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

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

The Decay of Optical Emission Form the Gamma-Ray Burst GRB 970228

The origin of gamma-ray bursts has been one of the great unsolved mysteries in high-energy astrophysics for almost 30 years. The recent discovery of fading sources at X-ray and optical wave-lengths coincident with the location of the gamma-ray burst GRB970228 therefore provides an unprecedented opportunity to probe the nature of these high-energy events. The optical counterpart appears to be a transient point source embedded in a region of extended nebulosity, the latter having been tentatively identified as a high-redshift galaxy. This would seem to favour models that place gamma-ray bursts at cosmological distances, although a range of mechanisms for producing the bursts is still allowed. A crucial piece of information for distinguishing between such models is how the brightness of the optical counterpart evolves with time. Here we re-evaluate the existing photometry of the optical counterpart of GRB970228 to construct an optical light curve for the transient event. We find that between 21 hours and six days after the burst, the R-band brightness decreased by a factor of approx. 50, with any subsequent decrease in brightness occurring at a much slower rate. As the point source faded, it also became redder. The initial behaviour of the source appears to be consistent with the 'fireball' model, in which the burst results from the merger of two neutron stars, but the subsequent decrease in the rate of fading may prove harder to explain. The gamma-ray burst of 28 February 1997, detected with the Gamma-Ray Burst Monitor on board the BeppoSAX satellite, and located with an approx. 3 feet radius position with the Wide Field Camera on the same satellite, was the first for which a fading X-ray and optical counterpart were discovered. The optical Counterpart was discovered from a comparison of V- and I-band images taken with the William Herschel Telescope (WHT) on February 28.99 UT, and the Isaac Newton Telescope (INT; V band) and the WHT (I band) on March 8.8 uT.

Galama, T.↗
NASA NTRS2005

Displacing Unpredictable Nulls in Antenna Radiation Patterns

A method of maintaining radio communication despite the emergence of unpredictable fades and nulls in the radiation pattern of an antenna has been proposed. The method was originally intended to be applied in the design and operation of a radio antenna aboard a robotic exploratory vehicle on a remote planet during communication with a spacecraft in orbit around the planet. The method could also be applied in similar terrestrial situations for example, radio communication between two ground vehicles or between a ground vehicle and an aircraft or spacecraft. The method is conceptually simple, is readily adaptable to diverse situations, and can be implemented without adding greatly to the weight, cost, power demand, or complexity of a system to which it may be applied. The unpredictable fades and nulls in an antenna radiation pattern arise because of electromagnetic interactions between the antenna and other objects within the near field of the antenna (basically, objects within a distance of a few wavelengths). These objects can include general vehicle components, masts, robotic arms, other antennas, the ground, and nearby terrain features. Figure 1 presents representative plots of signal strength versus time during a typical pass of a spacecraft or aircraft through the far field of such an antenna, showing typical nulls and fades caused by nearby objects. The traditional approach to ensuring reliability of communication in the presence of deep fades calls for increasing the effective transmitter power and/or reducing the receiver noise figure at the affected ground vehicle, possibly in combination with appropriate redesign of the equipment at the spacecraft or aircraft end of the communication link. These solutions can be expensive and/or risky and, depending on the application, can add significantly to weight, cost, and power demand. The proposed method entails none of these disadvantages.

Lux, James↗
NASA NTRS2018

Metabrain for Embedded Cognition (MBEC)

This study presents the application of Hidden Markov Models (HMM) to determine specialized features without expert input. Specifically, the application of such a method for classification of high multi-path fading is targeted, for demonstrating the feasibility of such an approach. This is the first step in the development of a meta-brain for embedded cognition (M-BEC) suite that can be used to apply machine learning to various communication systems at NASA GRC. The project explores the concept of fading and how it affects communication systems in a negative way. Currently, supervised learning methods are used to study the effects of fading on space links. However, such models rely on expert features to make predictions as to the state of a link and whether fading is present. This project offers the possibility of having the HMM learn what characteristics are important and make predictions based on those characteristics. This project explores Hidden Markov Models, their theory and applications to various problems, as well as the underlying equations and assumptions. A preliminary result is presented and recommendations are made as to the use of such an approach for communications systems.

