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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 433 records · Page 24
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DOE OSTI2022

Novel Application of Machine Learning Techniques for Rapid Source Apportionment of Aerosol Mass Spectrometer Datasets

In this work, we apply machine learning approaches sparse multinomial logistic regression to classify aerosol mass spectrometer (AMS) unit mass resolution (UMR) data followed by an ensemble regression technique for source apportionment of organic aerosols (OA). The classifier was trained on 60 well characterized laboratory and positive matrix factorization (PMF) deconvolved reference spectra to identify eight OA types. These include four laboratory-derived secondary organic aerosol (SOA) spectra, which include isoprene photooxidation SOA, isoprene epoxydiols (IEPOX) SOA, a monoterpene SOA type that includes a-pinene and ß-pinene SOA, and aromatic SOA from oxidation of naphthalene and m-xylene precursors, as well as PMF deconvolved spectra for three primary organic aerosol (POA) types, namely, hydrocarbon-like organic aerosol (HOA), biomass burning organic aerosol (BBOA), and cooking OA (COA), and a more oxidized oxygenated OA type (MO-OOA). A 5-fold cross-validation strategy, repeated 10 times, was used to assess the classifier’s performance. The classifier had high classification accuracy for COA, aromatic SOA, and isoprene SOA spectra but incorrectly classified ~9% by number of MO-OOA spectra as BBOA, 12% of BBOA spectra as HOA (and vice versa), and 18% of IEPOX-SOA spectra as aromatic SOA. Next, an ensemble regression model was trained on an artificially generated dataset consisting of mixtures of different OA types to assess its ability to predict fractional mass abundances from classification probabilities of various OA species obtained from the multinomial logistic regression classifier trained on the reference spectra. Ultimately, the proposed approach was applied for source apportionment of aircraft-based AMS measurements of OA UMR spectra during the HI-SCALE field campaign. On two representative days (May 6th and 18th, 2016), the algorithm determined that ~50-60% of OA by mass was MO-OOA, which represented a highly aged organic aerosol mixture from different sources. On both days, BBOA was determined to contribute less than 10% to OA by mass. However, on May 18th, the aromatic SOA fraction was higher compared to that on May 6th. The proposed approach is capable of rapidly analyzing AMS data in real time, making it suitable for applications where rapid source apportionment of AMS OA spectra is desirable.

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

Observational Constraints on Warm Cloud Microphysical Processes Using Machine Learning and Optimization Techniques

We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine‐learning and optimization techniques and are constrained by in situ cloud probe measurements from the recent Atmospheric Radiation Measurement Program field campaign at Azores. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively, outperforming existing parameterizations. Our results confirm that cloud and drizzle water content are the most important factors for determining accretion rates. However, for autoconversion, in addition to cloud water content and droplet number concentration, we discovered a key role of drizzle number concentration that is missing in current parameterizations. The robust relation between autoconversion rate and drizzle number concentration is surprising but real, and furthermore supported by theory. Thus, drizzle number concentration should be considered in parameterizations for improved representation of the autoconversion process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

4D imaging of lithium-batteries using correlative neutron and X-ray tomography with a virtual unrolling technique

The temporally and spatially resolved tracking of lithium intercalation and electrode degradation processes are crucial for detecting and understanding performance losses during the operation of lithium-batteries. Here, high-throughput X-ray computed tomography has enabled the identification of mechanical degradation processes in a commercial Li/MnO 2 primary battery and the indirect tracking of lithium diffusion; furthermore, complementary neutron computed tomography has identified the direct lithium diffusion process and the electrode wetting by the electrolyte. Virtual electrode unrolling techniques provide a deeper view inside the electrode layers and are used to detect minor fluctuations which are difficult to observe using conventional three dimensional rendering tools. Moreover, the 'unrolling' provides a platform for correlating multi-modal image data which is expected to find wider application in battery science and engineering to study diverse effects e.g. electrode degradation or lithium diffusion blocking during battery cycling.

