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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Equilibrium Thermodynamic Properties of Aqueous Solutions of Ionic Liquid 1-Ethyl-3-Methylimidazolium Methanesulfonate [EMIM][MeSO3]

Abstract The ionic liquid 1-ethyl-3-methylimidazolium methanesulfonate ([EMIM][MeSO 3 ]) has been considered as a promising alternative desiccant to triethylene glycol and lithium bromide commonly used in the industry. In this paper, the water activity coefficient of this binary system was measured from 303 K to 363 K with water concentration from 18% to 92%. The interaction energies between the ionic liquid molecules ( $${g}_{22}$$ g 22 ) and between the ionic liquid and water molecules ( $${g}_{12}$$ g 12 ) for the [EMIM][MeSO 3 ]/water binary system were determined from the water activity coefficient data using the Non-Random Two-Liquid (NRTL) model. The magnitude of the interaction energy between the [EMIM][MeSO 3 ] and water molecules ( $${g}_{12}$$ g 12 ) was found to be in the range of 45~49 kJ/mol, which was about 20% larger than that between the water molecules ( $${g}_{11}$$ g 11 ) in the [EMIM][MeSO 3 ]/water system. The large ( $${g}_{12}$$ g 12 ) can explain many observed macroscopic thermodynamic properties such as strong hygroscopicity in the ionic liquid [EMIM][MeSO 3 ]. These interaction energies were used to determine the heat of desorption of the [EMIM][MeSO 3 ]/water system, and the obtained heat of desorption was in good agreement with that calculated from the conventional Clausius-Clapeyron Equation.

42 ENGINEERING↗
DOE OSTI2022

Surrogate Hessian accelerated structural optimization for stochastic electronic structure theories

In this work, we present an efficient energy-based method for structural optimization with stochastic electronic structure theories, such as diffusion quantum Monte Carlo (DMC). This method is based on robust line-search energy minimization in reduced parameter space, exploiting approximate but accurate Hessian information from a surrogate theory, such as density functional theory. The surrogate theory is also used to characterize the potential energy surface, allowing for simple but reliable ways to maximize statistical efficiency while retaining controllable accuracy. We demonstrate the method by finding the minimum DMC energy structures of the selected flake-like aromatic molecules, such as benzene, coronene, and ovalene, represented by 2, 6, and 19 structural parameters, respectively. In each case, the energy minimum is found within two parallel line-search iterations. The method is near-optimal for a line-search technique and suitable for a broad range of applications. It is easily generalized to any electronic structure method where forces and stresses are still under active development and implementation, such as diffusion Monte Carlo, auxiliary-field Monte Carlo, and stochastic configuration interaction, as well as deterministic approaches such as the random-phase approximation. Accurate and efficient means of geometry optimization could shed light on a broad class of materials and molecules, showing high sensitivity of induced properties to structural variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Revisiting superconductivity in the extended one-band Hubbard model: Pairing via spin and charge fluctuations

The leading superconducting instabilities of the two-dimensional extended repulsive one-band Hubbard model within spin-fluctuation pairing theory depend sensitively on electron density, band, and interaction parameters. We map out the phase diagrams within a random-phase-approximation spin- and charge-fluctuation approach, and find that while B 1g (d x 2 –y 2 ) and B 2g (d xy ) pairing dominates in the absence of repulsive longer-range Coulomb interactions V NN , the latter induces pairing in other symmetry channels, including, e.g., A 2g (g-wave), nodal A 1g (extended s-wave), or nodal E u (p-wave) spin-triplet superconductivity. At the lowest temperatures, transition boundaries in the phase diagrams between symmetry-distinct spin-singlet orders generate complex time-reversal symmetry broken superpositions. By contrast, we find that boundaries between singlet and triplet regions are characterized by first-order transitions. Finally, motivated by recent photoemission experiments, we have determined the influence of an additional explicitly attractive nearest-neighbor interaction, V NN < 0, on the superconducting gap structure. Furthermore, depending on the electronic filling, such an attraction boosts E u (p-wave) spin-triplet or B 1g (d x 2 –y 2 ) spin-singlet ordering.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

