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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unlocking liquid chemisorption in solid matrices: immobilized deep eutectic solvent-ZIF-8 composites for next-generation CO 2 capture

Achieving net-zero emissions by 2050 requires scalable and durable CO 2 capture solutions, with direct air capture (DAC) gaining increasing prominence. Deep eutectic solvents (DESs) have emerged as promising candidates due to their strong chemisorptive properties, but their liquid-phase nature limits integration into solid systems. In this study, we introduce a solid–liquid hybrid approach by immobilizing [TEAB][TEPA] 2 , a highly CO 2 -reactive DES, onto various supports via non-covalent immobilization. This strategy induces solid-like behavior while retaining molecular-level reactivity of the DES. Among the supports including ZIF-8, zeolite Y, zirconia, and alumina, the [TEAB][TEPA] 2 @ZIF-8-56% composite demonstrated promising CO 2 uptake capacity of 2.00 mmol g −1 adsorbent at 1 bar, 1.48 at 0.15 bar, 0.96 at 0.01 bar, and 0.59 at 0.4 mbar. Particularly, we can observe that the chemisorption capacity under 400 ppm conditions is successfully introduced into ZIF-8, whereas pristine ZIF-8 showed negligible uptake under these same conditions. Breakthrough experiments confirmed robust capture behavior under humid conditions. The composite exhibited excellent cycling stability over 100 capture-release cycles, supported by thermogravimetric analysis. In situ DRIFTS verified that the chemisorptive nature of the DES remained intact after immobilization. Additional characterization studies, including FTIR, PXRD, N 2 physisorption, and XPS depth profiling, revealed partial DES infiltration and strong interfacial interactions. Comparative results using alumina-based composites underscored the importance of microporosity in stability. Finally, these findings suggest that DES-MOF composites hold promise as carbon capture materials, bridging liquid-phase functionality and solid-state robustness.

Yoo, Yunsung [Northwestern Univ., Evanston, IL (Un↗
DOE OSTI2025

Sulfide electrolyte additive enables multi-ionic transfer pathways in alkaline iron redox

Traditional alkaline iron (Fe) batteries rely on the conversion reaction between Fe and Fe(OH) 2 but suffer from hydrogen generation upon Fe formation on charging. Fe 2+ /Fe 3+ redox is a promising anode reaction for alkaline Fe batteries, as it alleviates the formation of hydrogen gas during charging. However, achieving complete Fe 2+ /Fe 3+ redox with a one-electron transfer reaction is challenging due to the formation of electrochemically inert Fe 3 O 4 materials. Here, we demonstrate that an alkaline sulfide-containing electrolyte facilitates the reversible multi-ion transfer and transport pathways within (and beyond) the Fe 2+ /Fe 3+ redox system, including Fe(OH) 2 /Fe 3 O 4 conversion, intercalation of hydrosulfide into layered Fe(OH) 2 , and hydrogen deposition, mediated by hydroxyl ions, hydrosulfide anions, and protons, respectively. This multi-ionic charge storage mechanism delivers a compelling discharge capacity of up to 330 mA h g −1 , as determined by chronopotentiometry measurements at a current density of 0.1 A g −1 , exceeding the theoretical iron redox capacity solely relying on Fe 2+ /Fe 3+ redox (∼299 mA h g −1 ). Our study will highlight the potential of alkaline iron redox as a green anode reaction for various aqueous energy storage systems by utilizing a scalable and low-concentration hydrosulfide electrolyte additive.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Small-x structure of oxygen and neon isotopes as seen by the Large Hadron Collider

Results on collisions of O-16 nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. O-16+O-16 collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3+1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on O-16+O-16 and Ne-20+Ne-20 collisions at root s(NN) = 70 GeV and 7 TeV. The choice of Ne-20 is motivated by its strongly elongated geometry, which may respond differently to the effect of the high-energy evolution compared to the more spherical O-16. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Inverse methods for design of soft materials

