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At least 55 records · Page 3

Positron stopping in multilayer materials

Positron annihilation spectroscopy provides a sensitive toolset for defect characterization. In beam based studies of single-layer targets, the form of implantation profiles is well established, depending on the kinetic energy and angle of incident positrons relative to the target surface and the density and average atomic number of the target. For multilayer systems, the difference in density and across the layers makes derivation of an analytical form difficult. To date, the determination of positron stopping profiles in multilayer targets has primarily involved Monte Carlo simulations. We present here an alternative approach that estimates the energy distribution dN/dE of those positrons transmitted past each layer boundary, by fitting the remaining tail of the stopping profile after each layer with a basis set comprised of calculated stopping profiles in the same material they are transmitted through. The stopping profile in the next layer is then found by summing a series of stopping profiles in the new medium in proportion to the determined distribution dN/dE. The results of our model are compared with simulation results in a system of alternating layers of Al and Au and find reasonable agreement in the predicted profile and excellent agreement in the predicted mean implantation depth. Finally, we derived a simple formula-based approach for the calculation of the mean implantation depth in two-layer systems that provides results in excellent agreement with the full model.

Jones, A. C. L. [Arizona State University, Tempe, ↗

Simulations of tokamak edge plasma turbulent fluctuations based on a minimal 3D model

In this study, a new simulation model for tokamak boundary plasma, SOLT3D, is implemented in the BOUT++ framework. The simulation model includes a set of dynamic equations describing collisional boundary plasma and neutral gas in the tokamak scrape-off layer and divertor region. The model is verified against standard linear plasma instabilities and available nonlinear results. For L-mode like conditions, SOLT3D reproduces characteristics of boundary plasma turbulent fluctuations that are similar to published experimental data, in terms of the amplitude and spatial dependence of the fluctuations. It also reproduces realistic plasma fluxes on material surfaces and expected Bohm-like effective radial transport. Plasma fluctuations inferred from the simulations imply inevitably a significant level of intrinsic 'noise' for axisymmetric tokamak plasma transport modeling, introducing errors on the order of unity. In particular, the toroidally averaged atomic rates below 5–10 eV are strongly modified by turbulent plasma fluctuations, which should significantly affect the standard axisymmetric modeling of the tokamak edge plasma and divertor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spectro-temporal comparisons of optical emission, absorption, and laser-induced fluorescence for characterizing ns and fs laser-produced plasmas

We performed simultaneous measurement of absorption, emission, and laser-induced fluorescence spectroscopic signatures for determining nanosecond and femtosecond laser-produced plasma’s physical properties throughout its lifecycle. Plasmas are produced by focusing either ~6 ns, 1064 nm pulses from an Nd:YAG or ~35 fs, ~800 nm pulses from a Ti:Sapphire laser on an Inconel target that contains Al as a minor alloying addition. A continuous-wave narrowband tunable laser was used for performing absorption and fluorescence spectroscopy while a fast-gated detection system was used for emission spectroscopy. The temporal evolution of emission, fluorescence, and absorbance of Al transitions are compared for both ns and fs laser-produced plasms. Time-resolved absorbance was also used for evaluating linewidth, lineshape, temperature, and column-averaged atomic number density at late times of ns and fs plasma evolution. Our results demonstrate that lower and excited-state populations of fs laser produced plasmas are short-lived in comparison to those in ns plasmas. The lower state population is observed to reach a maximum value earlier in time for the fs plasma versus the ns plasma, while the kinetic temperature for the ns plasma was higher than for the fs plasma at most times of the plasma evolution.

(280.4788) Optical Sensing, (300.2140) Emission Sp↗

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗

Collisional stopping power of ions in warm dense matter

Here, a model for the collisional stopping of ions on free electrons in warm dense matter is developed and explored. It is based on plasma kinetic theory, but with modifications to address the warm dense matter regime. Specifically, it uses the Boltzmann-Uehling-Uhlenbeck kinetic equation to incorporate effects of Fermi degeneracy of electrons. The cross section is computed from quantum scattering of electrons and ions occurring via the potential of mean force derived from an average atom model, which incorporates effects of strong Coulomb correlations. Predictions from this model show comparable accuracy to results from time-dependent density functional theory calculations for deuterium near solid density and a temperature of several electronvolts, at a fraction of the computational cost. Further, the model captures the transition of a plasma from the classical limit to the degenerate limit, including qualitative behaviors of solid state theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Properties of carbon up to 10 million kelvin from Kohn-Sham density functional theory molecular dynamics