25 ENERGY STORAGE↗
DOE OSTI2023

Understanding capacity fade in organic redox-flow batteries by combining spectroscopy with statistical inference techniques

Organic redox-active molecules are attractive as redox-flow battery (RFB) reactants because of their low anticipated costs and widely tunable properties. Unfortunately, many lab-scale flow cells experience rapid material degradation (from chemical and electrochemical decay mechanisms) and capacity fade during cycling (>0.1%/day) hindering their commercial deployment. In this work, we combine ultraviolet-visible spectrophotometry and statistical inference techniques to elucidate the Michael attack decay mechanism for 4,5-dihydroxy-1,3-benzenedisulfonic acid (BQDS), a once-promising positive electrolyte reactant for aqueous organic redox-flow batteries. We use Bayesian inference and multivariate curve resolution on the spectroscopic data to derive uncertainty-quantified reaction orders and rates for Michael attack, estimate the spectra of intermediate species and establish a quantitative connection between molecular decay and capacity fade. Our work illustrates the promise of using statistical inference to elucidate chemical and electrochemical mechanisms of capacity fade in organic redox-flow battery together with uncertainty quantification, in flow cell-based electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Direct identification of Ac and No molecules with an atom-at-a-time technique

The periodic table provides an intuitive framework for understanding chemical properties. However, its traditional patterns may break down for the heaviest elements occupying the bottom of the chart. Here, the large nuclei of actinides (Z > 88) and superheavy elements (Z ≥ 104) give rise to relativistic effects that are expected to substantially alter their chemical behaviours, potentially indicating that we have reached the end of a predictive periodic table. Relativistic effects have already been cited for the unusual chemistry of the actinides compared with those of their lanthanide counterparts. Unfortunately, it is difficult to understand the full impact of relativistic effects, as research on the later actinides and superheavy elements is scarce. Beyond fermium (Z = 100), elements need to be produced and studied one atom at a time, using accelerated ion beams and state-of-the-art experimental approaches. So far, no experiments have been capable of directly identifying produced molecular species. Here ions of actinium (Ac, Z = 89) and nobelium (No, Z = 102) were synthesized through nuclear reactions at the 88-Inch Cyclotron facility at Lawrence Berkeley National Laboratory and then exposed to trace amounts of H 2 O and N 2 . The produced molecular species were directly identified by measuring their mass-to-charge ratios using FIONA (For the Identification Of Nuclide A). These results mark the first, to our knowledge, direct identification of heavy-element molecular species using an atom-at-a-time technique and highlight the importance of such identifications in future superheavy-element chemistry experiments to deepen understanding of their chemical properties.

Pore, Jennifer L. [Lawrence Berkeley National Labo↗
DOE OSTI2025

An open retail boundary dataset for South Korea using open data and computer vision technique

Although delineating retail boundaries is important to explore and comprehend the dynamics of the retail sector, it is hard to find studies specifically addressing it in the South Korean context. This study fills this gap by proposing new retail boundaries across South Korea. To achieve this goal, we employed a variety of retailers and building datasets and proposed a unique computer vision-based framework with a deep ensemble voting technique. As a result, we delineated 6,636 distinct retail boundaries that were validated against existing reference retail boundaries. These newly delineated retail boundaries provide valuable insights for researchers, governments, and other relevant stakeholders by enhancing their understanding of retail geography. This dataset can be used as a foundational resource for analyses on topics such as pandemic recovery, retail gentrification, and the resilience of retail spaces in response to e-commerce growth, ultimately contributing to more robust retail sector research in South Korea.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimizing performance and yield of vertical GaN diodes using wafer scale optical techniques