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide a systematic means for navigating their inherently high-dimensional design spaces to create materials with targeted properties. Furthermore, while multiple physically motivated inverse strategies have been successfully implemented in silico, their translation to guiding experimental materials discovery has thus far been limited to a handful of proof-of-concept studies. In this perspective, we discuss recent advances in inverse methods for design of soft materials that address two challenges: (1) methodological limitations that prevent such approaches from satisfying design constraints and (2) computational challenges that limit the size and complexity of systems that can be addressed. Strategies that leverage machine learning have proven particularly effective, including methods to discover order parameters that characterize complex structural motifs and schemes to efficiently compute macroscopic properties from the underlying structure. We also highlight promising opportunities to improve the experimental realizability of materials designed computationally, including discovery of materials with functionality at multiple thermodynamic states, design of externally directed assembly protocols that are simple to implement in experiments, and strategies to improve the accuracy and computational efficiency of experimentally relevant models.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A non-hierarchical correlation discrete variable representation

The correlation discrete variable representation (CDVR) facilitates (multi-layer) multi-configurational time-dependent Hartree (MCTDH) calculations with general potentials. It employs a layered grid representation to efficiently evaluate all potential matrix elements appearing in the MCTDH equations of motion. The original CDVR approach and its multi-layer extension show a hierarchical structure: the size of the grids employed at the different layers increases when moving from an upper layer to a lower one. In this work, a non-hierarchical CDVR approach, which uses identically structured quadratures at all layers of the MCTDH wavefunction representation, is introduced. Here, the non-hierarchical CDVR approach crucially reduces the number of grid points required, compared to the hierarchical CDVR, shows superior scaling properties, and yields identical results for all three representations showing the same topology. Numerical tests studying the photodissociation of NOCl and the vibrational states of CH 3 demonstrate the accuracy of the non-hierarchical CDVR approach.

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

Effect of self-generated magnetic fields on x-ray emission in Kr-filled targets at the National Ignition Facility

We examine the effects of self-generated magnetic fields in a Kr gas pipe x-ray source platform. X-ray emission from Kr plasma is dependent on the plasma conditions, as the ionization state is largely a function of temperature. Magnetic fields are known to limit heat conduction, which increases temperature. We show that the emission in simulations of the gas pipe x-ray source is dependent on how self-generated magnetic fields are modeled. The inclusion of self-generated magnetic fields in simulations more accurately captures the emission of lower energy x-ray emission (L-shell), bringing results closer to experiments. The modeled x-ray emission and self-generated magnetic fields are shown to be particularly sensitive to the inclusion of the Nernst effect in simulations. Severely limiting the Nernst effect leads to a hotter Kr plasma, which can account for the discrepancy seen in earlier studies. By modifying the Nernst effect multiplier, we can achieve better experimental agreement in x-ray emission from gas pipes; the value of the multiplier that leads to the best agreement is dependent on the laser power of the drive. Currently, the suppression factor of the Nernst effect needed for high power drives (PL>200 TW) is more restrictive than what is currently put forward by non-local models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Superconductivity with T c ≈ 7 K under pressure for Cu- and Au-doped BaFe 2 As 2

It is noteworthy that chemical substitution of BaFe 2 As 2 (122) with the noble elements Cu and Au gives superconductivity with a maximum T c ≈ 3 K, while Ag substitution (Ag-122) stays antiferromagnetic. For Ba(Fe 1–x TM x ) 2 As 2 , TM = Cu, Au, or Ag, and by doping an amount of x = 0.04, a-lattice parameter slightly increases (0.4%) for all TM dopants, while c-lattice decreases (–0.2%) for TM = Cu, barely moves (0.05%) for Au, and increases (0.2%) for Ag. Despite the naive expectation that the noble elements of group 11 should affect the quantum properties of 122 similarly, they produce significant differences extending to the character of the ground state. For the Ag-122 crystal, evidence of only a filamentary superconductivity is noted with pressure. However, for Au and Cu doping (x ≈ 0.03) we find a substantial improvement in the superconductivity, with T c increasing to 7 K and 7.5 K, respectively, under 20 kbar of pressure. As with the ambient pressure results, the identity of the dopant therefore has a substantial impact on the ground state properties. Further, density functional theory calculations corroborate these results and find evidence of strong electronic scattering for Au and Ag dopants, while Cu is comparatively less disruptive to the 122 electronic structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Relativistic hybrid stars in light of the NICER PSR J0740 + 6620 radius measurement

