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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Formation energy puzzle in intermetallic alloys: Random phase approximation fails to predict accurate formation energies

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke- Ernzerhof (PBE) and the strongly constrained and appropriately normed (SCAN) meta-GGA. In addition, we utilized two nonlocal DFT functionals, the hybrid HSE06, and the state-of-the-art random phase approximation (RPA). The nonlocal functionals such as HSE06 and RPA yield accurate formation energies of binary alloys with completely-filled d-band metals, where semilocal functionals underperform. The accuracy at the nonlocal functionals is greatly reduced when a partially-filled d-band metal is present in an alloy, while PBE-GGA outperforms in these cases. We show that the accurate prediction of formation energies by any DFT method depends on its ability to predict the accurate electronic properties, e.g., valence d-band contribution to the density of states (DOS). The SCAN meta-GGA often corrects the PBE-DOS, however, it does not provide accurate formation energies compared to PBE. This is assumed to be due to the lack of proper error cancellation that should be expected due to the similar bulk nature of both alloys and their constituents, which may improve with the modification of meta-GGA ingredients. RPA yields too negative formation energies of alloys with partially-filled d-band metals. RPA results can be corrected by restoring the exchange-correlation kernel, thereby improving the short-range electron-electron correlation in metallic densities.

36 MATERIALS SCIENCE↗

Bayesian Spatial Models for Projecting Corn Yields

Climate change is predicted to impact corn yields. Previous studies analyzing these impacts differ in data and modeling approaches and, consequently, corn yield projections. We analyze the impacts of climate change on corn yields using two statistical models with different approaches for dealing with county-level effects. The first model, which is novel to modeling corn yields, uses a computationally efficient spatial basis function approach. We use a Bayesian framework to incorporate both parametric and climate model structural uncertainty. We find that the statistical models have similar predictive abilities, but the spatial basis function model is faster and hence potentially a useful tool for crop yield projections. We also explore how different gridded temperature datasets affect the statistical model fit and performance. Compared to the dataset with only weather station data, we find that the dataset composed of satellite and weather station data results in a model with a magnified relationship between temperature and corn yields. For all statistical models, we observe a relationship between temperature and corn yields that is broadly similar to previous studies. We use downscaled and bias-corrected CMIP5 climate model projections to obtain detrended corn yield projections for 2020–2049 and 2069–2098. In both periods, we project a decrease in the mean corn yield production, reinforcing the findings of other studies. However, the magnitude of the decrease and the associated uncertainties we obtain differ from previous studies.

54 ENVIRONMENTAL SCIENCES↗

Multifunctional materials and composites

Forming multifunctional materials and composites thereof includes contacting a first material having a plurality of oxygen-containing functional groups with a chalcogenide compound, and initiating a chemical reaction between the first material and the chalcogenide compound, thereby replacing oxygen in some of the oxygen-containing functional groups with chalcogen from the chalcogen-containing compound to yield a second material having chalcogen-containing functional groups and oxygen-containing functional groups. The first material is a carbonaceous material or a macromolecular material. A product including the second material is collected and may be processed further to yield a modified product or a composite.

36 MATERIALS SCIENCE↗

Production of light-flavor hadrons in pp collisions at $\sqrt{s}~=~7\text { and }\sqrt{s} = 13 \, \text { TeV} $

