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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Acceptor dopant mediated electrical property modification in Bi0.5Na0.5TiO3-based piezoceramic

The effect of Mn and Fe dopants on the electromechanical and electrochemical properties of 0.88[Bi 0.5 Na 0.5 ]TiO 3 –0.08[Bi 0.5 K 0.5 ]TiO 3 –0.04[Bi 0.5 Li 0.5 ]TiO 3 piezoceramic is investigated with particular emphasis on complex impedance in the temperature range from 450 to 600 °C. The impedance spectra have been simulated with equivalent circuits in order to extract bulk and grain boundary characteristics and to determine activation energies of conduction. Mn and Fe dopants considerably enhance the mechanical quality factor and decrease the dielectric loss compared to the undoped composition. Mn doping leads to dramatically higher resistivity in the bulk and a modest increase in the bulk activation energy. On the other hand, conductivity increases dramatically via Fe doping with a significant lowering of activation energy in the bulk and corresponding raising of the activation energy at grain boundaries in comparison to Mn-doped and undoped ceramic. The bulk conductivity of Fe-doped piezoceramic reaches as high as 0.01 S cm -1 at 600 °C.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Solar Wind Fluctuations and Their Consequences on the Magnetosphere

Efforts have been made to extract the physical meaning of each term in our prediction model of the Dst index using the solar wind as the only input. The work has been published Journal of Geophysical Research (Temerin and Li, 21002). We found different terms in the model representing different current in the magnetospheric system and each current has different rise and decay times, with the symmetric ring current the slowest, then the partial ring current, then the tail current. We also have been trying to understand the physical meaning of the diffusion coefficient used in our prediction model of relativistic electron fluxes at geostationary orbit. The model reproduced the observations of MeV electron flux variations well, the diffusion coefficient had be assumed only die to local magnetic field fluctuations, leading to its 10th power dependence on the L. We have studied the theoretical derivation of the diffusion coefficient and we believe that the effect electric field fluctuations at smaller L could become more significant. We have expanded our previous radiation belt electron prediction model, which predicted MeV electron geosynchronous orbit based on solar wind measurements, to predict MeV electrons inside geosynchronous orbit. The model results are compared with measurements from Polar/CEPPAD. Prediction efficiencies of 0.56 and 0.54, respectively, at L=6 and L=4, have been achieved over the entire year of 1998. This work wa reported at 2003 Fall AGU and has been accepted for publication in Space Weather (Barker et al., 2005). We also have used simultaneous measurements of the upstream solar wind and of energetic electrons at geosynchronous orbit to analyze the response of electrons over a very wide energy range, 50 keV-6MeV, to solar wind variations. Enhancements of energetic electron fluxes over this whole energy range are modulated by the solar wind speed and the polarity of the interplanetary magnetic field (IMF). The solar wind speed seems to be a dominant controlling parameter for electrons of all energy. This work has been published in Space Weather (Li et al., 2005).

Li, Xin-Lin↗
DOE OSTI2021

Systematic and statistical uncertainties of the hilbert-transform based high-precision FID frequency extraction method

Pulsed nuclear magnetic resonance (NMR) is widely used in high-precision magnetic field measurements. The absolute value of the magnetic field is determined from the precession frequency of nuclear magnetic moments. The Hilbert transform is widely used to extract the phase function from the observed free induction decay (FID) signal and then its frequency. In this paper, a detailed implementation of a Hilbert-transform based FID frequency extraction method is described. How artifacts and noise level in the FID signal affect the extracted phase function are derived analytically. A method of mitigating the artifacts in the extracted phase function of an FID is discussed. Correlations between noises of the phase function samples are studied for different noise spectra. We discovered that the error covariance matrix for the extracted phase function is nearly singular and improper for constructing the $\chi^2$ used in the fitting routine. A down-sampling method for fixing the singular covariance matrix has been developed, so that the minimum $\chi^2$-fit yields properly the statistical uncertainty of the extracted frequency. Other practical methods of obtaining the statistical uncertainty are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

An LSTM Deep Learning Network for ¿Background Radiation Prediction

Determination of appropriate background radiation is important in any measurement application. Environmental radiation monitors and monitors used to assess dose to individuals outside of controlled areas are particularly susceptible to changes in readings due to fluctuations in the environmental conditions. These fluctuations (e.g. radon progeny concentrations) lead to changes in the detector response in the actual radiation environment, and they need to be taken into account when extracting the net operational doses. Work has been ongoing to apply advances in Deep Learning and Artificial Intelligence to account for changes in detector responses based on environmental parameters; in particular, a Long-Short Term Memory (LSTM) Deep Learning architecture has been utilized to incorporate time-series data into a prediction model. In this work, we present the current status of the project to predict radiation measurements based on meteorological conditions and air packet trajectories extracted using the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) model.