SERTA Domain Containing Protein 1 (SERTAD1) Interacts with Classical Swine Fever Virus Structural Glycoprotein E2, Which Is Involved in Virus Virulence in Swine

E2 is the major structural glycoprotein of the classical swine fever virus (CSFV). E2 has been shown to be involved in important virus functions such as replication and virulence in swine. Using the yeast two-hybrid system, we previously identified several host proteins specifically interacting with CSFV E2. Here, we analyze the protein interaction of E2 with SERTA domain containing protein 1 (SERTAD1), a factor involved in the stimulation of the transcriptional activities of different host genes. We have confirmed that the interaction between these two proteins occurs in CSFV-infected swine cells by using a proximity ligation assay and confocal microscopy. Amino acid residues in the CSFV E2 protein that are responsible for mediating the interaction with SERTAD1 were mapped by a yeast two-hybrid approach using a randomly mutated E2 library. Using that information, a recombinant CSFV mutant (E2ΔSERTAD1v) that harbors substitutions in those residues mediating the protein-interaction with SERTAD1 was developed and used to study the role of the E2-SERTAD1 interaction in viral replication and virulence in swine. CSFV E2ΔSERTAD1v, when compared to the parental BICv, showed a clearly decreased ability to replicate in the SK6 swine cell line and a more severe replication defect in primary swine macrophage cultures. Importantly, 80% of animals infected with E2ΔSERTAD1v survived infection, remaining clinically normal during the 21-day observational period. This result would indicate that the ability of CSFV E2 to bind host SERTAD1 protein during infection plays a critical role in virus virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A minimal motif for sequence recognition by mitochondrial transcription factor A (TFAM)

Abstract Mitochondrial transcription factor A (TFAM) plays a critical role in mitochondrial transcription initiation and mitochondrial DNA (mtDNA) packaging. Both functions require DNA binding, but in one case TFAM must recognize a specific promoter sequence, while packaging requires coating of mtDNA by association with non sequence-specific regions. The mechanisms by which TFAM achieves both sequence-specific and non sequence-specific recognition have not yet been determined. Existing crystal structures of TFAM bound to DNA allowed us to identify two guanine-specific interactions that are established between TFAM and the bound DNA. These interactions are observed when TFAM is bound to both specific promoter sequences and non-sequence specific DNA. These interactions are established with two guanine bases separated by 10 random nucleotides (GN10G). Our biochemical results demonstrate that the GN10G consensus is essential for transcriptional initiation and contributes to facilitating TFAM binding to DNA substrates. Furthermore, we report a crystal structure of TFAM in complex with a non sequence-specific sequence containing a GN10G consensus. The structure reveals a unique arrangement in which TFAM bridges two DNA substrates while maintaining the GN10G interactions. We propose that the GN10G consensus is key to facilitate the interaction of TFAM with DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization of quantum chaos by two-point correlation functions

In this work, we propose a characterization of quantum many-body chaos: given a collection of simple operators, the set of all possible pair correlations between these operators can be organized into a matrix with a random-matrix-like spectrum. This approach is particularly useful for locally interacting systems, which do not generically show exponential Lyapunov growth of out-of-time-ordered correlators. We demonstrate the validity of this characterization by numerically studying the Sachdev-Ye-Kitaev model and a one-dimensional spin chain with random magnetic field (XXZ model).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of the Anions on the Interaction Energy between Water and Ionic Liquids

It is essential to understand the interaction energy between water and ionic liquids (ILs) in search of ILs for dehumidification applications. In this paper, the intermolecular interaction energy between water and 1-ethyl-3-methylimidazolium ([EMIM])-based ILs was investigated. The vapor-liquid equilibrium data were first measured for solutions of [EMIM][BF 4 ], [EMIM][N(CN) 2 ], [EMIM][CF 3 SO 3 ], and [EMIM][CH 3 SO 3 ] with water molar fractions of 8–95 % at temperatures of 303–343 K. The IL-IL and water-IL intermolecular interaction energies were determined by using the correlated non-random two-liquid model. The results revealed that fluorine atoms in anions reduce the attraction energy between IL and water, and thus, decrease the water affinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A crystal plasticity model with an atomistically informed description of grain boundary sliding for improved predictions of deformation fields