The production of \(\pi ^{\pm }\) , \(\mathrm{K}^{\pm }\) , \(\mathrm{K}^{0}_{S}\) , \(\mathrm{K}^{*}(892)^{0}\) , \(\mathrm{p}\) , \(\phi (1020)\) , \(\Lambda \) , \(\Xi ^{-}\) , \(\Omega ^{-}\) , and their antiparticles was measured in inelastic proton–proton (pp) collisions at a center-of-mass energy of \(\sqrt{s}\) = 13 TeV at midrapidity ( \(|y|<0.5\) ) as a function of transverse momentum ( \(p_{\mathrm{T}}\) ) using the ALICE detector at the CERN LHC. Furthermore, the single-particle \(p_{\mathrm{T}}\) distributions of \(\mathrm{K}^{0}_{S}\) , \(\Lambda \) , and \(\overline{\Lambda }\) in inelastic pp collisions at \(\sqrt{s} = 7\) TeV are reported here for the first time. The \(p_{\mathrm{T}}\) distributions are studied at midrapidity within the transverse momentum range \(0\le p_{\mathrm{T}}\le 20\) GeV/ c , depending on the particle species. The \(p_{\mathrm{T}}\) spectra, integrated yields, and particle yield ratios are discussed as a function of collision energy and compared with measurements at lower \(\sqrt{s}\) and with results from various general-purpose QCD-inspired Monte Carlo models. A hardening of the spectra at high \(p_{\mathrm{T}}\) with increasing collision energy is observed, which is similar for all particle species under study. The transverse mass and \(x_{\mathrm{T}}\equiv 2p_{\mathrm{T}}/\sqrt{s}\) scaling properties of hadron production are also studied. As the collision energy increases from \(\sqrt{s}\) = 7–13 TeV, the yields of non- and single-strange hadrons normalized to the pion yields remain approximately constant as a function of \(\sqrt{s}\) , while ratios for multi-strange hadrons indicate enhancements. The \(p_\mathrm{{T}}\) -differential cross sections of \(\pi ^{\pm }\) , \(\mathrm {K}^{\pm }\) and \(\mathrm {p}\) ( \(\overline{\mathrm{p}}\) ) are compared with next-to-leading order perturbative QCD calculations, which are found to overestimate the cross sections for \(\pi ^{\pm }\) and \(\mathrm{p}\) ( \(\overline{\mathrm{p}}\) ) at high \(p_\mathrm{{T}}\) .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

RT-EOM-CCSD Calculations of Inner and Outer Valence Ionization Energies and Spectral Functions

Photoelectron spectroscopy (PES) is a standard experimental method for material characterization, but its interpretation can be hampered by its reliance on standard materials. To facilitate the study of unknown systems, theoretical methods are desirable. Here we present a real-time equation-of-motion coupled cluster (RT-EOM-CC) approach for valence PES, extending our core-level development. Here, we demonstrate that RT-EOM-CC yields ionization energies and spectral functions in good agreement with experiment and CI-based methods, even for some more correlated cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Foundations of variational discrete action theory

Variational wave functions and Green's functions are two important paradigms for solving quantum Hamiltonians, each having their own advantages. Here we detail the variational discrete action theory (VDAT), which exploits the advantages of both paradigms in order to approximately solve the ground state of quantum Hamiltonians. VDAT consists of two central components: the sequential product density matrix (SPD) ansatz and a discrete action associated with the SPD. The SPD is a variational ansatz inspired by the Trotter decomposition and characterized by an integer $\mathscr{N}$, recovering many well-known variational wave functions, in addition to the exact solution for $\mathscr{N}$ = ∞. The discrete action describes all dynamical information of an effective integer time evolution with respect to the SPD. We generalize the path integral to our integer time formalism, which converts a dynamic correlation function in integer time to a static correlation function in a compound space. We also generalize the usual many-body Green's function formalism to integer time, which results in analogous but distinct mathematical structures, yielding integer time versions of the generating functional, Dyson equation, and Bethe-Salpeter equation. We prove that the SPD can be exactly evaluated in the multiband Anderson impurity model (AIM) by summing a finite number of diagrams. For the multiband Hubbard model, we prove that the self-consistent canonical discrete action approximation (SCDA), which is the integer time analog of the dynamical mean-field theory, exactly evaluates the SPD for d = ∞. VDAT within the SCDA provides an efficient yet reliable method for capturing the local physics of quantum lattice models, which will have broad applications for strongly correlated electron materials. More generally, VDAT should find applications in various many-body problems in physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cortical proteins may provide motor resilience in older adults

Motor resilience proteins may be a high value therapeutic target that offset the negative effects of pathologies on motor function. This study sought to identify cortical proteins associated with motor decline unexplained by brain pathologies that provide motor resilience. We studied 1226 older decedents with annual motor testing, postmortem brain pathologies and quantified 226 proteotypic peptides in prefrontal cortex. Twenty peptides remained associated with motor decline in models controlling for ten brain pathologies (FDR < 0.05). Higher levels of nine peptides and lower levels of eleven peptides were related to slower decline. A higher motor resilience protein score based on averaging the levels of all 20 peptides was related to slower motor decline, less severe parkinsonism and lower odds of mobility disability before death. Cortical proteins may provide motor resilience. Targeting these proteins in further drug discovery may yield novel interventions to maintain motor function in old age.