Abstract To improve the manufacturing of vertical GaN devices for power electronics applications, the effects of defects in GaN substrates need to be better understood. Many non-destructive techniques including photoluminescence, Raman spectroscopy and optical profilometry, can be used to detect defects in the substrate and epitaxial layers. Raman spectroscopy was used to identify points of high crystal stress and non-uniform conductivity in a substrate, while optical profilometry was used to identify bumps and pits in a substrate which could cause catastrophic device failures. The effect of the defects was studied using vertical P-i-N diodes with a single zone junction termination extention (JTE) edge termination and isolation, which were formed via nitrogen implantation. Diodes were fabricated on and off of sample abnormalities to study their effects. From electrical measurements, it was discovered that the devices could consistently block voltages over 1000 V (near the theoretical value of the epitaxial layer design), and the forward bias behavior could consistently produce on-resistance below 2 mΩ cm 2 , which is an excellent value considering DC biasing was used and no substrate thinning was performed. It was found that high crystal stress increased the probability of device failure from 6 to 20%, while an inhomogeneous carrier concentration had little effect on reverse bias behavior, and slightly (~ 3%) increased the on-resistance (R on ). Optical profilometry was able to detect regions of high surface roughness, bumps, and pits; in which, the majority of the defects detected were benign. However a large bump in the termination region of the JTE or a deep pit can induce a low voltage catastrophic failure, and increased crystal stress detected by the Raman correlated to the optical profilometry with associated surface topography.

42 ENGINEERING↗
DOE OSTI2021

A multi-technique approach to understanding delithiation damage in LiCoO2 thin films

Abstract We report on the delithiation of LiCoO 2 thin films using oxalic acid (C 2 H 2 O 4 ) with the goal of understanding the structural degradation of an insertion oxide associated with Li chemical extraction. Using a multi-technique approach that includes synchrotron radiation X-ray diffraction, scanning electron microscopy, micro Raman spectroscopy, photoelectron spectroscopy and conductive atomic force microscopy we reveal the balance between selective Li extraction and structural damage. We identify three different delithiation regimes, related to surface processes, bulk delithiation and damage generation. We find that only a fraction of the grains is affected by the delithiation process, which may create local inhomogeneities. However, the bulk delithiation regime is effective to delithiate the LCO film. All experimental evidence collected indicates that the delithiation process in this regime mimics the behavior of LCO upon electrochemical delithiation. We discard the formation of Co oxalate during the chemical extraction process. In conclusion, the chemical route to Li extraction provides additional opportunities to investigate delithiation while avoiding the complications associated with electrolyte breakdown and simplifying in-situ measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electron beam surface remelting enhanced corrosion resistance of additively manufactured Ti-6Al-4V as a potential in-situ re-finishing technique

This study explores the effect of surface re-finishing on the corrosion behavior of electron beam manufactured (EBM) Ti-G5 (Ti-6Al-4V), including the novel application of an electron beam surface remelting (EBSR) technique. Specifically, the relationship between material surface roughness and corrosion resistance was examined. Surface roughness was tested in the as-printed (AP), mechanically polished (MP), and EBSR states and compared to wrought (WR) counterparts. Electrochemical measurements were performed in chloride-containing media. It was observed that surface roughness, rather than differences in the underlying microstructure, played a more significant role in the general corrosion resistance in the environment explored here. While both MP and EBSR methods reduced surface roughness and enhanced corrosion resistance, mechanical polishing has many known limitations. The EBSR process explored herein demonstrated positive preliminary results. The surface roughness (R a ) of the EBM-AP material was considerably reduced by 82%. Additionally, the measured corrosion current density in 0.6 M NaCl for the EBSR sample is 0.05 µA cm –2 , five times less than the value obtained for the EBM-AP specimen (0.26 µA cm –2 ).