Propagation↗
NASA NTRS2019

Vortex Radiometry: Enabling Frequency Agile Communications

Exponential proliferation of UAVs and CubeSats puts NASA's high priority communication systems at risk. UAVs and CubeSats are easy to acquire, modify and build, making it extremely likely that some will be used in unauthorized ways. While these systems provide several benefits to society, their increased use also increases the probability of unintentional signal interference, and even deliberate jamming of NASA's communication systems.This paper presents an algorithm to determine 1) when an interference induced fade will occur, 2) how long the fade will persist for and 3) how intense the fade will be. The algorithm requires data collected from Vortex Radiometers (VRs), which probe the RF environment using annular antenna beam patterns. A set of numerical simulations show that a multi-beam VR system can instruct a cognitive antenna to switch between Ka- and X-Band communications, in order to avert interference from small diameter noise sources. Analysis of the simulation results indicate that practical VR systems will require several concentric annular beam patterns, in order to mitigate fades from noise sources of various sizes. The paper concludes by identifying technology challenges that need to be overcome to achieve these capabilities.

Orbital Angular Momentum↗
NASA NTRS2020

Validation of a Digital Noise Power Integration Technique for Radiometric Clear Sky Attenuation Estimation at Q-band

This paper presents the validation of a digital signal processing technique that can be used to estimate radiometric sky noise, and hence, atmospheric absorption, within existing digital receivers at little/no additional cost. To demonstrate this, a receiver was constructed that simultaneously records the beacon signal power from the ALPHASAT Aldo Paraboni technology demonstration payload, as well as the integrated noise power in the adjacent band. Calibration from the digital radiometer is performed using tip-curve calibration procedures. Atmospheric fading is then obtained by observing the beacon as well as the radiometric signals. This enables the comparison of fading obtained by the two techniques and provides a means to calibrate the received beacon power level to obtain total atmospheric attenuation. It is shown that for low levels of fading, up to a few dB, the two techniques provide good agreement. This approach can therefore provide a low-cost option for geostationary mmwave satellite channel measurements in the low fading regime, which can be useful in the design and operation of the feeder links in emerging satcom systems.

radiometer↗
DOE OSTI2022

Computational Elucidation of Mechanical Degradation in NMC Cathodes: Impact on Cell Performance

Next-generation lithium ion batteries are expected to demonstrate superior energy and power density with longer cycle life for successful electrification of the automobile, aviation, and marine industries. Adoption of lithium metal anodes with solid electrolytes can help to achieve that goal given that the dendrite-related issues are solved eventually. Another possibility is to use Ni-rich high-capacity NMC cathode materials with liquid and/or solid electrolytes, which presently experiences rapid capacity fade while charged to higher voltages. Several mechanical and chemical degradation mechanisms are active within these NMC-based cathode particles. Recent experimental research activities attempted to correlate the mechanical damage with the capacity fade experienced by Ni-rich LiNi x Mn y Co z O 2 (x+y+z = 1) (NMC) cathodes. Here, a computational framework is developed in this study capable of quantifying the evolution of inter primary particle and cathode/electrolyte interfacial fracture experienced by the poly- and single-crystalline NMC cathodes during charge/discharge operation. Influences of mechanical degradation on the overall cell capacity, while operating with liquid and/or solid electrolytes, are successfully characterized. Decreasing the size of the cathode primary particles, or the size of the single-crystalline cathodes, can mitigate the overall mechanical degradation, and subsequent capacity fade, experienced by NMC cathodes. The developed theoretical methodology can help the engineers and scientists to better understand the mechanical degradation mechanism prevalent in Ni-rich NMC cathodes and build superior lithium ion-based energy storage devices for the application in next-generation devices.