Buchman, Aron↗

Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a deep potential model for F and CF 2 etching of Si and SiO 2

An understanding of plasma-surface interactions at increasingly smaller scales is invaluable for the development of novel technologies and processing techniques. Molecular dynamics (MD) simulations can provide insights into atomic-scale interactions, though they are restricted by the availability of interatomic potentials. Machine learning methods, such as Deep Potential Molecular Dynamics (DeepMD), provide a systematic framework for the development of accurate and flexible ab initio-based models. In this work, we develop DeepMD models for the ion-enhanced etching of Si and SiO 2 by F and CF 2 radicals. We employ an active learning process to expand the data set on which the model is trained and demonstrate its effect on the model accuracy. The DeepMD results are compared to data from classical MD simulations and experiments. Physical sputtering yields of SiO 2 by Ar + ions show good agreement with previous simulation results using conventional interatomic potentials, though the predicted depth profiles are different. Etching yields are calculated as a function of ion energy and neutral to ion flux ratio for the Ar + ion-enhanced etching of SiO 2 and Si by F atoms, as well as for etching of SiO 2 by CF 2 radicals, showing reasonable agreement with experimental data. Finally, an ion-enhanced surface kinetic model is fitted to the DeepMD etch yields, and the fitted parameters are compared to quantities computed directly from DeepMD simulations. This study illustrates how molecular dynamics simulations using machine learning potentials can provide an accurate model of etching processes relevant to device manufacturing.

Kounis-Melas, Andreas [Princeton Univ., NJ (United↗

Further Development of the Tamped Richtmyer-Meshkov Instability Method and Application to Molybdenum Dynamic Strength Calibration and Tabulation

The high pressure and high strain rate dynamic strength of Mo is experimentally and computationally investigated in the 3–20 GPa stress, 50–600 C temperature, and 10 5 –10 6 /s strain rate regimes using a modified tamped Richtmyer-Meshkov instability (RMI) method. Modifications to the tamped RMI method include a method to determine loading states during strain, a new strength calibration function based on interface shape, and a robust uncertainty quantification method. These modifications improve fidelity of the tamped RMI method, allowing evaluation of the compensating effects of pressure hardening, strain rate hardening, strain hardening, and thermal softening. The new calibration function based on interface shape is not limited to sinusoidal corrugations and could be applied to additional interface shapes. Plate impact experiments are performed at Argonne National Laboratory’s Advanced Photon Source’s Dynamic Compression Sector operated by Washington State University (DCS), driving a planar shock front through a corrugated Mo-D 2 O or Mo-C 8 F 18 interface, forcing the corrugation to significantly deform. The extent of interfacial deformation, RMI growth, is experimentally observed using X-ray phase contrast imaging at the DCS. RMI jet lengths and jet shapes are extracted from the experimental radiographs, then used to calibrate numerical simulations performed with the Sandia National Laboratories (SNL) hydrocode CTH. Mo yield strength, Y, as a function of shock pressure, P, strain rate, $\dot{\varepsilon }$, accumulated strain, ϵ, relative volumetric compression, RD , and temperature, T , is determined for each impact experiment and presented. The calibrated Mo yield strength values range 1.2–1.8 GPa, with strength generally decreasing as the impact stress increases. This trend is likely caused by thermal softening or strain localization. The tabular yield strength versus loading condition data presented in this paper can be used to fit complex strength models.

