the metal/ligand Kohn–Sham orbitals thus resulting in large deviations from the reference larger than 4 eV. Smaller values of U can be employed to mitigate this effect and recover the right energetics.
Reactor neutrino experiments have seen major improvements in precision in recent years. With the experimental uncertainties becoming lower than those from theory, carefully considering all sources of $\bar{ν}$ e is important when making theoretical predictions. One source of νe that is often neglected arises from the irradiation of the nonfuel materials in reactors. The $\bar{ν}$ e rates and energies from these sources vary widely based on the reactor type, configuration, and sampling stage during the reactor cycle and have to be carefully considered for each experiment independently. In this article, we present a formalism for selecting the possible $\bar{ν}$ e sources arising from the neutron captures on reactor and target materials. We apply this formalism to the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, the $\bar{ν}$ e source for the the Precision Reactor Oscillation and Spectrum Measurement (PROSPECT) experiment. Overall, we observe that the nonfuel $\bar{ν}$ e contributions from HFIR to PROSPECT amount to 1% above the inverse beta decay threshold with a maximum contribution of 9% in the 1.8–2.0 MeV range. Nonfuel contributions can be particularly high for research reactors like HFIR because of the choice of structural and reflector material in addition to the intentional irradiation of target material for isotope production. We show that typical commercial pressurized water reactors fueled with low-enriched uranium will have significantly smaller nonfuel $\bar{ν}$ e contribution.
The Galileon theory is a prototypical effective field theory that incorporates the Vainshtein screening mechanism—a feature that arises in some extensions of general relativity, such as massive gravity. The Vainshtein effect requires that the theory contain higher order derivative interactions, which results in Galileons, and theories like them, failing to be technically well posed. While this is not a fundamental issue when the theory is correctly treated as an effective field theory, it nevertheless poses significant practical problems when numerically simulating this model. These problems can be tamed using a number of different approaches: introducing an active low-pass filter and/or constructing a UV completion at the level of the equations of motion, which controls the high momentum modes. These methods have been tested on cubic Galileon interactions, and have been shown to reproduce the correct low-energy behavior. Here we show how the numerical UV-completion method can be applied to quartic Galileon interactions, and present the first simulations of the quartic Galileon model using this technique. We demonstrate that our approach can probe physics in the regime of the effective field theory in which the quartic term dominates, while successfully reproducing the known results for cubic interactions. Published by the American Physical Society 2024
The thermocatalytic reduction of CO2 by H2 often proceeds via two competing reaction mechanisms—the reverse water gas shift reaction (rWGSR, CO2 + H2 ⇌ CO + H2O) and methanation (CO2 + 4H2 ⇌ CH4 + 2H2O). Atomically dispersed Rh1 catalysts on TiO2 show high selectivity toward the rWGSR compared with larger Rh nanoclusters, but the origin of this size-dependent selectivity has not been fully explained. Here we report density functional theory (DFT) calculations and microkinetic simulations that clarify the Rh1 active sites and rWGSR pathway on anatase TiO2(101), as well as the high rWGSR selectivity of Rh1 compared with supported Rhx (x = 2–8 atoms) nanoclusters. DFT-computed formation energies, vibrational frequency analysis, and microkinetic modeling suggest three plausible active sites: Rh1 on titania (Rh1/TiO2(101)), Rh1 with a nearby hydroxyl group (Rh1OH/TiO2(101)), and Rh1 near an oxygen vacancy at a three-fold coordinated site (Rh1 near O3cvac). Predicted turnover frequencies and apparent activation barriers for Rh1 indicate a faster reaction involving CO2 dissociation assisted by a support oxygen vacancy via Rh1 near O3cvac, as well as slower reactions involving Rh1OH/TiO2(101) or Rh1/TiO2(101) through a COOH intermediate. Furthermore, these Rh1 sites are selective toward CO rather than CH4 because of the weak adsorption of CO, large barrier for C-O bond dissociation, and the lack of nearby metal sites for H2 dissociation, in contrast to Rhx nanoclusters, including Rh2 dimers.
