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

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

DCE-MRI defined subvolumes of a brain metastatic lesion by principle component analysis and fuzzy-c-means clustering for response assessment of radiation therapy

Purpose: To develop a pharmacokinetic modelfree framework to analyze the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data for assessment of response of brain metastases to radiation therapy. Methods: Twenty patients with 45 analyzable brain metastases had MRI scans prior to whole brain radiation therapy (WBRT) and at the end of the 2-week therapy. The volumetric DCE images covering the whole brain were acquired on a 3T scanner with approximately 5 s temporal resolution and a total scan time of about 3 min. DCE curves from all voxels of the 45 brain metastases were normalized and then temporally aligned. A DCE matrix that is constructed from the aligned DCE curves of all voxels of the 45 lesions obtained prior to WBRT is processed by principal component analysis to generate the principal components (PCs). Then, the projection coefficient maps prior to and at the end of WBRT are created for each lesion. Next, a pattern recognition technique, based upon fuzzy-c-means clustering, is used to delineate the tumor subvolumes relating to the value of the significant projection coefficients. The relationship between changes in different tumor subvolumes and treatment response was evaluated to differentiate responsive from stable and progressive tumors. Performance of the PC-defined tumor subvolume was also evaluated by receiver operating characteristic (ROC) analysis in prediction of nonresponsive lesions and compared with physiological-defined tumor subvolumes. Results: The projection coefficient maps of the first three PCs contain almost all response-related information in DCE curves of brain metastases. The first projection coefficient, related to the area under DCE curves, is the major component to determine response while the third one has a complimentary role. In ROC analysis, the area under curve of 0.88 ± 0.05 and 0.86 ± 0.06 were achieved for the PC-defined and physiological-defined tumor subvolume in response assessment. Conclusions: The PC-defined subvolume of a brain metastasis could predict tumor response to therapy similar to the physiological-defined one, while the former is determined more rapidly for clinical decision-making support.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Nanoscale Magnetic Ordering Dynamics in a High Curie Temperature Ferromagnet

Thermally driven transitions between ferromagnetic and paramagnetic phases are characterized by critical behavior with divergent susceptibilities, long-range correlations, and spin dynamics that can span kHz to GHz scales as the material approaches the critical temperature T c , but it has proven technically challenging to probe the relevant length and time scales with most conventional measurement techniques. In this study, we employ scanning nitrogen-vacancy center based magnetometry and relaxometry to reveal the critical behavior of a high-T c ferromagnetic oxide near its Curie temperature. Cluster analysis of the measured temperature-dependent nanoscale magnetic textures points to a 3D universality class with a correlation length that diverges near T c . Meanwhile, the temperature-dependent spin dynamics, measured through all optical relaxometry suggest that the phase transition is in the XY universality class. In conclusion, our results capture both static and dynamic aspects of critical behavior, providing insights into universal properties that govern phase transitions in magnetic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Influence of dynamic factors on nonwetting fluid snap-off in pores

Snap-off is an important dynamic multiphase flow phenomenon which occurs in porous media. It plays a dominant role in the residual trapping and mobilization/immobilization of nonwetting fluids such as hydrocarbons or CO 2 . Current studies, applications, and threshold criteria of snap-off are mostly based on static or equilibrium conditions. Thus, the dynamics of snap-off which is relevant for many real world applications has rarely been systematically studied. While a static criterion indicates the snap-off potential for nonwetting fluids, the competition between the time required for snap-off and the local pore throat capillary number determines whether snap-off actually occurs. Using a theoretical model to couple the wetting film thickness to the local capillary number at the pore throat, we analyzed the dynamics of the wetting/nonwetting interface instability in sinusoidally constricted capillary tubes. The influence of dynamic factors as encapsulated by the effect of local capillary number on nonwetting fluid snap-off time were investigated for varying pore throat to pore body aspect ratio and pore body distances. Finally, the analysis showed that snap-off can be inhibited by a sufficiently large local capillary number even in cases where the static snap-off criterion has been met.

58 GEOSCIENCES↗
DOE OSTI2018

Bistability analysis in mathematical model of M-phase control in Xenopus oocyte extracts

To gain more insight into the molecular mechanism that regulates eukaryotic cell cycle, we propose a modification to an existing Mathematical model of mitosis-promoting factor control in Xenopus oocyte extract. To achieve this, we redirect how cell exits from mitosis using ubiquitin ligase enzyme APCP:Cdc20 which is acting as a modifier in cyclin degradation. We present a modified wiring map using combination of mass action kinetics and Michaelis–Menten kinetics to represent the biochemical processes. This results in a system of non-linear ordinary differential equations. The equilibria of the system were analyzed analytically. Using MPF as a bifurcation parameter, we analytically derived conditions under which bistability can occur in the MPF activation module. We find that for bistability to occur, it is necessary that the rate of phosphorylation of Wee1 must be greater than the rate of its dephosphorylation and that the concentration of MPF must lie in certain range of parameter values. Numerical simulations conducted show that the time taken to exit the cell cycle is shorter than those published in some reports and the sensitivity analysis results suggest that the rate of synthesis of cyclin is the most sensitive parameter in the dynamics of cell cycle. Through numerical experiments, we found new parameter sets that will give rise to bistability in the MPF activation module.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Anomalously high elastic modulus of a poly(ethylene oxide)-based composite electrolyte