Degtiarenko, Pavel↗
DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Asymmetric Reaction Pathways of Conversion-Type Electrodes for Lithium-Ion Batteries

Metal oxides have been actively explored as promising conversion-type electrode materials for lithium ion batteries due to high deliverable capacity but still notorious for poor cyclability, capacity fading, voltage hysteresis, etc. Yet, the fundamental reason for the undesirable properties of metal oxides behind the repetitive conversion process is still obscure. In this work, we take advantage of synchrotron X-ray techniques as well as transmission electron microscopy to monitor the structural changes during both conversion (lithiation) and reconversion (delithiation) reactions. Difference in diffusion rates of lithium and metal plays a decisive role in determining the reaction pathway. We find lithium accommodation and extraction occur via different reaction routes: lithiation follows a kinetically driven way while delithiation adopts a route close to the thermodynamic ground state path. Thermodynamic structural evolution features the formation of an intermediate phase of Li-Metal (M)-O, suggesting lithium removal accompanies with the Li/M ionic exchange and rearrangement of oxygen framework. The slow diffusion of metal ions and the high kinetic and energy barrier for dissociating the intermediate phase are mainly responsible for uncompleted reconversion reaction, evidenced by remaining Li-M-O phase at the end of charge. Imperfect reconversion reaction eventually limits the utilization of lithium ions over the repeated cycling. Furthermore, this work sheds light on structural changes occurring at metal oxides during both conversion and reconversion processes, which is strongly linked with the performances of conversion-type materials in applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Systematic uncertainty of off-shell corrections and higher-twist contribution in DIS at large x

We study the systematic uncertainty and biases introduced by theoretical assumptions needed to include large-x DIS data in a global QCD analysis. Working in the CTEQ-JLab framework, we focus on different implementations of higher-twist corrections to the nucleon structure functions and of offshell PDF deformations in deuteron targets and discuss how their interplay impacts the extraction of the d -quark PDF and the calculation of the neutron structure function at large x.

Cerutti, Matteo↗
NASA NTRS2012

Engagement Assessment Using EEG Signals

In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance.

Li, Feng↗
DOE OSTI2020

Actinide Separation Inspired by Self-Assembled Metal–Polyphenolic Nanocages

The separation of actinides has a vital place in nuclear fuel reprocessing, recovery of radionuclides, and remediation of environmental contamination. Here we propose a new paradigm of nanocluster-based actinide separation, namely, nanoextraction, that can achieve efficient sequestration of uranium in an unprecedented form of giant coordination nanocages using a cone-shaped macrocyclic pyrogallol[4]arene as the extractant. The U 24 -based hexameric pyrogallol[4]arene nanocages with distinctive [U 2 (PG) 2 ] binuclear units (PG = pyrogallol) that rapidly assembled in situ in monophasic solvent were identified by single-crystal X-ray diffraction, MALDI-TOF mass spectrometry, NMR spectroscopy, and small-angle X-ray and neutron scattering. Furthermore, comprehensive biphasic extraction studies showed that this novel separation strategy has enticing advantages such as fast kinetics, high efficiency, and good selectivity over lanthanides, thereby demonstrating its potential for efficient separation of actinide ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Advanced Characterization to Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks

Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic source of CM is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). CM recovery from these waste feedstocks is promising due to their abundances and fast availability as waste products. On the other hand, the CM occurrence in these wastes is in small quantities compared to traditional ore bodies. Thus, novel and strategic separation and extraction processes are under exploration. Researchers at DOE’s National Energy Technology Laboratory (NETL) are collecting and analyzing CM data for aforementioned fossil energy wastes, and utilizing advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to understand the CM speciation and binding environments in these materials to better inform sustainable and effective recovery. Successful examples discussed in this talk include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.

characterization and extraction↗
DOE OSTI2024

Characterization Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks

Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Ni, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic CM source is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). While they can contain lower CM concentrations then traditional ore, the quantity and fast availability as waste feedstock makes them a promising CM resource. To explore their promise, researchers at DOE’s National Energy Technology Laboratory (NETL) have collected and analyzed CM data for aforementioned fossil energy wastes, and utilized advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to identify the CM speciation and binding environments, and developed sustainable and targeted CM recovery. Successful examples include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.