Accurate prediction of adsorption energies on heterogeneous catalyst surfaces is crucial to predicting reactivity and screening materials. Adsorption linear scaling relations have been developed extensively but often lack accuracy and apply to one adsorbate and a single binding site type at a time. These facts undermine their ability to predict structure sensitivity and optimal catalyst structure. Using machine learning on nearly 300 density functional theory calculations, we demonstrate that generalized coordination number scaling relations hold well for oxygen- and high-valency carbon-binding species but fail for others. Here we reveal that the valency and the electronic coupling of a species with the surface, along with the site type and its coordination environment, are critical for small species adsorption. The model simultaneously predicts the adsorption energy and preferred site and significantly outperforms linear scalings in accuracy. It can expose the structure sensitivity of chemical reactions and enable enhanced catalyst activity via engineering particle shape and facet defects. The generality of our methodology is validated by training the model with transition metal data and transferring it to predict adsorption energies on single-atom alloys.
In order to further improve the accuracy of rovibrational IR line lists generated from the “Best Theory +Reliable High-resolution Experiment” (BTRHE) strategy from 0.01-0.05 cm-1, or 300-1500 MHz, to ~10 MHz, we explore the current limits of the Data-Model-Theory synergy by examining the accuracy and consistency of existing data, then propose that “hot” bands in microwave (MW) spectra is the solution we need for future enhancements. The Ames SO2 J=0-20 rovibrational energy levels computed on the semi-empirically refined Ames-2 potential energy surface (PES) are fit to the Effective Hamiltonian (EH) model regularly used in the experimental infrared (IR) analysis for SO2 isotopologues. In the fitted EH(Ames) model, the rotational constants A/B/C and all 5 quartic centrifugal distortion constants display clear, systematic, and consistent patterns along the vibrational state energy or quanta. Such consistent patterns may facilitate the vibrational assignments for MW hot bands and extract more information from high temperature MW spectra. Some EH(Expt) analyses were carried out with the lowest order Coriolis Coupling term, C1. Their constants should not be directly compared with other EH(Expt) and EH(Ames) results. After excluding them, our = EH(Ames)- EH(Expt) analyses for 5 isotopologues (626, 636, 646, 628 and 828) indicates some loss of accuracy and consistency starting from vibrational states as low as 22 or 1000 cm-1. Some EH parameters, e.g. K, may have relative deviations as large as 50-100% and totally lose any recognizable patterns. This simply means that current EH(Expt) models do not have the system-wide consistency we need to further refine the EH(Ames) and Ames rovibrational IR line lists. A large part of such defects are probably inherited from the limited precision of experimental line positions, i.e. 1E-3 ~ 1E-4 cm-1, or 3-30 MHz. This is confirmed in a series of truncation tests using the Ames data. Although the EH(Ames) consistency may help identify unreliable rovibrational EH(Expt) parameters, and make reliable predictions for minor isotopologues and unobserved vibrational bands, we believe only the highly accurate “hot” MW transitions can provide real enhancements for EH(Expt) accuracy and consistency. “Hot” MW spectra should play a more significant role in the future synergy of Data, Model, and Theory in the field of rovibrational IR studies.