Accurately modeling dense plasmas over wide-ranging conditions of pressure and temperature is a grand challenge critically important to our understanding of stellar and planetary physics as well as inertial confinement fusion. In this work, we employ Kohn-Sham density functional theory (DFT) molecular dynamics (MD) to compute the properties of carbon at warm and hot dense matter conditions in the vicinity of the principal Hugoniot. In particular, we calculate the equation of state (EOS), Hugoniot, pair distribution functions, and diffusion coefficients for carbon at densities spanning 8 g/$\mathrm{cm^3}$ to 16 g/$\mathrm{cm^3}$ and temperatures ranging from 100 kK to 10 MK using the Spectral Quadrature method. Here, we find that the computed EOS and Hugoniot are in good agreement with path integral Monte Carlo results and the sesame database. Additionally, we calculate the ion-ion structure factor and viscosity for selected points. All results presented are at the level of full Kohn-Sham DFT-MD, free of empirical parameters, average-atom, and orbital-free approximations employed previously at such conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Crystal structure and physical properties of Yb 2 In and Eu 2–x Yb x In alloys

While binary R E 2 In , where R E = rare earth , have been reported a few decades ago, recent investigations revealed intriguing new physical insights. For instance, the discovery of a nearly ideal first-order ferromagnetic transition in Eu 2 In calls for further exploration of structures and properties of R E 2 In , in particular for the least-documented R E = Eu and Yb cases. In this work, we investigate Eu 2 – x Yb x In pseudobinaries with nominal values of x = 0.25 , 0.5, 0.75, 1, 1.5, 2 by powder x-ray diffraction (including as function of temperature from 100 to 375 K for Yb 2 In ), magnetization (5–300 K), as well as electrical resistivity (5–300 K) and calorimetric (2–150 K) measurements for Yb 2 In . Compared to other RE , Yb or Eu always raise challenging questions linked to their valence states. From average atomic volume, Yb is anticipated to be divalent in Yb 2 In , at least between 100 and 375 K, which is in line with the absence of 4 f magnetism. In agreement with x-ray diffraction and magnetization data, the resistivity of Yb 2 In is rather featureless and typical of a metal. Establishing Yb 2 In as a nonmagnetic isostructural reference for Eu 2 In allows one to use its heat capacity to revisit that of the latter, and get experimental insights into the exceptional magnetocaloric effect of the compound with Eu. In particular, we show that a third of the total magnetic entropy ( S m ≈ 35.6 J mo l – 1 K – 1 at T = 100 K ) is concentrated in a 3 K temperature window around the T C of Eu 2 In . Starting from the ferromagnetic compound Eu 2 In [ T C = 55.2 ( 5 ) K ] , we show that Yb substitutions in Eu 2 – x Yb x In lead to a decrease in both the Curie temperature [ T C = 41 ( 2 ) and 32(2) K for x = 0.25 and 0.5] and magnetic saturation, while weakening the first-order character of the transition as x increases. A significant isothermal entropy change of 5.1 ( 4 ) J mo l – 1 K – 1 for Δ B = 2 T is found at 44 K in Eu 1.75 Yb 0.25 In , demonstrating that the giant magnetocaloric effect of Eu 2 In can be tuned to lower temperatures by Yb substitutions.

36 MATERIALS SCIENCE↗

Development of a multiphase equation of state for gallium with experiments and ab initio free-energy calculations

Here, we present a five-phase equation of state (EOS) for elemental gallium (Ga) that is developed using both experimental data and new theoretical predictions. Four experimentally observed solid phases (Ga-I, Ga-II, Ga-III, and Ga-IV) and one liquid phase are included. To improve our understanding of the thermal behavior of Ga and its phase boundaries under compression, we have performed ab initio density functional theory (DFT) free-energy calculations for the Ga-III and liquid phases, which enables us to determine the melt temperature to be 2214 ± 100 K at 110 GPa, extending significantly beyond the existing experimental melt data, which are limited to 25 GPa. In order to best describe the electron-thermal contribution, which dominates the liquid free energy at high temperatures, we have carried out averaged-atom-in-jellium DFT calculations to cover the entire temperature and density range of the EOS. The resulting multiphase Ga EOS is able to accurately reproduce a diverse variety of data, including known phase boundaries, the principal Hugoniot, low-pressure liquid isobars, and diamond-anvil-cell isotherm measurements at high pressures. It agrees more closely with key experimentally measured properties than other Ga EOS models targeted for high-pressure applications.

