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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tuning the Structural and Magnetic Properties in Mixed Cation Mn x Co 2– x P 2 S 6

The metal thiophosphates (MTP), M 2 P 2 S 6, are a versatile class of van der Waals materials, which are notable for the possibility of tuning their magnetic properties with the incorporation of different transition-metal cations. Further, they also offer opportunities to probe the independent and synergistic role of the magnetically active cation sublattice when coupled to P 2 Q 6 polyhedra. Herein, we report the structural, magnetic, and electronic properties of the series of MTPs, Mn x Co 2– x P 2 S 6 ( x = 0.25, 0.5, 1, 1.5, 1.75) synthesized by the P 2 S 5 flux method. In this work, structural and elemental analysis indicates a homogeneous stoichiometry in the Mn x Co 2– x P 2 S 6 compounds. We observe that a correlation is apparent between the intensities of specific Raman modes and Raman shifts with respect to the alloying ratio between Mn and Co. Magnetic susceptibility measurements indicate that the alloyed systems adopt an ordered antiferromagnetic (AFM) configuration with a dependence of the Néel temperature on the alloying ratio. A possible magnetic frustration behavior was observed for the composition MnCoP 2 S 6 due to magnetic moment compensation as the alloying ratio between Mn and Co approaches parity. Interestingly, mixed oxidation states of the metal cation species are also observed in Mn x Co 2– x P 2 S 6 along with a linear dependence of the work function on the alloying ratio of Mn and Co.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Revisiting Conversion Reaction Mechanisms in Lithium Batteries: Lithiation-Driven Topotactic Transformation in FeF 2

Intercalation-type electrodes have now been commonly employed in today’s batteries as such materials are capable of storing and releasing lithium reversibly via topotactic transformation, conducive to small structural change, but they have limited interstitial sites to hold Li. In contrast, conversion electrodes feature high Li-storage capacity, but often undergo large structural change during (de)lithiation, resulting in cycling instability. One exception is iron fluoride (FeF 2 ), a conversion-type cathode that exhibits both high capacity and high cycling stability. Herein, we report a lithiation-driven topotactic transformation in a single crystal of FeF2, unveiled by in situ visualization of the spatial and crystallographic correlation between the parent and converted phases. Specifically, conversion in FeF 2 resembles the intercalation process but involves transport of both Li + and Fe 2+ ions within the F-anion array, leading to formation of Fe preferentially along specific crystallographic orientations of FeF 2 . Throughout the process, the F-anion framework is retained, creating a checkerboard-like structure, within which the volume change is largely compensated, thereby enabling the high cyclability in FeF 2 . Lastly, findings from this study, with unique insights into conversion reaction mechanisms, may help to pave the way for designing conversion-type electrodes for the next-generation high energy lithium batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗
DOE OSTI2021

Structural evolution of a DNA repair self-resistance mechanism targeting genotoxic secondary metabolites

Abstract Microbes produce a broad spectrum of antibiotic natural products, including many DNA-damaging genotoxins. Among the most potent of these are DNA alkylating agents in the spirocyclopropylcyclohexadienone (SCPCHD) family, which includes the duocarmycins, CC-1065, gilvusmycin, and yatakemycin. The yatakemycin biosynthesis cluster in Streptomyces sp. TP-A0356 contains an AlkD-related DNA glycosylase, YtkR2, that serves as a self-resistance mechanism against yatakemycin toxicity. We previously reported that AlkD, which is not present in an SCPCHD producer, provides only limited resistance against yatakemycin. We now show that YtkR2 and C10R5, a previously uncharacterized homolog found in the CC-1065 biosynthetic gene cluster of Streptomyces zelensis , confer far greater resistance against their respective SCPCHD natural products. We identify a structural basis for substrate specificity across gene clusters and show a correlation between in vivo resistance and in vitro enzymatic activity indicating that reduced product affinity—not enhanced substrate recognition—is the evolutionary outcome of selective pressure to provide self-resistance against yatakemycin and CC-1065.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Superconductivity in the doped quantum spin liquid on the triangular lattice