25 ENERGY STORAGE↗
DOE OSTI2021

Performance and lifetime of intercalative water deionization cells for mono- and divalent ion removal

We report intercalative deionization (IDI) uses two cation intercalation electrodes separated by an anion exchange membrane in a symmetric cell design that has the potential to deliver electrochemically desalinated water in an energy- and water-efficient way. Here, we define and measure metrics to describe the performance and lifetime of IDI cells and compare them for NaCl and CaCl 2 feed solutions. With 20 mM NaCl, NiHCF/AEM/NiHCF flow cells achieve 10 mM average concentration change at a productivity of 20 l/h/m 2 and 5 mM average concentration change at 130 l/h/m 2 . In both cases the cells are operated at a 3C current rate and consume ~30 Wh/m 3 of energy. With 10 mM CaCl 2 , the specific capacity and salt removal of IDI flow cells is ~4 times lower. NiHCF/NiHCF beaker cells with CaCl 2 electrolyte suffer from strong capacity fade, while the same cells with NaCl electrolyte achieve 500 cycles without any capacity fade. Our post-mortem analysis using X-ray diffraction, secondary electron microscopy, energy dispersive X-ray spectroscopy, synchrotron-based X-ray absorption spectroscopy and micro X-ray fluorescence mapping reveals that NiHCF dissolves upon repeated intercalation with Ca 2+ , releasing residual K + , Ni 2+ and Fe(CN) 6 3 , which precipitates as a crystalline decomposition product on the electrodes. This side reaction deprives the active material NiHCF of charge compensating Fe, and thus accounts for the observed capacity fade.

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

Forecasting battery capacity and power degradation with multi-task learning

Lithium-ion batteries degrade due to usage and exposure to environmental conditions, which affects their capability to store energy and supply power. Accurately predicting the capacity and power fade of lithium-ion battery cells is challenging due to intrinsic manufacturing variances and coupled nonlinear ageing mechanisms. In this paper, we propose a data-driven prognostics framework to predict both capacity and power fade simultaneously with multi-task learning. The model is able to predict the degradation trajectory of both capacity and internal resistance together with knee-points and end-of-life points accurately at early-life stage. The validation shows an average percentage error of 2.37% and 1.24% for the prediction of capacity fade and resistance rise, respectively. The model's ability to accurately predict the degradation, facing capacity and resistance estimation errors, further demonstrates the model's robustness and generalizability. Compared with single-task learning models for forecasting capacity and power degradation, the model shows a significant prediction accuracy improvement and computational cost reduction. This work presents the highlights of multi-task learning in the degradation prognostics for lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantifying the Influence of Charge Rate and Cathode-Particle Architectures on Degradation of Li-Ion Cells Through 3D Continuum-Level Damage Models

In this article, we develop a 3D, continuum-level damage model implemented on statistically generated LiNi 0.5 Mn 0.3 Co 0.2 O (NMC 532) secondary cathode particles. The primary motivation of the particle-level model is to inform cathode-particle design through detailed exploration of the influence of secondary and primary particle sizes on the damage predicted during operation, and determine charging profiles that reduce cathode fracture. The model considers NMC 532 secondary particles containing an agglomeration of anisotropic, randomly oriented grains. These brittle, Ni-based cathodes are prone to mechanical degradation, which reduces overall battery cycle life. The model predicts that secondary-particle fracture is primarily due to non-ideal grain interactions and high-rate charge demands. The model predicts that small secondary-particles with large grains develop significantly less damage than larger secondary particles with small grains. The model predicts most of the chemo-mechanical damage accumulates in the first few cycles. The chemo-mechanical model predicts monotonically increasing capacity fade with cycling and rate. Comparing to experimental results, the model is well suited for capturing initial capacity fade mechanisms, but additional physics is required to capture long-term capacity fade effects.