We explore the implications of the recent radius determination of PSR J0740 + 6620 by the NICER experiment, combined with the neutron skin measurement by the PREX-II experiment and the associated inference of the slope of symmetry energy, for the structure of hybrid stars with a strong first-order phase transition from nucleonic to quark matter. Furthermore, we combine a covariant density-functional nucleonic equation of state (EOS) with a constant-speed-of-sound EOS for quark matter. We show that the radius and tidal deformability ranges obtained from GW170817 can be reconciled with the implication of the PREX-II experiment if there is a phase transition to quark matter in the low-mass compact star. In the high-mass segment, the EOS needs to be stiff to comply with the large-radius inference for PSR J0740 + 6620 and J0030 + 0451 with masses M ≃ 2 M ⊙ and M≃1.4 M⊙. We show that twin stars are not excluded, but the mass and radius ranges (with M ≥ M ⊙ ) are restricted to narrow domains ΔM twin ≲ 0.05 M ⊙ and ΔR twin ~ 1.0 km. We also show that the existence of twin configurations is compatible with the light companion in the GW190814 event being a hybrid star in the case of values of the sound-speed square s = 0.6 and s = 1/3.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Clogging, dynamics, and reentrant fluid for active matter on periodic substrates

Here, we examine the collective states of run-and-tumble active matter disks driven over a periodic obstacle array. When the drive is applied along a symmetry direction of the array, we find a clog-free uniform liquid state for low activity, while at higher activity, the density becomes increasingly heterogeneous and an active clogged state emerges in which the mobility is strongly reduced. For driving along nonsymmetry or incommensurate directions, there are two different clogging behaviors consisting of a drive-dependent clogged state in the low activity thermal limit and a drive-independent clogged state at high activity. These regimes are separated by a uniform flowing liquid at intermediate activity. There is a critical activity level above which the thermal clogged state does not occur, as well as an optimal activity level that maximizes the disk mobility. Thermal clogged states are dependent on the driving direction while active clogged states are not. In the low activity regime, diluting the obstacles produces a monotonic increase in the mobility; however, for large activities, the mobility is more robust against obstacle dilution. We also examine the velocity-force curves for driving along nonsymmetry directions and find that they are linear when the activity is low or intermediate but become nonlinear at high activity and show behavior similar to that found for the plastic depinning of solids. At higher drives, the active clustering is lost. For low activity, we also find a reentrant fluid phase, where the system transitions from a high mobility fluid at low drives to a clogged state at higher drives and then back into another fluid phase at very high drives. We map the regions in which the thermally clogged, partially clogged, active uniform fluid, clustered fluid, active clogged, and directionally locked states occur as a function of disk density, drift force, and activity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On the equivalence of nonequilibrium and equilibrium measurements of slip in molecular dynamics simulations

Here, we show that nonequilibrium and equilibrium measurements of slip are consistent, provided the hydrodynamic wall location associated with the equilibrium measurement is properly taken into account. The latter is a strong function of the fluid state and wall-fluid interaction and cannot be neglected as it typically has been. Our results are based on an alternative approach for calculating the hydrodynamic wall location which alleviates most of the difficulties associated with its calculation via a Green-Kubo integral that appear to have contributed to its neglect. Extensive molecular dynamics simulations are used to validate our approach including a model for calculating the slip length that does not involve a Green-Kubo integral.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Matrix-Model Simulations Using Quantum Computing, Deep Learning, and Lattice Monte Carlo

Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black holes, and it underpins the only practical numerical approach to the study of complex high-dimensional supergravity theories. Understanding quantum black holes and the role of entanglement in a holographic setup is of paramount importance for the realization of a quantum theory of gravity. Moreover, a complete numerical understanding of the holographic duality and the emergence of geometric space-time features from microscopic degrees of freedom could pave the way for new discoveries in quantum information science. Euclidean lattice Monte Carlo simulations are the de facto numerical tool for understanding the spectrum of large matrix models and have been used to test the holographic duality. However, they are not tailored to extract dynamical properties or even the quantum wave function of the ground state of matrix models. Quantum computing and deep learning provide potentially useful approaches to study the dynamics of matrix quantum mechanics. If successful in the context of matrix models, these rapidly improving numerical techniques could become the new Swiss army knife of quantum gravity practitioners. In this paper, we perform the first systematic survey for quantum computing and deep-learning approaches to matrix quantum mechanics, comparing them to lattice Monte Carlo simulations. These provide baseline benchmarks before addressing more complicated problems. In particular, we test the performance of each method by calculating the low-energy spectrum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A15 phase Ta 3⁢ Sb thin films: Direct synthesis, charge transport, and spin-orbit torque

Ta 3 ⁢Sb is one of the A15 compounds that have been predicted to have giant spin Hall conductivities due to the gapped Dirac-like band crossings in their electronic structures. We use co-sputtering to directly synthesize thin films of Ta 3 ⁢Sb and identify a large window of Ta:Sb flux ratio that permits the formation of single-phase A15 structure. These sputtered films have an actual Ta:Sb atomic ratio of 4:1, as determined from Rutherford backscattering spectrometry. Their high resistivity, at the Mott-Ioffe-Regel limit, suggests that the electron mean free path is comparable to interatomic distances. From harmonic Hall and spin-torque ferromagnetic resonance measurements, the intrinsic spin Hall conductivity of thin film Ta 3 ⁢Sb is estimated to be in the range of −526 to −1230⁢(ℏ/𝑒)S/cm at 300 K, lower in magnitude than the predicted value of −1400⁢(ℏ/𝑒)S/cm . Here, first-principles calculations of the electronic structure show that the discrepancy is consistent with an increase of the Fermi level due to the nonideal stoichiometry needed to stabilize the A15 structure.

Density functional theory↗
DOE OSTI2024

Variation-Resilient FeFET-Based In-Memory Computing Leveraging Probabilistic Deep Learning

Reliability issues stemming from device level nonidealities of nonvolatile emerging technologies like ferroelectric field-effect transistors (FeFETs), especially at scaled dimensions, cause substantial degradation in the accuracy of in-memory crossbar-based AI systems. Here, in this work, we present a variation-aware design technique to characterize the device level variations and to mitigate their impact on hardware accuracy employing a Bayesian neural network (BNN) approach. An effective conductance variation model is derived from the experimental measurements of cycle-to-cycle (C2C) and device-to-device (D2D) variations performed on FeFET devices fabricated using 28 nm high-k metal gate technology. The variations were found to be a function of different conductance states within the given programming range, which sharply contrasts earlier efforts where a fixed variation dispersion was considered for all conductance values. Such variation characteristics formulated for three different device sizes at different read voltages were provided as prior variation information to the BNN to yield a more exact and reliable inference. Near-ideal accuracy for shallow networks (MLP5 and LeNet models) on the MNIST dataset and limited accuracy decline by ~3.8%–16.1% for deeper AlexNet models on CIFAR10 dataset under a wide range of variations corresponding to different device sizes and read voltages, demonstrates the efficacy of our proposed device-algorithm co-design technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Data-Driven Closures and Assimilation for Stiff Multiscale Random Dynamics

Here, we introduce a data-driven and physics-informed framework for propagating uncertainty in stiff, multiscale random ordinary differential equations (RODEs) driven by correlated (colored) noise. Unlike systems subjected to Gaussian white noise, a deterministic equation for the joint probability density function (PDF) of RODE state variables does not exist in closed form. Moreover, such an equation would require as many phase-space variables as there are states in the RODE system. To alleviate this curse of dimensionality, we instead derive exact, albeit unclosed, reduced-order PDF (RoPDF) equations for low-dimensional observables/quantities of interest. The unclosed terms take the form of state-dependent conditional expectations, which are directly estimated from data at sparse observation times. However, for systems exhibiting stiff, multiscale dynamics, data sparsity introduces regression discrepancies that compound during RoPDF evolution. This is overcome by introducing a kinetic-like defect term to the RoPDF equation, which is learned by assimilating in sparse, low-fidelity RoPDF estimates. Two assimilation methods are considered, namely nudging and deep neural networks, which are successfully tested against Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Assessing Nonlinear Polarization in Electrochemical Cells using AC Impedance Spectroscopy