Crystal plasticity (CP) is a powerful meso-scale technique for deformation modeling in polycrystalline materials. Crystal plasticity models typically do not include an explicit description of grain boundary (GB) sliding, which could lead to inaccurate predictions of strain distributions, especially in the vicinity of GBs. In the present study, a CP model is developed that includes GB sliding as an additional deformation mechanism and models the interaction between slip and GB sliding. Atomistic simulations are used to formulate the constitutive model for GB sliding and its interaction with incident slip. The deformation fields and structure of the GBs are obtained directly from experimental characterization and are faithfully reproduced as bicrystal systems for molecular dynamics simulations. The GBs are modeled as random-type (non-coincidence, asymmetrical) boundaries as observed from experimental data. The underlying atomistic-scale mechanism for pure sliding of random GBs was found to be analogous to fluid-flow. The interaction between incident slip and a sliding GB caused local increases in stress concentration, which further led to a momentary increase in the local sliding rate. The displacement profiles at the sliding GBs computed from the CP model with sliding accommodation are 38% more accurate than the baseline CP model as quantified by the mean squared error between the simulations and experiment. Here these results help improve the sophistication and accuracy of deformation modeling by including physics-based descriptions for GB sliding and its interaction with slip, eventually leading to more reliable predictions of micromechanical quantities.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Entanglement-fidelity limits of photonically networked atomic qubits from recoil and timing

The remote entanglement of two atomic quantum memories through photonic interactions is accompanied by atomic momentum recoil. When the interactions occur at different times, such as from the random emission over the lifetime of the atomic excited state, the difference in recoil timing can expose “which-path” information and ultimately lead to decoherence. Time-bin encoded photonic qubits can be particularly sensitive to asynchronous recoil timing. In this paper we study the limits of entanglement fidelity in atomic systems due to recoil and other timing imbalances and show how these effects can be suppressed or even eliminated through proper experimental design.

Quantum communication↗
DOE OSTI2022

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly

Switchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO 3 – , Ca 2+ , PO 4 3– , and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

plant biomass↗
DOE OSTI2020

Uncertainty Quantification in Scientific ML

The intricate interactions between data sampling, model selection and the inherent randomness in complex systems strongly emphasize the need for a rigorous characterization of ML algorithms. In conventional statistics, uncertainty quantification (UQ) provides this characterization by measuring how accurately a model reflects the physical reality and by studying the impact of different error sources on the prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fine-scale vegetation composition and structure shape spatiotemporal variation in surface albedo across a low Arctic tundra landscape

The unprecedented rate of warming in the Arctic is driving changes in the structure and composition of tundra vegetation. Increases in deciduous tall shrub cover, height, and density are of particular concern, as these changes alter local surface albedo in ways that could amplify effects on the regional surface energy budget (SEB). Despite this importance, significant uncertainties remain in understanding the interplay between fine-scale vegetation patterns and emergent albedo dynamics across space and time. Here, we address these uncertainties by (1) quantifying spatiotemporal variation in surface shortwave albedo and (2) determining the relative influence of fine-scale vegetation composition, structure, and environmental conditions on albedo across a representative low-Arctic tundra landscape on Alaska’s Seward Peninsula. To do this, we synthesized multi-scale, multi-platform remote sensing observations, including a novel Landsat-derived albedo time series, a fine-scale map of Arctic plant functional type (PFT) fractional cover, and airborne LiDAR estimates of canopy height and topography. We show that there are substantial reductions in winter albedo for pixels dominated by tall, woody PFTs (28.13%) relative to pixels dominated by non-woody vegetation, but almost no change in summer albedo (3% increase). Further, we identified a unimodal trend in the relationship between canopy height and the timing of the springtime transition from high (snowy) to low (leafy) albedo (peak at 5.5 m), possibly because of competing ‘snow-fence’ and ‘protrusion’ snow-shrub interactions. To explore the primary drivers of albedo, we constructed a random forest model and found that canopy height and the fractional cover of woody PFTs were as- or more important predictors of winter albedo than topographic features. These findings provide strong evidence for the impacts of local vegetation characteristics on regional surface albedo, highlighting the need for better quantification of snow-shrub interactions to accurately predict the Arctic’s SEB under future environmental change.