Voorhees, T. J. [Sandia National Lab. (SNL-CA), Li↗

From model to crop: functional characterization of SPL8 in M. truncatula led to genetic improvement of biomass yield and abiotic stress tolerance in alfalfa

Biomass yield, salt tolerance and drought tolerance are important targets for alfalfa ( Medicago sativa L. ) improvement. Medicago truncatula has been developed into a model plant for alfalfa and other legumes. By screening a Tnt1 retrotransposon-tagged M. truncatula mutant population, we identified three mutants with enhanced branching. Branch development determines shoot architecture which affects important plant functions such as light acquisition, resource use and ultimately impacts biomass production. Molecular analyses revealed that the mutations were caused by Tnt1 insertions in the SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 8 (SPL8) gene. The M. truncatula spl8 mutants had increased biomass yield, while overexpression of SPL8 in M. truncatula suppressed branching and reduced biomass yield. Scanning electron microscopy (SEM) analysis showed that SPL8 inhibited branching by directly suppressing axillary bud formation. Based on the M. truncatula SPL8 sequence, alfalfa SPL8 (MsSPL8) was cloned and transgenic alfalfa plants were produced. MsSPL8 down-regulated or up-regulated alfalfa plants exhibited similar phenotypes to the M. truncatula mutants or overexpression lines, respectively. Specifically, the MsSPL8 down-regulated alfalfa plants showed up to 43% increase in biomass yield in the first harvest. The impact was even more prominent in the second harvest, with up to 86% increase in biomass production compared to the control. Furthermore, downregulation of MsSPL8 led to enhanced salt and drought tolerance in transgenic alfalfa. Results from this research offer a valuable approach to simultaneously improve biomass production and abiotic stress tolerance in legumes.

09 BIOMASS FUELS↗

High-order limiting methods using maximum principle bounds derived from the Boltzmann equation I: Euler equations

The use of limiting methods for high-order numerical approximations of hyperbolic conservation laws generally requires defining an admissible region/bounds for the solution. In this work, we present a novel approach for computing solution bounds and limiting for the Euler equations through the kinetic representation provided by the Boltzmann equation, which allows for extending limiters designed for linear advection directly to the Euler equations. Given an arbitrary set of solution values to compute bounds over (e.g., numerical stencil) and a desired linear advection limiter, the proposed approach yields an analytic expression for the admissible region of particle distribution function values, which may be numerically integrated to yield a set of bounds for the density, momentum, and total energy. Further, these solution bounds are shown to preserve positivity of density/pressure/internal energy and, when paired with a limiting technique, can robustly resolve strong discontinuities while recovering high-order accuracy in smooth regions without any ad hoc corrections (e.g., relaxing the bounds). This approach is demonstrated in the context of an explicit unstructured high-order discontinuous Galerkin/flux reconstruction scheme for a variety of difficult problems in gas dynamics, including cases with extreme shocks and shock-vortex interactions. Furthermore, this work presents a foundation for limiting techniques for more complex macroscopic governing equations that can be derived from an underlying kinetic representation for which admissible solution bounds are not well-understood.

42 ENGINEERING↗

Lévy-stable two-pion Bose-Einstein correlations in s NN = 200 GeV Au + Au collisions

Here, we present a detailed measurement of charged two-pion correlation functions in 0–30% centrality √ s NN = 200 GeV Au + Au collisions by the PHENIX experiment at the Relativistic Heavy Ion Collider. The data are well described by Bose-Einstein correlation functions stemming from Lévy-stable source distributions. Using a fine transverse momentum binning, we extract the correlation strength parameter λ, the Lévy index of stability α, and the Lévy length scale parameter R as a function of average transverse mass of the pair m T . We find that the positively and the negatively charged pion pairs yield consistent results, and their correlation functions are represented, within uncertainties, by the same Lévy-stable source functions. The λ(m T ) measurements indicate a decrease of the strength of the correlations at low m T . The Lévy length scale parameter R(m T ) decreases with increasing m T , following a hydrodynamically predicted type of scaling behavior. The values of the Lévy index of stability α are found to be significantly lower than the Gaussian case of α = 2, but also significantly larger than the conjectured value that may characterize the critical point of a second-order quark-hadron phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impact of Sr-Incorporation on Cr Oxidation and Water Dissociation in La (1- x ) Sr x CrO 3

