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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interplay of molten salt and dopants in tuning the performance of single-crystalline LiNiO 2

Single-crystalline layered oxide cathodes have seen great research interest in recent years. Adoption of single-crystal morphology improves mechanical robustness and eliminates intergranular boundaries, improving the chemical stability of the cathode. Furthermore, single-crystal cathodes also suffer from worsened lithium-diffusion kinetics stemming from the significantly increased diffusion path lengths. Sluggish lithiation kinetics induce concentration gradients within the cathode particle during cell operation, resulting in the accumulation of lattice strain, which deteriorates cell performance. Foreign dopants have been shown to greatly improve ion diffusion in many high-Ni layered oxide cathode systems. In particular, we identify Ti and Te as promising dopants to ameliorate the slow diffusion kinetics. We find that doping 1 mol.% Te into single crystal LiNiO 2 greatly improves Li + diffusivity, as determined through galvanostatic intermittent titration technique. Further incorporating 2 mol.% Al and pairing with lithium-metal anode in a localized high concentration electrolyte (LHCE) delivers 206 mA h g -1 at C/3 rate and retains 94% capacity after 100 cycles in Li metal half cells. By addressing kinetically mediated degradation with Te doping, and surface-based degradation with Al and LHCE, the cathode experiences very little polarization and overpotential growth, enabling stable cycling with high accessible capacity.

25 ENERGY STORAGE↗
DOE OSTI2021

Single Iridium Atom Doped Ni 2 P Catalyst for Optimal Oxygen Evolution

Single-atom catalysts (SACs) with 100% active sites have excellent prospects for application in the oxygen evolution reaction (OER). However, further enhancement of the catalytic activity for OER is quite challenging, particularly for the development of stable SACs with overpotentials <180 mV. Here, we report an iridium single atom on Ni 2 P catalyst (Ir SA -Ni 2 P) with a record low overpotential of 149 mV at a current density of 10 mA·cm –2 in 1.0 M KOH. The Ir SA -Ni 2 P catalyst delivers a current density up to ∼28-fold higher than that of the widely used IrO 2 at 1.53 V vs RHE. Both the experimental results and computational simulations indicate that Ir single atoms preferentially occupy Ni sites on the top surface. The reconstructed Ir–O–P/Ni–O–P bonding environment plays a vital role for optimal adsorption and desorption of the OER intermediate species, which leads to marked enhancement of the OER activity. Additionally, the dynamic “top-down” evolution of the specific structure of the Ni@Ir particles is responsible for the robust single-atom structure and, thus, the stability property. In conclusion, this Ir SA -Ni 2 P catalyst offers novel prospects for simplifying decoration strategies and further enhancing OER performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Pore-Space-Partition-Enabled Exceptional Ethane Uptake and Ethane-Selective Ethane–Ethylene Separation

A modell material for C 2 H 6 /C 2 H 4 separation would simultaneously have the highest C 2 H 6 uptake capacity and the highest C 2 H 6 /C 2 H 4 selectivity. But such material is elusive. A benchmark material for ethane-selective C 2 H 6 /C 2 H 4 separation is peroxo-functionalized MOF-74-Fe that exhibits the best known separation performance due to its high C 2 H 6 /C 2 H 4 selectivity (4.4), although its C 2 H 6 uptake capacity is moderate (74.3 cm 3 /g). Here, we report a family of pore-space-partitioned crystalline porous materials (CPMs) with exceptional C 2 H 6 uptake capacity and C 2 H 6 /C 2 H 4 separation potential (i.e., C 2 H 4 recovered from the mixture) despite their moderate C 2 H 6 /C 2 H 4 selectivity (up to 1.75). The ethane uptake capacity as high as 166.8 cm 3 /g at 1 atm and 298 K, more than twice that of peroxo-MOF-74-Fe, was previously achieved even though the isosteric heat of adsorption (21.9–30.4 kJ/mol) for these CPMs is as low as about one-third of that for peroxo-MOF-74-Fe (66.8 kJ/mol). While the overall C 2 H 6 /C 2 H 4 separation potentials have not yet surpassed peroxo-MOF-74-Fe, these robust CPMs exhibit outstanding properties including high thermal stability (up to 450 °C) and aqueous stability, low regeneration energy, and a high degree of chemical and geometrical tunability within the same isoreticular framework.

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

Evidence of Au(111) topological states in a kagome analogue lattice and their robustness beyond ultra-low temperatures and defect-free conditions

The experimental realization of kagome lattices that exhibit the predicted coexistence of topological states with high electron kinetics and non-dispersing quantum states remains challenging. Additionally, the robustness of these states against structural perturbations has rarely been explored. Here, we report on the formation of an analogue kagome structure via the electrostatic self-assembly of 4,7-dibromobenzo[c]-1,2,5-thiadiazole (2Br-BTD) molecules on Au(111). Local spectroscopic measurements, supported by theoretical calculations, reveal that the weak molecular coupling reshapes the topological-induced Shockley surface state of Au(111) by imposing a (7 × 7) periodicity, resulting in new band crossings. The molecular overlayer favours the opening of electron gaps at these positions manifested as sharp peaks in dI/dV spectra and electron localization in either the hexagonal or triangular sublattices of the kagome structure. To explore the robustness of these topological states, we monitored their stability under varied conditions, including different temperatures, the unaltered herringbone reconstruction of the Au(111) surface and local structural relaxation of the molecular assembly. These results demonstrate the degree of topological protection of these states, which holds potential for fundamental and applied research.