Wu, Christine J. [Lawrence Livermore National Labo↗

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. For this work, we used stable isotope metabolomics to trace 13 C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13 C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13 C-labeled metabolites differed primarily by carbon source (R 2 = 0.68) rather than time (R 2 = 0.07), with source-specific differences persisting throughout incubations. The 13 C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13 C in metabolite markers of biomass (amino acids and nucleic acids). The 13 C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13 C by the end of incubations. Temporal patterns in the 13 C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling.

59 BASIC BIOLOGICAL SCIENCES↗

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.

36 MATERIALS SCIENCE↗

Development of Ion Stopping Models for HED Plasmas Using Unified Self-Consistent Field Models and Self-Consistent Electron Distributions

We have implemented several corrections to the electronic stopping power model combining the RPA dielectric response formalism and local density approximation with electronic density distribution calculated in an average atom model. These modifications include strong collision correction, local field correction, electron binding energy correction, and the Barkas effect. The combined results bring the RPA-LDA stopping power in cold targets to closer agreements with experiments for a wide range of materials. The same method is then applied to the stopping of ions in warm dense plasmas. The computational framework developed during this project is publicly available on GitHub (https://github.com/dedx-erpa/dedx). Tabulated data for protons in cold target for common materials are located in the data/ subdirectory of the repository.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Transformation of atomically dispersed platinum in SAPO-37 into platinum clusters: catalyst for ethylene hydrogenation

Atomically dispersed supported platinum catalysts were synthesized by the reaction of Pt(acac) 2 (acac = acetylacetonato) with the silicoaluminophosphate molecular sieve SAPO-37, with infrared spectra showing that the reaction involved SAPO OH groups. Extended X-ray absorption fine structure (EXAFS) spectra show that, after heating in air to 623 K, each platinum atom on average was bonded to approximately two oxygen atoms of the SAPO support, with no evidence of platinum clusters. X-ray absorption near edge spectra (XANES) indicate a platinum formal oxidation state of approximately +2. Here, these supported mononuclear species lacked catalytic activity for ethylene hydrogenation at 1 bar and room temperature, but activity arose during catalysis in a once-through flow reactor/X-ray absorption spectroscopy cell, as the XANES white line intensity decreased, indicating reduction of the platinum, and the EXAFS-determined Pt–Pt coordination number (CN) increased from essentially zero to 2.7 ± 0.5 after 2 h, indicating the formation of platinum clusters of only a few atoms each. The data indicate the almost instantaneous formation of the clusters and identify them as the catalytically active species. Subsequent exposure of the catalyst to ethylene as in situ EXAFS and XANES data were recorded led to a decrease in the Pt–Pt coordination number to 1.6 ± 0.3 and an increase in the white line intensity, indicating partial oxidative fragmentation of the clusters by ethylene. Platinum clusters in SAPO-37 formed in separate experiments by exposure to H 2 prior to catalysis were also catalytically active for ethylene hydrogenation. Here, the data thus show how to dial in the catalytic activity by forming platinum clusters by exposure of mononuclear platinum to H 2 and how to dial back the activity by oxidative fragmentation of the clusters by reaction with ethylene, all under mild conditions; the ethylene : H 2 ratio of the reactant gas determines the average platinum nuclearity and thus the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach

We present global predictions of the ground state mass of atomic nuclei based on a novel Machine Learning algorithm. We combine precision nuclear experimental measurements together with theoretical predictions of unmeasured nuclei. This hybrid data set is used to train a probabilistic neural network. In addition to training on this data, a physics-based loss function is employed to help refine the solutions. The resultant Bayesian averaged predictions have excellent performance compared to the testing set and come with well-quantified uncertainties which are critical for contemporary scientific applications. We assess extrapolations of the model’s predictions and estimate the growth of uncertainties in the region far from measurements.

74 ATOMIC AND MOLECULAR PHYSICS↗

Spectral line identification from a photoionised silicon plasma in emission

Next-generation X-ray satellite telescopes such as XRISM, NewAthena and Lynx will enable observations of exotic astrophysical sources at unprecedented spectral and spatial resolution. Proper interpretation of these data demands that the accuracy of the models is at least within the uncertainty of the observations. One set of quantities that might not currently meet this requirement is transition energies of various astrophysically relevant ions. Current databases are populated with many untested theoretical calculations. Accurate laboratory benchmarks are required to better understand the coming data. We obtained laboratory spectra of X-ray lines from a silicon plasma at an average spectral resolving power of ∼7500 with a spherically bent crystal spectrometer on the Z facility at Sandia National Laboratories. Many of the lines in the data are measured here for the first time. We report measurements of 53 transitions originating from the K-shells of He-like to B-like silicon in the energy range between ∼1795 and 1880 eV (6.6–6.9 Å). The lines were identified by qualitative comparison against a full synthetic spectrum calculated with ATOMIC. The average fractional uncertainty (uncertainty/energy) for all reported lines is ∼5.4 × 10 −5 . We compare the measured quantities against transition energies calculated with RATS and FAC as well as those reported in the NIST ASD and XSTAR’s uaDB. Average absolute differences relative to experimentally measured values are 0.20, 0.32, 0.17 and 0.38 eV, respectively. All calculations/databases show good agreement with the experimental values; NIST ASD shows the closest match overall.