Stuckman, Mengling↗
DOE OSTI2020

Probing Mg Intercalation in the Tetragonal Tungsten Bronze Framework V 4 Nb 18 O 55

While commercial Li-ion batteries offer the highest energy densities of current rechargeable battery technologies, their energy storage limit has almost been achieved. Therefore, there is considerable interest in Mg batteries, which could offer increased energy densities in comparison to Li-ion batteries if a high-voltage electrode material, such as a transition-metal oxide, can be developed. However, there are currently very few oxide materials which have demonstrated reversible and efficient Mg 2+ insertion and extraction at high voltages; this is thought to be due to poor Mg 2+ diffusion kinetics within the oxide structural framework. Here, in this paper, the authors provide conclusive evidence of electrochemical insertion of Mg 2+ into the tetragonal tungsten bronze V 4 Nb 18 O 55 , with a maximum reversible electrochemical capacity of 75 mA h g –1 , which corresponds to a magnesiated composition of Mg 4 V 4 Nb 18 O 55 . Experimental electrochemical magnesiation/demagnesiation revealed a large voltage hysteresis with charge/discharge (1.12 V vs Mg/Mg 2+ ); when magnesiation is limited to a composition of Mg 2 V 4 Nb 18 O 55 , this hysteresis can be reduced to only 0.5 V. Hybrid-exchange density functional theory (DFT) calculations suggest that a limited number of Mg sites are accessible via low-energy diffusion pathways, but that larger kinetic barriers need to be overcome to access the entire structure. The reversible Mg 2+ intercalation involved concurrent V and Nb redox activity and changes in crystal structure, as confirmed by an array of complementary methods, including powder X-ray diffraction, X-ray absorption spectroscopy, and energy-dispersive X-ray spectroscopy. Consequently, it can be concluded that the tetragonal tungsten bronzes show promise as intercalation electrode materials for Mg batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A contextual sensor system for non-intrusive machine status and energy monitoring

Event-driven contexts in manufacturing occur pervasively as a result of interactions among involved entities such as machines, workers, materials, and environment. One of the primary tasks in smart manufacturing is to derive a context-aware system conveniently incorporating worker knowledge for generating timely actionable intelligence for workers on factory floor and supervisors to respond. In this paper, we propose to design a human-and-machine interaction recognition framework by using a causality concept to collect contextual data for classifications of normal and abnormal machine operations. The causes and effects are between workers and machines for this initial research. To apply the causality to recognize worker interactions, initially a reliable way to identify the states of machines is necessary. The proposed contextual sensor system, consisting of a power meter for measuring machine operation conditions, a visual camera for capturing worker and machine interactions via a finite state machine model, and an algorithm for determining power signatures of individual components via energy disaggregation is implemented on semiconductor fabrication machines (manual or PLC controlled) each with multiple components. The experiment results demonstrate its context extraction capability such as components states and their corresponding energy usage in real time as well as its ability to identify anomalous operation conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Relativistic spin dynamics for vector mesons

We propose a relativistic theory for spin density matrices of vector mesons based on Kadanoff-Baym equations in the closed-time-path formalism. The theory puts the calculation of spin observables such as the spin density matrix element ρ 00 for vector mesons on a solid ground. Within the theory we formulate ρ 00 for ϕ mesons into a factorization form in separation of momentum and spacetime variables. We argue that the main contribution to ρ 00 at lower energies should be from the ϕ fields that can polarize the strange quark and antiquark in the same way as electromagnetic fields. The key observation is that there is correlation inside the ϕ meson wave function between the ϕ field that polarizes the strange quark and that polarizes the strange antiquark. This is reflected by the fact that the contributions to ρ 00 are all in squares of fields that are nonvanishing even if the fields may strongly fluctuate in spacetime. The fluctuation of strong force fields can be extracted from ρ 00 of unflavored vector mesons as links to fundamental properties of quantum chromodynamics. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