42 ENGINEERING↗
DOE OSTI2020

Li-rich cathodes for rechargeable Li-based batteries: reaction mechanisms and advanced characterization techniques

Due to their high specific capacities beyond 250 mA h g -1 , lithium-rich oxides have been considered as promising cathodes for the next generation power batteries, bridging the capacity gap between traditional layered-oxide based lithium-ion batteries and future lithium metal batteries such as lithium sulfur and lithium air batteries. However, the practical application of Li-rich oxides has been hindered by formidable challenges. To address these challenges, the understanding of their electrochemical behaviors becomes critical and is expected to offer effective guidance for both materials and cell development. This work aims to provide fundamental insights into the reaction mechanisms, electrochemical challenges and modification strategies of lithium-rich oxides. We first summarize the research history, the pristine structures, and the classification of lithium-rich oxides. Then we review the critical reaction mechanisms that are closely related to their electrochemical features and performances, such as lattice oxygen oxidation, oxygen vacancy formation, transition-metal migration, layered to spinel transitions, ‘two-phase mechanism’, and lattice evolution. These discussions are coupled with state-of-the-art characterization techniques. As a comparison, the anionic redox reactions of layered sodium transition metal oxides are also discussed. Finally, after a brief overview of the correlation among the aforementioned mechanisms, we provide perspectives on the rational design of lithium-rich oxides with high energy densities and long-term cycling stability.

25 ENERGY STORAGE↗
DOE OSTI2021

(S)TEM-EELS as an advanced characterization technique for lithium-ion batteries

Although the lithium-ion battery (LIB) has acquired commercial success as a sustainable power source, it still suffers from multiple challenges for the future applications. In order to further develop next-generation batteries, the dynamics of structure change, charge transfer, and ion diffusion occurring inside the battery need to be deeply understood by advanced characterization techniques. (Scanning) transmission electron microscopy-electron energy loss spectroscopy ((S)TEM-EELS) is an effective method for the nano-scale detection of structural and chemical information in materials. Herein, this review systematically introduces the advantages and fundamentals of (S)TEM-EELS and its unique applications in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Dynamics of fluorinated imide-based ionic liquids using nuclear magnetic resonance techniques

There is increasing interest in studying molecular motions in ionic liquids to gain better insights into their transport properties and to expand their applications. Here, in this study, we have employed the fast field cycling relaxometry and pulsed field gradient nuclear magnetic resonance techniques to investigate the rotational and translational dynamics of fluorinated imide-based ionic liquids (ILs) at different temperatures. We have studied a total of six ILs composed of the 1-butyl-3-methylimidazolium cation ([BMIM] + ) combined with chemically modified analogs of the bis((trifluoromethyl)sulfonyl)imide anion ([NTf 2 ] − or [TFSI] − ). The primary objective of this paper is to broaden the understanding of how the anion's conformational flexibility, fluorination, and mass affect the molecular dynamics of cations and anions. Our results indicate that flexibility has the most significant impact on the rotational and translational motions of ions. Meanwhile, the effect of fluorination and mass is only relevant when conformational flexibility does not change significantly between the ILs being compared.

25 ENERGY STORAGE↗
DOE OSTI2020

Real-time power management technique for microgrid with flexible boundaries

In order to diminish the impacts brought by high penetration of renewable energy on the reliability of distribution systems, some distribution networks (e.g. Chattanooga electric power board system) have deployed smart switches (SSs) to island some areas to mitigate outage losses. However, due to intermittency and sharply changing rate of renewable energy, it is likely to experience insufficient or excessive power for islanded areas. Therefore, a microgrid controller featured with flexible boundaries is proposed. With proposed microgrid controller, the microgrid can not only shrink or expand its boundaries according to current renewable energy supply, but also disconnect/connect to the main grid with a designated SS. Furthermore, to ensure the microgrid controller could obtain suitable boundaries on the time scale of seconds, a real-time power management technique with alternative generating algorithm is designed to generate all possible alternative boundaries and choose the optimal one, which is scalable to any topology. In addition, in order to maintain state of charge of batteries within a desirable range, anti-overcharge/discharge strategies are designed. Four comprehensive experiments verify that the implementation of the microgrid controllers can realise flexible boundaries and deal with sharply changing rate of renewable generation or load on the time scale of seconds.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Barium stars as tracers of s -process nucleosynthesis in AGB stars: II. Using machine learning techniques on 169 stars

Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process (s-process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the FRUITY and Monash stellar models. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s-process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = –0.21 and –0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Closure to “Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains”

Here, this paper presents a closure to “Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains” by Hongxiang Yan, Zhuoran Duan, Mark S. Wigmosta, Ning Sun, Ethan D. Gutmann, Bert Kruyt, and Jeffrey R. Arnold. https://doi.org/10.1061/JHYEFF .HEENG-6147.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Microstructural investigation of PBX 9501: Comparing wet slurry and resonant acoustic mixing techniques

The microstructure of a high explosive (HE) material directly influences the reactive behavior under a variety of insults. Furthermore, the preparation method of polymer-bonded explosives (PBX), as well as the constituent material particle size distribution and consolidation parameters, will dominate the microstructural features that are observed. Here, we compare batches of PBX 9501 prepared by the typical wet slurry process and those prepared by resonant acoustic mixing. The “prills” produced by the wet slurry process leads to an inherently different microstructure than the coated powder produced by resonant acoustic mixing. Additionally, we observed that the conditions required to consolidate (press) the material to the nominal PBX 9501 density varied depending on the preparation technique, which also dictates the observed binder distribution. Furthermore, X-ray microcomputed tomography and ultra-small-angle X-ray scattering analyses revealed distinct differences in the void structure and distribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

3ω techniques for measurement of volumetric heat capacity and anisotropic thermal conductivity of a solution processable, hybrid organic/inorganic film, Te-PEDOT:PSS

We report that measuring the thermal properties of anisotropic films of hybrid materials poses a challenge to existing metrology techniques. We have developed a new approach for measuring the volumetric heat capacity and anisotropic thermal conductivity of these systems using the 3ω method. While there exist many avenues for measuring the thermal properties of thin films, most carry with them difficult requirements such as smooth surfaces or advanced lithography. Here, we present measurements of a film's in-plane and cross-plane conductance and its volumetric heat capacity using relatively simple sample configurations, each requiring a single heater. For the measurement of volumetric heat capacity, we present a new model fitting method, relying on a standard film-on-substrate configuration. For the measurement of in-plane thermal conductance by 3ω, we have developed the use of an embedded micro-wire heater in suspended drop cast films, allowing for a 12 μm wide heater without the need for advanced lithography. We also expose the surprisingly significant effect of thermal radiation in the suspended film measurement and its associated error. Our measurements reveal a large anisotropy in the thermal conductivity of our test material, Te-PEDOT:PSS, of k in-plane / k cross-plane = 19, consistent with the nanoscale morphology of the material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Direct current magnetic Hall probe technique for measurement of field penetration in thin film superconductors for superconducting radio frequency resonators

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently, high purity niobium is the material of choice for SRF cavities that have been optimized to operate near their theoretical field limits. This brings about the need for significant R & D efforts to develop next generation superconducting materials that could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under a high RF magnetic field without penetration of quantized magnetic vortices through the cavity wall. Therefore, the magnetic field at which vortices penetrate a superconductor is one of the key parameters of merit of SRF cavities. Techniques to measure the onset of magnetic field penetration on thin film samples need to be developed to mitigate the issues with the conventional magnetometry measurements that are strongly influenced by the film orientation and shape and edge effects. In this work, we report the development of an experimental setup to measure the field of full flux penetration through films and multi-layered superconductors. Our system combines a small superconducting solenoid that can generate a magnetic field of up to 500 mT at the sample surface and three Hall probes to detect the full flux penetration through the superconductor. We report this setup can be used to study alternative materials that could potentially outperform niobium, as well as superconductor–insulator–superconductor (SIS) multilayer coatings on niobium.

47 OTHER INSTRUMENTATION↗