Cu(I) active sites in metalloproteins are involved in O 2 activation, but their O 2 reactivity is difficult to study due to the Cu(I) d 10 closed shell which precludes the use of conventional spectroscopic methods. Kβ X-ray emission spectroscopy (XES) is a promising technique for investigating Cu(I) sites as it detects photons emitted by electronic transitions from occupied orbitals. Here, we demonstrate the utility of Kβ XES in probing Cu(I) sites in model complexes and a metalloprotein. Using Cu(I)Cl, emission features from double-ionization (DI) states are identified using varying incident X-ray photon energies, and a reasonable method to correct the data to remove DI contributions is presented. Kβ XES spectra of Cu(I) model complexes, having biologically relevant N/S ligands and different coordination numbers, are compared and analyzed, with the aid of density functional theory (DFT) calculations, to evaluate the sensitivity of the spectral features to the ligand environment. While the low-energy Kβ 2,5 emission feature reflects the ionization energy of ligand np valence orbitals, the high-energy Kβ 2,5 emission feature corresponds to transitions from molecular orbitals (MOs) having mainly Cu 3d character with the intensities determined by ligand-mediated d–p mixing. A Kβ XES spectrum of the Cu(I) site in preprocessed galactose oxidase (GO pre ) supports the 1Tyr/2His structural model that was determined by our previous X-ray absorption spectroscopy and DFT study. Finally, the high-energy Kβ 2,5 emission feature in the Cu(I)-GO pre data has information about the MO containing mostly Cu 3d x 2 –y 2 character that is the frontier molecular orbital (FMO) for O 2 activation, which shows the potential of Kβ XES in probing the Cu(I) FMO associated with small-molecule activation in metalloproteins.
As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.
Electrocatalytic CO 2 reduction into value-added multicarbon products offers a means to close the anthropogenic carbon cycle using renewable electricity. However, the unsatisfactory catalytic selectivity for multicarbon products severely hinders the practical application of this technology. In this paper, we report a cascade AgCu single-atom and nanoparticle electrocatalyst, in which Ag nanoparticles produce CO and AgCu single-atom alloys promote C-C coupling kinetics. As a result, a Faradaic efficiency (FE) of 94 ± 4% toward multicarbon products is achieved with the as-prepared AgCu single-atom and nanoparticle catalyst under ~720 mA cm -2 working current density at -0.65 V in a flow cell with alkaline electrolyte. Density functional theory calculations further demonstrate that the high multicarbon product selectivity results from cooperation between AgCu single-atom alloys and Ag nanoparticles, wherein the Ag single-atom doping of Cu nanoparticles increases the adsorption energy of *CO on Cu sites due to the asymmetric bonding of the Cu atom to the adjacent Ag atom with a compressive strain.
The discovery of superconductivity in hole-doped infinite layer nickelates, RNiO 2 (R = Nd, Pr, La) has resulted in sustained interest in the field. A definitive picture of low-energy many-body states has not yet emerged. Here we provide insights into the low-energy physics, based on our embedded dynamical mean-field theory calculations, and propose a correlation (U)-temperature (T) phase diagram. The key features are a low-T Fermi liquid (FL) phase, a high-T Curie-Weiss regime, and an antiferromagnetic phase in a narrow U-T region. We associate the onset of the FL phase with partial screening of Ni-d moments; however, full screening occurs at lower temperatures. This may be related to insufficiency of conduction electrons to effectively screen the Ni-d moments, suggestive of Nozieres Exhaustion Principle. Our results suggest that RNiO 2 are in the paramagnetic state, close to an antiferromagnetic dome, making magnetic fluctuations feasible. This may be consequential for superconductivity.
Thermal density functional theory is commonly used in simulations of warm dense matter, a highly energetic phase characterized by substantial thermal effects and by correlated electrons demanding quantum mechanical treatment. Methods that account for temperature dependence, such as Mermin–Kohn–Sham finite-temperature density functional theory and free energy density functional theory, are now employed with more regularity and available in many standard code packages. However, approximations from zero-temperature density functional theory are still often used in temperature-dependent simulations using thermally weighted electronic densities as an input to exchange–correlation functional approximations, a practice known to miss temperature-dependent effects in the exchange–correlation free energy of these systems. Here, in this work, the temperature-dependent adiabatic connection is demonstrated and analyzed using a well-known parameterization of the uniform electron gas free energy. Useful tools based on this formalism for analyzing and constraining approximations of the exchange–correlation at zero temperature are leveraged for the finite-temperature case. Inspired by the Lieb–Oxford inequality, which provides a lower bound for the ground-state exchange–correlation energy, bounds for the exchange–correlation at finite temperatures are approximated for various degrees of electronic correlation.