AC impedance spectroscopy is widely used to evaluate performance limitations in energy storage and conversion devices (e.g., batteries, supercapacitors, and fuel cells). This work shows that integrating the resistive elements in an equivalent circuit as functions of steady-state current enables one to recover overpotentials associated with different processes (e.g., ion migration, charge transfer, and diffusion) in nonlinear electrochemical power supplies. Closed form expressions for diffusion overpotentials are derived using this method for transmissive and reflective boundary conditions and three electrode symmetries (planar, cylindrical, and spherical). Discussion is also extended to macroscopically homogenous porous electrodes which are relevant for most real-world devices. Overall, the approach described herein is a powerful tool to identify rate-limiting steps and guide material/component design.

25 ENERGY STORAGE↗
DOE OSTI2023

Quantum Application Specifications and Benchmarks

This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. The computations focus on quantum simulation tasks, such as quantum dynamics, thermal state preparation and ground state estimation. The primary function of the software is to develop estimates of the requirements for large-scale fault-tolerant quantum computers to solve these scientific computations. The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.

Coffrin, Carleton↗
DOE OSTI2020

Dynamics of Subsiding Shells in Actively Growing Clouds with Vertical Updrafts

The dynamics of a subsiding shell at the edges of actively growing shallow cumulus clouds with updrafts is analyzed using direct numerical simulation. The actively growing clouds have a fixed in-cloud buoyancy and velocity. Turbulent mixing and evaporative cooling at the cloud edges generate a subsiding shell that grows with time. A self-similar regime is observed for first- and second-order moments when normalized with respective maximum values. Internal scales derived from integral properties of the flow problem are identified. A self-similarity analysis using these scales reveals that contrary to classical self-similar flows, the turbulent kinetic energy budget terms and velocity moments scale according to the buoyancy and not with the mean velocity. The shell thickness is observed to increase linearly with time. The buoyancy scale remains time invariant and is set by the initial cloud–environment thermodynamics. The shell accelerates ballistically with a magnitude set by the saturation value of the buoyancy of the cloud–environment mixture. In this regime, the shell is buoyancy driven and independent of the in-cloud velocity. Relations are obtained for predicting the shell thickness and minimum velocities by linking the internal scales with external flow parameters. The values thus calculated are consistent with the thickness and velocities observed in typical shallow cumulus clouds. The entrainment coefficient is a function of the initial state of the cloud and the environment, and is shown to be on the same order of magnitude as fractional entrainment rates calculated for large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Robustness of the Stochastic Parameterization of Subgrid-Scale Wind Variability in Sea Surface Fluxes

Abstract High-resolution numerical models have been used to develop statistical models of the enhancement of sea surface fluxes resulting from spatial variability of sea surface wind. In particular, studies have shown that flux enhancement is not a deterministic function of the resolved state. Previous studies focused on single geographical areas or used a single high-resolution numerical model. This study extends the development of such statistical models by considering six different high-resolution models, four different geographical regions, and three different 10-day periods, allowing for a systematic investigation of the robustness of both the deterministic and stochastic parts of the data-driven parameterization. Results indicate that the deterministic part, based on regressing the unresolved normalized flux onto resolved-scale normalized flux and precipitation, is broadly robust across different models, regions, and time periods. The statistical features of the stochastic part of the model (spatial and temporal autocorrelation and parameters of a Gaussian process fit to the regression residual) are also found to be robust and not strongly sensitive to the underlying model, modeled geographical region, or time period studied. Best-fit Gaussian process parameters display robust spatial heterogeneity across models, indicating potential for improvements to the statistical model. These results illustrate the potential for the development of a generic, explicitly stochastic parameterization of sea surface flux enhancements dependent on wind variability.

Endo, Kota↗