Abstract Broad interest in quantum spin liquid (QSL) phases was triggered by the notion that they can be viewed as insulating phases with preexisting electron pairs, such that upon light doping they might automatically yield high temperature superconductivity. Yet despite intense experimental and numerical efforts, definitive evidence showing that doping QSLs leads to superconductivity has been lacking. We address the problem of a lightly doped QSL through a large-scale density-matrix renormalization group study of the t - J model on finite-circumference triangular cylinders with a small but nonzero concentration of doped holes. We provide direct evidences that doping QSL can naturally give rise to d -wave superconductivity. Specifically, we find power-law superconducting correlations with a Luttinger exponent, K s c ≈ 1, which is consistent with a strongly diverging superconducting susceptibility, $${\chi }_{sc} \,\sim\, {T}^{-(2\,-\,{K}_{sc})}$$ χ s c ~ T − ( 2 − K s c ) as the temperature T → 0. The spin–spin correlations—as in the undoped QSL state—fall exponentially which suggests that the superconducting pair-pair correlations evolve smoothly from the insulating parent state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Nuclear shell structure governs short-range nucleon pairing

Atomic nuclei are intricate quantum systems in which nucleons (protons and neutrons) are held together by the strong nuclear force. At very short distances, nucleons can momentarily form high-momentum pairs—known as short-range-correlated pairs—that shape the high-momentum structure of nuclear matter. Studying how nucleons form short-range-correlated pairs provides a rare experimental window into the short-distance behaviour of the strong interaction. Here, in this study, we use the scattering of high-energy electrons from 40 Ca, 48 Ca and 54 Fe, chosen for their distinct shell structures, to probe the formation of short-range-correlated pairs. Unexpectedly, we find that short-range-correlated pairing depends far more on the specific quantum orbitals occupied by protons and neutrons than on the nuclear mass or neutron–proton imbalance. This dependence is much stronger than that predicted by theoretical models. Our results point to a need for new angular-momentum quantum selection rules governing short-range nucleon pairing and reveal a deep connection between long-range nuclear shell structure and short-range interactions.

Nguyen, D. [Thomas Jefferson National Accelerator ↗
DOE OSTI2023

Magnetic coupling between Fe(NO) spin probe ligands through diamagnetic Ni II , Pd II and Pt II tetrathiolate bridges

Reaction of the nitrosylated-iron metallodithiolate ligand, paramagnetic (NO)Fe(N 2 S 2 ), with [M(CH 3 CN) n ][BF 4 ] 2 salts (M = Ni II , Pd II , and Pt II ; n = 4 or 6) affords di-radical tri-metallic complexes in a stairstep type arrangement ([FeMFe] 2+ , M = Ni, Pd, and Pt), with the central group 10 metal held in a MS 4 square plane. These isostructural compounds have nearly identical ν(NO) stretching values, isomer shifts, and electrochemical properties, but vary in their magnetic properties. Despite the intramolecular Fe∙∙∙Fe distances of ca. 6 Å, antiferromagnetic coupling is observed between {Fe(NO)} 7 units as established by magnetic susceptibility, EPR, and DFT studies. The superexchange interaction through the thiolate sulfur and central metal atoms is on the order of Ni II < Pd II $\ll$ Pt II with exchange coupling constants (J) of -3, -23, and -124 cm -1 , consistent with increased covalency of the M–S bonds (3d < 4d < 5d). This trend is reproduced by DFT calculations with molecular orbital analysis providing insight into the origin of the enhancement in the exchange interaction. Specifically, the magnitude of the exchange interaction correlates surprisingly well with the energy difference between the HOMO and HOMO-1 orbitals of the triplet states, which is reflected in the central metal's contribution to these orbitals. These results demonstrate the ability of sulfur-dense metallodithiolate ligands to engender strong magnetic communication by virtue of their enhanced covalency and polarizability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗
DOE OSTI2020

Area and thickness dependence of Auger recombination in nanoplatelets

The ability to control both the thickness and the lateral dimensions of colloidal nanoplatelets offers a test-bed for area and thickness dependent properties in 2D materials. An important example is Auger recombination, which is typically the dominant process by which multiexcitons decay in nanoplatelets. In this report, we uncover fundamental properties of biexciton decay in nanoplatelets by comparing the Auger recombination lifetimes based on interacting and noninteracting formalisms with measurements based on transient absorption spectroscopy. Specifically, we report that electron-hole correlations in the initial biexcitonic state must be included in order to obtain Auger recombination lifetimes in agreement with experimental measurements and that Auger recombination lifetimes depend nearly linearly on the lateral area and somewhat more strongly on the thickness of the nanoplatelet. We also connect these scalings to those of the area and thickness dependencies of single exciton radiative recombination lifetimes, exciton coherence areas, and exciton Bohr radii in these quasi-2D materials.