Exciplexes are excited-state complexes formed as a result of partial charge transfer from the donor to the acceptor species when one moiety of the donor–acceptor pair is electronically excited. The arene–amine exciplex formed between oligo-(p-phenylene) (OPP) and triethylamine (TEA) is of interest in the catalytic photoreduction of CO2 because it can compete with complete electron transfer to the OPP catalyst. Therefore, formation of the exciplex can hinder the generation of a radical anion OPP·− necessary for subsequent CO2 reduction. We report an implementation of a workflow automating quantum-chemistry calculations that generate and characterize an ensemble of structures to represent this exciplex state. We use FireWorks, Pymatgen, and Custodian Python packages for high-throughput ensemble generation. The workflow includes time-dependent density functional theory optimization, verification of excited-state minima, and exciplex characterization with natural transition orbitals, exciton analysis, excited-state Mulliken charges, and energy decomposition analysis. Fluorescence spectra computed for these ensembles using Boltzmann-weighted contributions of each structure agree better with experiment than our previous calculations based on a single representative exciplex structure [Kron et al., J. Phys. Chem. A 126, 2319–2329 (2022)]. The ensemble description of the exciplex state also reproduces an experimentally observed red shift of the emission spectrum of [OPP-4–TEA]* relative to [OPP-3–TEA]*. The workflow developed here streamlines otherwise labor-intensive calculations that would require significant user involvement and intervention.
Here, a theoretically highly efficient mechanism, operating at high laser intensities and powers, is identified for spectral transferring huge laser energies to shorter ultraviolet and x-ray wavelengths. With megajoule laser energies currently available at near-optical wavelengths, this transfer would, in theory, enable megajoule x-ray lasers, a huge advance over the millijoules x-ray pulses produced now. In fact, enabling even kilojoule x-ray lasers would still be a fantastic advance, and a more likely achievable one, considering practical experimental inefficiencies.
Here we report ab initio calculations of the electronic and vibrational properties in CuPb 9 (PO 4 ) 6 O, including the electron-phonon coupling strength via strong-coupling Migdal-Eliashberg theory. We verify the presence of appealing flat electronic bands near the Fermi level, a strong hybridization between the Cu 3d and O 2p states, and soft low-energy phonons, which can suggest high-temperature superconducting behavior. However, the electron-phonon coupling strength appears insufficient to overcome the Coulomb repulsion between an electron pair and thus does not support high-temperature superconductivity in CuPb 9 (PO 4 ) 6 O via the conventional electron-phonon Migdal-Eliashberg mechanism. Even neglecting Coulomb repulsion of the electron pair we find this electron-phonon coupling suggests a superconducting transition temperature of less than 2 K.
Radio pulsars provide unparalleled opportunities for making measurements of astrophysically interesting phenomena. The author concentrates on two particular applications of high precision timing observations of pulsars: tests of relativistic gravitation theory using the binary pulsar 1913+16, and tests of cosmological models using timing data from millisecond pulsars. New upper limits are presented for the energy density of a cosmic background of low frequency gravitational radiation.
Magnetospheric research is a relatively new area in the study of the Earth's environment. The present report attempts to overview past and future research on this topic. The goals of magnetospheric research are numerous, and include: understanding large scale magnetospheres of the Earth and other planets; understanding the plasma physical processes operating within the various magnetospheres; to understand how mass, energy and momentum are transmitted from the solar wind; to understand quantitatively the coupling between magnetospheres and their ionospheres; and to understand the magnetospheric mechanisms which accelerate particles to high energies, as well as the ultimate fate of these particles. The report continues on to summarize a number of proposed space missions aimed at data acquisition. Finally, there is a brief discussion of the theory and modeling of magnetospheres.