Austin, Dave [University of Central Florida, Orlan↗
DOE OSTI2022

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey (DES) year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy-bias model and redMaGiC galaxy sample, we obtain 10% constraints on the matter density of the Universe. Here, we also implement a nonlinear galaxy-bias model to probe smaller scales that includes parametrization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. Using the redMaGiC galaxy sample as foreground lens galaxies and adopting the best-fitting cosmological parameters from DES year-1 data, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the S 8 parameter. We find that a scale-, redshift- and sky-area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We trace the source of this correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the S 8 parameter are consistent with previous studies and we find a small shift in the Ω m constraints compared to the fiducial redMaGiC sample. We infer the constraints on the mean host-halo mass of the redMaGiC galaxies in this new sample from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately 1.6 × 10 13 M ⊙ /h.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Describing Function Analysis of Transformer Magnetizing Inductance for Direct Power Control of Back-to-Back Modular Multilevel Converters with Advanced Grid Support

This paper provides a detailed investigation into the application of describing function-based analysis for assessing transformer magnetizing inductance and its impact on system performance. The focus is on a back-to-back modular multilevel converter architecture, designed to interconnect systems operating at different frequencies. The study explores the implementation of a Direct Power Control strategy, examining its effects on transformer magnetizing inductance saturation and offering effective mitigation techniques. Furthermore, the integration of advanced grid support functionalities is highlighted, demonstrating how these enhancements bolster the converter's ability to improve grid stability and power quality, positioning it as a robust solution for modern power systems. The proposed approach is validated through extensive computer simulations based MAT LAB/Simulink domain, supported by significant case study results, confirming its practical effectiveness.

back-to-back modular multilevel converters (B2B- M↗
DOE OSTI2026

Enabling Grid-Forming Control with Fault Ride-Through in Unbalanced Distribution Networks

Distribution networks are often unbalanced, causing oscillatory responses in inverter control designed for balanced conditions. Here, to address this problem, this paper proposes a novel time-domain transformation appropriate for inverter control and enables the decomposition of three-phase unbalanced signals into constant positive and negative components. Relations useful for calculating unbalanced active and reactive power are derived from first principle, providing insight into vector products of unbalanced three-phase signals. Furthermore, a grid-forming control effective under unbalanced conditions is developed, which delivers superior performance while meeting UNIFI1 specifications for grid-forming control under unbalanced conditions. specifications applicable to category 4 inverter-based resource, like setting and regulating frequency/voltage, providing voltage support, sharing active power, injecting negative sequence current, and riding through faults. A current limiter is proposed for safe fault ride-through and integrates with the grid-forming control featuring frequency/voltage droop controllers and current and voltage control loops. The transformation of interconnected inverters is formulated and stability of the proposed control analyzed to support robust parameter selections. The effectiveness of the proposed transformation and grid-forming control is demonstrated through analytical results and real-time simulation of a IEEE 123 distribution network on the Real-Time Digital Simulator. Comparison with existing methods shows that the proposed strategy satisfies the UNIFI specifications with a much better performance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Coastal Sea Level Observations Record the Twentieth-Century Enhancement of Decadal Climate Variability

Changes in the amplitude of decadal climate variability over the twentieth century have been noted, with most evidence derived from tropical Pacific sea surface temperature records. However, the length, spatial coverage, and stability of most instrumental records are insufficient to robustly identify such nonstationarity, or resolve its global spatial structure. Here, it is found that the long-term, stable, observing platform provided by tide gauges reveals a dramatic increase in the amplitude and spatial coherence of decadal (11–14-yr period) coastal sea level (ζ) variability between 1960 and 2000. During this epoch, western North American ζ was approximately out of phase with ζ in Sydney, Australia, and led northeastern U.S. ζ by approximately 1–2 years. The amplitude and timing of changes in decadal ζ variability in these regions are consistent with changes in atmospheric variability. Specifically, central equatorial Pacific wind stress and Labrador Sea heat flux are highly coherent and exhibit contemporaneous, order-of-magnitude increases in decadal power. These statistical relationships have a mechanistic underpinning: Along the western North American coastline, equatorial winds are known to drive rapidly propagating ζ signals along equatorial and coastal waveguides, while a 1–2-yr lag between Labrador Sea heat fluxes and northeastern United States ζ is consistent with a remotely forced, buoyancy-driven, mechanism. Tide gauges thus provide strong independent support for an increase in interbasin coherence on decadal time scales over the second half of the twentieth century, with implications for both the interpretation and prediction of climate and sea level variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Material Discovery and Design Principles of Perovskite Oxides for Reversible Solid Oxide Cells (R-SOC)