2D materials↗
DOE OSTI2019

Phase transition preceding magnetic long-range order in the double perovskite Ba 2 NaOsO 6

Recent theoretical studies [G. Chen et al., Phys. Rev. B 82, 174440 (2010); H. Ishizuka et al., Phys. Rev. B 90, 184422 (2014)] for the magnetic Mott insulator Ba 2 NaOsO 6 have proposed a low-temperature order parameter that breaks lattice rotational symmetry without breaking time reversal symmetry, leading to a nematic phase just above the magnetic ordering temperature. We present high-resolution calorimetric and magnetization data of the same Ba 2 NaOsO 6 single crystal and show evidence for a weakly field-dependent phase transition occurring at a temperature of T s ≈ 9.5K, above the magnetic ordering temperature of T c ≈ 7.5K. This transition appears as a broadened step in the low-field temperature dependence of the specific heat. The evolution of the phase boundary with applied magnetic field suggests that this phase coincides with the phase of broken local point symmetry seen in NMR experiments at high fields [L. Lu et al., Nat. Commun. 8, 14407 (2017)]. Here, the magnetic field dependence of the specific heat provides clear indications for magnetic correlations persisting at temperatures between T c and T s where long-range magnetic order is absent, giving support for the existence of the proposed nematic phase.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pairing correlations in the cuprates: A numerical study of the three-band Hubbard model

We study the three-band Hubbard model for the copper oxide plane of the high-temperature superconducting cuprates using determinant quantum Monte Carlo and the dynamical cluster approximation (DCA) and provide a comprehensive view of the pairing correlations in this model using these methods. Specifically, we compute the pair-field susceptibility and study its dependence on temperature, doping, interaction strength, and charge-transfer energy. Using the DCA, we also solve the Bethe-Salpeter equation for the two-particle Green's function in the particle-particle channel to determine the transition temperature to the superconducting phase on smaller clusters. Our calculations reproduce many aspects of the cuprate phase diagram and indicate that there is an “optimal” value of the charge-transfer energy for the model where T c is largest. Finally, these results have implications for our understanding of superconductivity in both the cuprates and other doped charge-transfer insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Modification of Quark-Gluon Distributions in Nuclei by Correlated Nucleon Pairs

We extend the QCD Parton Model analysis using a factorized nuclear structure model incorporating individual nucleons and pairs of correlated nucleons. Our analysis of high-energy data from lepton deep-inelastic scattering, Drell-Yan, and W and Z boson production simultaneously extracts the universal effective distribution of quarks and gluons inside correlated nucleon pairs, and their nucleus-specific fractions. Such successful extraction of these universal distributions marks a significant advance in our understanding of nuclear structure properties connecting nucleon- and parton-level quantities. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Impact of Electrolyte Additives on the Lifetime of High Voltage NMC Lithium-Ion Pouch Cells

This work involves improving the lifetime of lithium-ion cells during high voltage cycling using electrolyte additives. Three generations of electrolyte additives were investigated and screened in NMC442/graphite pouch cells using a 24 h voltage-hold protocol at 40 degrees C to accelerate oxidative reactions occurring at 4.4 V. Once promising additives and combinations were identified, they were then tested in cobalt-free NMC640/graphite cells for long-term cycling to upper cutoff voltages of 4.3, 4.4, and 4.5 V at temperatures of 20, 40, and 55 degrees C. Degradation mechanisms were probed using dV/dQ analysis, micro-X-ray fluorescence spectroscopy, and electrochemical impedance spectroscopy. The primary failure mode of cells held at high voltages is due to increase in cell impedance, which is correlated to the dissolution of transition metals, specifically manganese, originating from the positive electrode. We believe this dissolution is presumably due to the formation of a high impedance rock salt surface layer on the NMC positive electrode particles. Such deleterious outcomes can be limited by selecting an appropriate electrolyte additive package. It is hoped that this paper can provide a starting point for developing NMC Li-ion cells that can operate to voltages as high as 4.4 V and still display long lifetimes.