Arctic↗
DOE OSTI2021

Charge density wave and superconductivity in the disordered Holstein model

The interplay between electron-electron correlations and disorder has been a central theme of condensed matter physics over the past several decades, with particular interest in the possibility that interactions might cause delocalization of an Anderson insulator into a metallic state, and the disrupting effects of randomness on magnetic order and the Mott phase. In this work, we extend this physics to explore electron-phonon interactions and show, via exact quantum Monte Carlo simulations, that the suppression of the charge density wave correlations in the half-filled Holstein model by disorder can stabilize a superconducting phase. Our simulations thus capture qualitatively the suppression of charge ordered phases and emergent superconductivity recently seen experimentally.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Coexistence and Interaction of Spinons and Magnons in an Antiferromagnet with Alternating Antiferromagnetic and Ferromagnetic Quantum Spin Chains

In conventional quasi-one-dimensional antiferromagnets with quantum spins, magnetic excitations are carried by either magnons or spinons in different energy regimes: they do not coexist independently, nor could they interact with each other. In this Letter, by combining inelastic neutron scattering, quantum Monte Carlo simulations and Random Phase Approximation calculations, we report the discovery and discuss the physics of the coexistence of magnons and spinons and their interactions in Botallackite-Cu 2 (OH) 3 Br. This is a unique quantum antiferromagnet consisting of alternating ferromagnetic and antiferromagnetic Spin-1/2 chains with weak interchain couplings. Furthermore, our study presents a new paradigm where one can study the interaction between two different types of magnetic quasiparticles: magnons and spinons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Implementation and Performance

Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and substrates. Methods based on many-body perturbation theory, such as the random phase approximation (RPA), have previously been limited due to their computational complexity. However, this is now a surmountable barrier due to the advances in computational power available, in particular through modern GPU-based supercomputers. In this work, we describe the implementation of RPA calculations within BerkeleyGW and show its favorable computational performance on large complex systems relevant for catalysis and electrochemistry applications. Our implementation builds off of the static subspace approximation which, by employing a compressed representation of the frequency dependent polarizability, enables the evaluation of the RPA correlation energy with significant acceleration and systematically controllable accuracy. We find that the computational cost of calculating the RPA correlation energy scales only linearly with system size for systems containing up to 50 thousand bands, and is expected to scale quadratically thereafter. We also show excellent strong scaling results across several supercomputers, demonstrating the performance and portability of this implementation.

algorithmic development↗
DOE OSTI2024

Disorder Enhanced Thermalization in Interacting Many-Particle System

We introduce an extension of the non-equilibrium dynamical mean field theory to incorporate the effects of static random disorder in the dynamics of a many-particle system by integrating out different disorder configurations resulting in an effective time-dependent density-density interaction. We use this method to study the non-equilibrium transient dynamics of a system described by the Fermi Anderson-Hubbard model following an interaction and disorder quench. The method recovers the solution of the disorder-free case for which the system exhibits qualitatively distinct dynamical behaviors in the weak-coupling (prethermalization) and strong-coupling regimes (collapse-and-revival oscillations). However, we find that weak random disorder promotes thermalization. In the weak coupling regime, the jump in the quasiparticle weight in the prethermal regime is suppressed by random disorder while in the strong-coupling regime, random disorder reduces the amplitude of the quasiparticle weight oscillations. These results highlight the importance of disorder in the dynamics of realistic many-particle systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Dispersive interactions between standard and Dirac materials and the role of dimensionality

The van der Waals (vdW) interaction plays a prominent role between neutral objects at separations where short ranged chemical forces are negligible. This type of dispersive coupling is determined by the interplay between geometry and response properties of the materials making up the objects. Here, we investigate the vdW interaction between 1D, 2D, and 3D standard and Dirac materials within the Random Phase Approximation, which takes into account collective excitations originating from the electronic Coulomb potential. A comprehensive understanding of characteristic functionalities and scaling laws are obtained for systems with parabolic energy dispersion (standard materials) and crossing linear bands (Dirac materials). By comparing the quantum mechanical and thermal limits the onset of thermal fluctuations in the vdW interaction is discussed showing that thermal effects are significantly pronounced at smaller scales in reduced dimensions.

36 MATERIALS SCIENCE↗