Reversible solid oxide cells (R-SOCs) are highly efficient devices for energy conversion and storage, capable of operating for both hydrogen utilization and production. In fuel cell mode, an R-SOC consumes hydrogen or natural gas to generate electricity, while in electrolysis mode, it produces hydrogen from steam. The discover of new materials with rapid oxygen surface exchange kinetics and enduring stability is crucial for the economically viable commercialization of R-SOCs. To facilitate this pursuit, we conducted extensive Density Functional Theory (DFT) calculations and developed Machine Learning (ML) models to predict critical catalytic properties essential for R-SOCs, such as oxygen surface exchange/diffusivity, and area-specific resistance (ASR). BaCoxFeyZrzO3-d(BFCZ)(x+y+z=1) emerged as a promising family of electrode materials with high activity and stability, validated through systematic experimental study. Moreover, a robust numerical multiphysics model was developed to optimize materials and microstructure parameters, providing the ability to predict the performance of functional R-SOCs.

Liu, Jian↗
DOE OSTI2022

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Noble metal catalysts and processes for reforming of methane and other hydrocarbons

Processes for converting methane and/or other hydrocarbons to synthesis gas (i.e., a gaseous mixture comprising H 2 and CO) are disclosed, in which at least a portion of the hydrocarbon(s) is reacted with CO 2 . At least a second portion of the methane may be reacted with H 2 O (steam), thereby improving overall thermodynamics of the process, in terms of reducing endothermicity (ΔH) and the required energy input, compared to “pure” dry reforming in which no H2O is present. Catalysts for such processes advantageously possess high activity and thereby can achieve significant levels of methane conversion at temperatures below those used conventionally under comparable conditions. These catalysts also exhibit high sulfur tolerance, in addition to reduced rates of carbon (coke) formation, even in the processing (reforming) of heavier (e.g., naphtha boiling-range or jet fuel boiling-range) hydrocarbons. The robustness of the catalyst translates to high operating stability. A representative catalyst comprises 1 wt-% Pt and 1 wt-% Rh as noble metals, on a cerium oxide support.

Marker, Terry L.↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Constraints on cosmological parameters and galaxy bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy bias model and redMaGiC galaxy sample, we obtain constraints on the matter content of the universe to be $\Omega_{\rm m} = 0.325^{+0.033}_{-0.034}$. We also implement a non-linear galaxy bias model to probe smaller scales that includes parameterizations based on hybrid perturbation theory, and find that it leads to a 17% gain in cosmological constraining power. Using the redMaGiC galaxy sample as foreground lens galaxies, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the $S_8$ parameter. We find that a scale-, redshift- and sky-area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. After accounting for this decorrelation, we infer the constraints on the mean host halo mass of the redMaGiC galaxies from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately $1.5 \times 10^{13} M_{\odot}/h$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2024

Bipolar Organic Cathodes for Stable and Sustainable Na‐Ion and Rechargeable Al Batteries

Bipolar organic materials have emerged as promising cathode materials for rechargeable batteries because of their high voltage and high capacity. However, they suffer from poor cyclic stability and slow reaction kinetics. In this work, we designed and synthesized two bipolar organic cathode materials, containing carbonyl (n‐type) and amine (p‐type) functional groups, as well as extended conjugation structures, for Na‐ion batteries (NIBs) and rechargeable aluminum batteries (RABs). As universal electrode materials, bipolar organic materials exhibited exceptional electrochemical performance in terms of high capacity, high voltage, long cycle life, and fast rate capability. Further, the extended conjugation structures in backbones of the bipolar organic materials facilitate the π–π stacking with graphene, playing a critical role in the high performance. Furthermore, the formation of a stable and robust NaF‐rich cathode electrolyte interphase was shown to stabilize the bipolar organic cathode in NIBs. Electrochemical kinetic measurements reveal that both functional groups undergo reversible redox reactions. Specifically, the electron transfer rate constant of the p‐type amine group is one order of magnitude higher than that of the n‐type carbonyl group. These results highlight the efficacy of developing bipolar organic materials for achieving high‐performance organic cathode in NIBs and RABs.

25 ENERGY STORAGE↗
DOE OSTI2026

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗
DOE OSTI2022

Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability

This paper describes a milling stability identification approach that simultaneously considers: physics-based models for the tool tip frequency response functions and stability predictions; the binary result from a milling test (automatically labeled as stable or unstable based on frequency content); chatter frequency when an unstable result is obtained; and user risk tolerance. The algorithm applies probabilistic Bayesian machine learning with adaptive, parallelized Markov Chain Monte Carlo sampling to update the probability of stability with each milling test. Furthermore, the result is a robust solution for rapid convergence to optimized milling parameters for maximum metal removal rate using all available information.

42 ENGINEERING↗