Azam, Saad↗
DOE OSTI2020

Principal Component Analysis for Extremes and Application to U.S. Precipitation

Here, we propose a method for analyzing extremal behavior through the lens of a most efficient basis of vectors. The method is analogous to principal component analysis, but is based on methods from extreme value analysis. Specifically, rather than decomposing a covariance or correlation matrix, we obtain our basis vectors by performing an eigendecomposition of a matrix that describes pairwise extremal dependence. We apply the method to precipitation observations over the contiguous United States. We find that the time series of large coefficients associated with the leading eigenvector shows very strong evidence of a positive trend, and there is evidence that large coefficients of other eigenvectors have relationships with El Niño–Southern Oscillation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Electron dynamics in extended systems within real-time time-dependent density-functional theory

Due to a beneficial balance of computational cost and accuracy, real-time time-dependent density-functional theory has emerged as a promising first-principles framework to describe electron real-time dynamics. Here we discuss recent implementations around this approach, in particular in the context of complex, extended systems. Results include an analysis of the computational cost associated with numerical propagation and when using absorbing boundary conditions. Here we extensively explore the shortcomings for describing electron–electron scattering in real time and compare to many-body perturbation theory. Modern improvements of the description of exchange and correlation are reviewed. In this work, we specifically focus on the Qb@ll code, which we have mainly used for these types of simulations over the last years, and we conclude by pointing to further progress needed going forward.

2D materials↗
DOE OSTI2020

Long Term Degradation of LSM Based SOFC Cathodes: Use of a Proven Accelerated Test Regimen

The overall goals of the program were: • To understand the microstructural basis of long-term performance loss in solid oxide fuel cells (SOFCs) with cathodes based on lanthanum strontium manganite (LSM, (La 1–x Sr x ) 1–yM nO 3±z ); • To develop strategies for optimizing LSM–based cathodes that achieve improved long-term performance, while exhibiting microstructural and chemical stability, for commercial fuel cell systems. The research project carried out accelerated testing of SOFCs with LSM-based cathodes of selected compositions. After intervals of accelerated testing (and control tests using non-accelerated conditions), the cells underwent extensive microstructural characterization to determine the physical and chemical changes in the cells. By analysis of a) the results of the testing, b) the observed microstructural changes, and c) the differences in these correlations between different cathode compositions and test durations, the research: • Identified a correlation between microstructural change and performance loss: specifically, between decrease of three-phase boundary (TPB) density and increase of area specific re-sistance (ASR) during operation; • Identified a cathode composition parameter — Mn excess, defined as 1/(1–y) in (La 1–x Sr x ) 1–y MnO 3±z ) — and how it affects TPB density, ASR and change of cell performance over time.

08 HYDROGEN↗
DOE OSTI2025

Representing Complex Systems as Graphs for Debugging and Predictive Maintenance-Preliminary Thoughts

Representing complex systems as graphs enables use of mathematical tools to identify faults or predict failures. Graph nodes correspond to individual modules or subsystems, and edges link coupled system parts. ‘Probes’ measure the node outputs, monitoring the system health for unexpected behavior. Assuming one cannot probe every point, within a system, the fault correlates to a region—not necessarily the specific location. Bayesian networks trained to understand fault patterns can accurately identify the source. The diagnostic tool described aides debugging by pinpointing system failure causes. For predictive maintenance, probe data develop probability distribution functions describing subsystem mean time to failure. Unit lifetime can be estimated through these probability distributions. Two approaches include using Bayesian classifiers to infer the system failure source and developing maintenance schedules by treating systems as collections of random variables. When failure behavior does not follow a closed form function, use of similarity models is proposed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolomics provides a unique snapshot into the world of small molecules and the complex biological processes that govern the human, animal, plant, and environmental ecosystems encapsulated by the One Health modeling framework. However, this “molecular snapshot” is only as informative as the number of metabolites confidently identified within it. The spectral similarity (SS) score is traditionally used to identify compound(s) in mass spectrometry approaches to metabolomics, where spectra are matched to reference libraries of candidate spectra. Unfortunately, there is little consensus on which of the dozens of available SS metrics should be used. This lack of standard SS score creates analytic uncertainty and potentially leads to issues in reproducibility, especially as these data are integrated across other domains. In this work, we use metabolomic spectral similarity as a case study to showcase the challenges in consistency within just one piece of the One Health framework that must be addressed to enable data science approaches for One Health problems. Here, using a large cohort of datasets comprising both standard and complex datasets with expert-verified truth annotations, we evaluated the effectiveness of 66 similarity metrics to delineate between correct matches (true positives) and incorrect matches (true negatives). We additionally characterize the families of these metrics to make informed recommendations for their use. Our results indicate that specific families of metrics (the Inner Product, Correlative, and Intersection families of scores) tend to perform better than others, with no single similarity metric performing optimally for all queried spectra. This work and its findings provide an empirically-based resource for researchers to use in their selection of similarity metrics for GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

59 BASIC BIOLOGICAL SCIENCES↗