25 ENERGY STORAGE↗
DOE OSTI2022

Promoting Reversibility of Multielectron Redox in Alkali-Rich Sulfide Cathodes through Cryomilling

We report conventional cathodes for Li-ion batteries (LIBs) are reaching their theoretical capacity limits. One way to meet the growing demands for high-capacity LIBs is by developing so-called Li-rich cathode materials that greatly benefit from additional capacities from anionic moieties in the structure. Li-rich materials are intrinsically subject to higher degrees of (de)intercalation, leaving the particles more prone to fractures and thus rapid capacity fade. Alkali-rich LiNaFeS 2 reversibly cycles with capacities exceeding 300 mAh g -1 , but its capacity fades faster than an isostructural material Li 2 FeS 2 . Using synchrotron-based transmission X-ray microscopy (TXM), we demonstrate that the capacity fade of LiNaFeS 2 stems from particle fractures in the first charge cycle. We improve the cycling performance of LiNaFeS 2 by means of cryomilling, which enhances capacity retention at cycle 50 by 76%. Through crystallographic and morphological characterization techniques, we confirm that cryomilling not only decreases particle and crystallite size while increasing microstrain but also prevents particles from fracturing. Cryomilling is a powerful tool to engineer nanoscale battery materials, and TXM allows the direct observation of morphological changes of the particles, which can be leveraged to develop next-generation cathode materials for LIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Oxygen Loss in Layered Oxide Cathodes for Li-Ion Batteries: Mechanisms, Effects, and Mitigation

Layered lithium transition metal oxides derived from LiMO 2 (M = Co, Ni, Mn, etc.) have been widely adopted as the cathodes of Li-ion batteries for portable electronics, electric vehicles, and energy storage. Oxygen loss in the layered oxides is one of the major factors leading to cycling-induced structural degradation and its associated fade in electrochemical performance. Herein, we review recent progress in understanding the phenomena of oxygen loss and the resulting structural degradation in layered oxide cathodes. We first present the major driving forces leading to the oxygen loss and then describe the associated structural degradation resulting from the oxygen loss. Here, we follow this analysis with a discussion of the kinetic pathways that enable oxygen loss, and then we address the resulting electrochemical fade. Finally, we review the possible approaches toward mitigating oxygen loss and the associated electrochemical fade as well as detail novel analytical methods for probing the oxygen loss.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High Energy Density Aqueous Flow Battery Utilizing Extremely Stable, Branching-Induced High-Solubility Anthraquinone near Neutral pH

An anthraquinone featuring a chiral carboxylate-capped methyl-branched side chain with an ether linkage, 2,2'-((9,10-dioxo-9,10-dihydroanthracene-2,6-diyl)bis(oxy))dipropionic acid (2,6-D2PEAQ), was synthesized and evaluated for use in aqueous redox flow batteries. It was found to have an extraordinary solubility of 2 M (4 M electrons), corresponding to a theoretical volumetric capacity of 107.2 Ah/L for the negative electrolyte, which is 10 times that of its unbranched counterpart. The 2,6-D2PEAQ molecule demonstrated stability against thermal 2 decomposition and was extremely stable under cell cycling conditions. Here, a capacity fade rate of 0.02% day over 14 days was demonstrated in a 1.1 M 2,6-D2PEAQ nearly capacity-balanced cell when paired with a ferro-/ferricyanide posolyte at pH 7. Compared to other aqueous redoxactive organic molecules, its demonstrated fade rate is lower than that of any molecule with a demonstrated volumetric capacity of ≥55 Ah/L, and its volumetric capacity is greater than that of any molecule with a demonstrated fade rate of ≤0.5%/day.