The oxidation and reduction of metal oxides and their interaction with the environment play a critical role in material stability and the ability to catalyze reactions. The local change in valence and formation of surface adsorbates affect the oxide electronic structure and chemical reactivity, yet are challenging to probe experimentally. Here we present a detailed study of the oxidation and reduction of Cr in the perovskite oxide family of La(1-x)SrxCrO3 using ambient pressure X-ray photoelectron spectroscopy. The incorporation of Sr increases the propensity to oxidize the surface, leading to the presence of Cr4+ and Cr6+ principally confined to the top unit cell when in equilibrium with O2 gas. These acidic sites are readily reduced to Cr3+ in equilibrium with H2O vapor, and the resultant amount of hydroxyls formed from the dissociation of H2O is directly proportional to the density of surface sites which had been oxidized. Our quantification of the redox stability of La(1-x)SrxCrO3 and the relationship between the extent of oxidation, reduction, and hydroxylation with Sr yields important insight into the surface functionality during electrochemical applications.

ambient pressure X-ray photoelectron spectroscopy↗

Control of polarization in bulk ferroelectrics by mechanical dislocation imprint

Defects are essential to engineering the properties of functional materials ranging from semiconductors and superconductors to ferroics. Whereas point defects have been widely exploited, dislocations are commonly viewed as problematic for functional materials and not as a microstructural tool. In this work, we developed a method for mechanically imprinting dislocation networks that favorably skew the domain structure in bulk ferroelectrics and thereby tame the large switching polarization and make it available for functional harvesting. The resulting microstructure yields a strong mechanical restoring force to revert electric field–induced domain wall displacement on the macroscopic level and high pinning force on the local level. This induces a giant increase of the dielectric and electromechanical response at intermediate electric fields in barium titanate [electric field–dependent permittivity (ε 33 ) ≈ 5800 and large-signal piezoelectric coefficient ( d 33 *) ≈ 1890 picometers/volt]. Dislocation-based anisotropy delivers a different suite of tools with which to tailor functional materials.

36 MATERIALS SCIENCE↗

Date Release Report for Large Surface Explosion Coupling Experiment (LSECE) Nevada National Security Site

The DTRA sponsored 2020-2022 Large Surface Explosion Coupling Experiment (LSECE) consists of two large ground surface chemical explosions, data collection, analysis and modeling carried out in 2020-2022. The LSECE chemical explosions were carried out at the site of prior NNSA sponsored buried chemical explosions that were part of the Source Physics Experiment (SPE) Phase II in Dry Alluvium Geology (DAG). This report described the data collected under LSECE that is being made publicly available. The prior buried explosion DAG data are described in a separate report (https://www.osti.gov/biblio/1825534) and are also publicly available. The LSECE explosions, data analysis and numerical modeling work sponsored by DTRA were intended to address three objectives: 1) Generate seismo-acoustic data to test and improve numerical models of explosion energy coupling in dry alluvium geology; 2) To improve seismo-acoustic yield estimation techniques as a function of depth and medium properties; 3) To study and improve acoustic propagation modeling under two different atmospheric conditions. The LSECE data that were collected have expanded the prior DAG buried explosion dataset to include surface chemical explosions recorded on a common set of seismo-acoustic stations. They have allowed a more detailed study of above and below surface seismo-acoustic energy coupling with applications to explosion monitoring and assessment. The two approximately 1-ton TNT equivalent yield LSECE explosions were detonated at different times of the day to explore the effects of the different atmospheric conditions. The first chemical explosion “Artemis” was conducted before dawn when temperature inversions were present. The second chemical explosion “Apollo” was conducted on a sunny afternoon when the temperature gradient was more linear. The LSECE chemical explosion data were also collected across a variety of different sensor types to allow evaluation of their effectiveness in recovering useful information. The LSECE instrumentation included fiber optic or Distributed Acoustic Sensing (DAS), a dense array or Large-N array of seismometers, borehole accelerometers, DAS and a velocity meter, airborne acoustic instruments and a variety of visual and remote sensing data.

58 GEOSCIENCES↗