astrophysical plasmas↗

Isotopic mass effects of tritium-fueled high-performance TFTR supershots

An increase in total stored energy correlated with the addition of tritium fuel was observed in supershots during the TFTR DT campaign. This supershot regime had strikingly high, centrally peaked ion and electron temperatures, and the largest neutron emission rates observed in TFTR. This paper presents a study of the causes of this increase in stored energy in supershots. Twenty-six supershots have been recently reanalyzed with the TRANSP plasma analysis code. Early TRANSP simulations did not accurately match the measured magnitude and time evolutions of the neutron emission rates. This mismatch is attributed to neglecting apparent increases of trace amounts of heavy impurities during neutral beam injection. The new TRANSP runs were tuned to accommodate this and match the measured global neutron emission rates. These new runs also had improved fidelity in predicting the time histories and radial dependencies of measured DT neutron emission rates. That in turn adds confidence in the simulated thermal deuterium and tritium density profiles that are needed for calculating the average hydrogenic atomic mass profiles. Six subsets of these supershots had well matched toroidal field B tor , plasma current I p , flux geometry, and total injected neutral beam power. The mix of D and T beam ions was varied for different discharges. The magnitude of the increase of the thermal ion energy W i with added tritium was relatively small, and the total W tot increase is dominated by the increase in fast beam ions with T. Analyses at times before the occurrences of deleterious MHD instabilities yielded scaling of W tot with the volume-average isotopic mass consistent with previous publications. The relative fraction of fast energy ions is expected to be small in practical tokamak reactors. Thus the increase in stored energy W tot observed in TFTR supershots does not appear likely to be significantly helpful for producing useful fusion energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Charge state distributions in dense plasmas

Charge state distributions in hot, dense plasmas are a key ingredient in the calculation of spectral quantities like the opacity. However, they are challenging to calculate, as models like Saha–Boltzmann become unreliable for dense, quantum plasmas. Here, we present a new variational model for the charge state distribution, along with a simple model for the energy of the configurations that includes the orbital relaxation effect. Comparison with other methods reveals generally good agreement with average atom-based calculations, the breakdown of the Saha–Boltzmann method, and mixed agreement with a chemical model. We conclude that the new model gives a relatively inexpensive, but reasonably high fidelity method of calculating the charge state distribution in hot dense plasmas, in local thermodynamic equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Computational studies of structural, energetic, and electronic properties of pure Pt and Mo and mixed Pt/Mo clusters: Comparative analysis of characteristics and trends

The added technological potential of bimetallic clusters and nanoparticles, as compared to their pure (i.e., one-component) counterparts, stems from the ability to further fine-tune their properties and, consequently, functionalities through a simultaneous use of the “knobs” of size and composition. The practical realization of this potential can be greatly advanced by the knowledge of the correlations and relationships between the various characteristics of bimetallic nanosystems on the one hand and those of their pure counterparts as well as pure constituent components on the other hand. Here, in this study, we present results of a density functional theory based study of pure Pt n and Mo n clusters aimed at revisiting and exploring further their structural, electronic, and energetic properties. These are then used as a basis for analysis and characterization of the results of calculations on two-component Pt n-m Mo m clusters. The analysis also includes establishing relationships between the properties of the Pt n-m Mo m clusters and those of their Pt n-m and Mo m components. One of the particularly intriguing findings suggested by the calculated data is a linear dependence of the average binding energy per atom in sets of Pt n-m Mo m clusters that have the same fixed number m of Mo atoms and different number n-m of Pt atoms on the fractional content (n-m)/n of Pt atoms. We derive an analytical model that establishes the fundamental basis for this linearity and expresses its parameters—the m-dependent slope and intercept—in terms of characteristic properties of the constituent components, such as the average binding energy per atom of Mo m and the average per-atom adsorption energy of the Pt atoms on Mo m . The conditions of validity and degree of robustness of this model and of the linear relationship predicted by it are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