25 ENERGY STORAGE↗
DOE OSTI2022

Formation of S0s in extreme environments Ⅲ: the role of environment in the formation pathways

It is well established that there are at least two main channels to form lenticular (or S0) galaxies. The first, which we name ‘faded spiral’ scenario, includes quenching events that led to consumption or removal of gas from a spiral progenitor. The second, which we call ‘merger’ scenario, includes merger-like events and interactions between galaxies. Each scenario leaves characteristic signatures in the newly formed lenticular galaxy. However, the conditions that trigger one mechanism over another are still unknown. This paper is the third of a series aimed at understanding the role of the environment in the formation of lenticular galaxies. In this study, we combine the kinematics, morphology, and properties of the stellar populations of 329 S0s from the SAMI and MaNGA surveys in order to highlight the role of the environment in the process. We divide the S0s into two classes (A and B) according to their global properties, that we can associate to the products of a faded spiral scenario (class A) or a merger scenario (class B). Here we then study how the various classes are distributed within different environments. Our study reveals that the ‘faded spiral’ pathway is the most efficient channel to produce S0s, and it becomes more efficient as the mass of the group or cluster or local density of galaxies increase. The merger pathway is also a viable channel, and its efficiency becomes higher with decreasing local density or environment mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Investigation of Active Life Balancing to Recondition Li-ion Battery Packs for 2nd Life

An investigation is presented into the application of active life balancing battery management systems to recondition inhomogeneous Li-ion battery packs and achieve homogeneity in capacity for second life. This paper proposes a life balancing objective map, which controls the state of charge references for each cell in a battery pack based on its capacity relative to other cells. The impacts of life balancing objective maps on the reconditioning time and overall pack capacity fade are considered. Moreover, the proposed approach accounts for various load and environmental effects, including depth-of-discharge, battery pack temperature, number of cycles per day, and cells’ resting time at various states of charge. The study results in a battery pack with convergent capacities achieved in minimal time, while curtailing overall capacity fade. Simulation results for a battery pack with sixteen series connected 75 Ah Kokam NMC cells with 3.6% initial capacity imbalance are presented, indicating a reconditioning time of 1.34 months with a final capacity imbalance of 0.1% and an overall capacity fade of 0.005%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Are Capacity and Energy Loss Equivalent Metrics for Battery Aging Reporting?

Battery aging in research publications and manufacturer specification sheets for individual cells is commonly reported as capacity (Ah) versus cycle number. However, the key measured quantity in battery-powered devices is energy (Wh), which is derived from integrating capacity with voltage. In this work, we compare the rate of capacity and energy loss across a wide range of Li-ion single-cell cycling studies with different positive electrode chemistries, charge–discharge rates, and temperatures. We find that the relative rate of discharge energy loss varies with cycling conditions. For many cells cycled under moderate conditions, the rate of discharge energy fade is only slightly faster than the rate of discharge capacity fade. However, some cells demonstrated up to a 15% decline in cycle count when 80% energy retention rather than 80% capacity retention was used as the end-of-life metric. These results highlight the importance of reporting cell aging based on energy fade to avoid overestimating battery lifetime in full systems.

batteries↗
DOE OSTI2021

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗
DOE OSTI2021

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗
DOE OSTI2024

Leveraging Temperature-Dependent (Electro)Chemical Kinetics for High-Throughput Flow Battery Characterization

The library of redox-active organics that are potential candidates for electrochemical energy storage in flow batteries is exceedingly vast, necessitating high-throughput characterization of molecular lifetimes. Demonstrated extremely stable chemistries require accurate yet rapid cell cycling tests, a demand often frustrated by time-denominated capacity fade mechanisms. We have developed a high-throughput setup for elevated temperature cycling of redox flow batteries, providing a new dimension in characterization parameter space to explore. We utilize it to evaluate capacity fade rates of aqueous redox-active organic molecules, as functions of temperature. We demonstrate Arrhenius-like behavior in the temporal capacity fade rates of multiple flow battery electrolytes, permitting extrapolation to lower operating temperatures. Collectively, these results highlight the importance of accelerated decomposition protocols to expedite the screening process of candidate molecules for long lifetime flow batteries.

25 ENERGY STORAGE↗