The practical use of lithium metal anodes in solid-state batteries requires a polymer membrane with high lithium-ion conductivity, thermal/electrochemical stability, and mechanical strength. The primary challenge is to effectively decouple the ionic conductivity and mechanical strength of the polymer electrolytes. We report a remarkably facile single step synthetic strategy based on in-situ crosslinking of poly(ethylene oxide) (xPEO) in the presence of a woven glass fiber (GF). Such a simple method yields composite polymer electrolytes (CPE) of anomalously high elastic modulus up to 2.5 GPa over a broad temperature range (20 °C – 245 °C) that has never been previously documented. An unsupervised machine learning algorithm, K-mean clustering analysis, was implemented on the hyperspectral Raman mapping at the xPEO/GF interface. Using such a unique means, we show for the first time that the promoted mechanical strength originates from xPEO and GF interactions through dynamic hydrogen and ionic bonding. High ionic conductivity is achieved by the addition plasticizer (e.g. tetraglyme), where trifluoromethanesulfonate anions are tethered to the xPEO matrix and Li + cations are favorably transported through coordination with the plasticizer. Further, stringent galvanostatic cycling tests indicates the CPE can be stably cycled for >3000 h in a Li-metal symmetric cell at a moderate temperature (nearly 1500 Coulombs/cm 2 Li equivalents), outperforming most of the PEO-based electrolytes. The GF reinforced CPE reported here has multifunctional uses, such as solid electrolytes for all solid-state batteries and membranes for redox-flow batteries. Although the focus of this study is on lithium-based batteries, the results are equally promising for other alkali metal based batteries such as sodium and potassium.

25 ENERGY STORAGE↗
DOE OSTI2020

An iterative learning and inference approach to managing dynamic cyber-vulnerabilities of complex systems

As modern systems become increasingly reliant on cyber-technologies and continue to be integrated with physical systems, managing risks from deliberate and non-deliberate sources is a significant research challenge. Unlike strictly physical systems, cyber-enabled physical systems are influenced by dynamic and evolving technologies, environments, and attack mechanisms. As a result, vulnerabilities are rapidly changing and difficult to detect and manage. While there is recent interest in the dynamic properties of performance through resilience analysis, limited research addresses the dynamic nature of cyber-system vulnerability. This paper presents a dynamic iterative learning approach to evaluate the state of health for systems as related to cyber-vulnerabilities. These time-varying system health characteristics may not be visible, but can be inferred using observable characteristics. The approach recognizes that multiple types of vulnerabilities need to be included in a holistic system health assessment. The methods are applied to the Common Vulnerability Scoring System database containing over 100,000 documented cybersecurity vulnerabilities. This work is the first to acknowledge the dynamic properties of cyber-vulnerability, while also inferring system health using observable data and hidden states of system health. This work will be of interest to managers of large-scale cyber-enabled physical systems who are seeking to prioritize system health investments.

Chatterjee, Samrat↗
DOE OSTI2021

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer–particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental–theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Here, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Asymmetric charge separation and recombination in symmetrically functionalized σ–π hybrid oligosilanes

The flexibility of σ-conjugated silanes presents new opportunities for manipulating charge generation, transport, and non-linear optical properties of materials. Recently we synthesized a series of acceptor–donor–acceptor (ADA) compounds in which a methylated oligosilane core (D) is flanked by electron-deficient cyanovinyl-substituted arenes (A). Based on a detailed characterization of the photophysics of ADA and donor–acceptor (DA) architectures using both steady state and ultrafast spectroscopic measurements we illustrate that asymmetric charge separation occurs directly following light absorption. Lippert analysis of solvatochromic emission indicates large changes in dipole moments on excitation consistent with the formation of dipolar emissive states. Time resolved absorption measurements reveal common excited-state relaxation behavior across molecular structures: spectral dynamics associated with the relaxation of nascent excited states occur on a common timescale for all structures within the same solvent environment, whereas charge recombination via excited-state decay consistently follows a common energy gap law. Ultrafast time-resolved Raman measurements reveal that reduction of the cyanovinyl moieties is instantaneous with excitation, with only minor shifts in vibrational features over the course of excited-state relaxation. We conclude that excited-state symmetry breaking that gives rise to asymmetric intramolecular charge transfer (ICT) is associated with the conformation of the central Si chain. In contrast, ultrafast solvent reorganization or solvent-controlled intramolecular dynamics only serve to stabilize nascent dipolar excited states, rather than induce charge separation from an initial quadrupolar state.

Zhou, Jiawang↗
DOE OSTI2019

Building intermixed donor–acceptor architectures for water-processable organic photovoltaics

A modified synthesis method for aqueous nanoparticle printing inks, based upon vacuum-assisted solvent removal, is reported. Poly(3-hexylthiophene):phenyl C 61 butyric acid methyl ester nanoparticle inks were prepared via this modified miniemulsion method, leading to both an improvement in photoactive layer morphology and a substantial reduction in the ink fabrication time. A combination of UV-visible spectroscopy, photoluminescence spectroscopy and scanning transmission X-ray microscopy measurements revealed a nanoparticle morphology comprising highly intermixed donor–acceptor domains. Consistent with these measurements, dynamic mechanical thermal analysis of the nanoparticles showed a glass transition temperature (T g ) of 104 °C, rather than a pure polymer phase or pure fullerene phase T g . Together the spectroscopy, microscopy and thermomechanical data indicate that rapid solvent removal generates a more blended nanoparticle morphology. As such, this study highlights a new experimental lever for optimising nanostructure in the photoactive layer of nanoparticulate organic photovoltaic devices by enabling highly intermixed donor–acceptor architectures to be built from customised nanoparticulate inks.

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

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗
DOE OSTI2017

Predicting Total Dissolved Gas Travel Time in Hydropower Reservoirs

Large spills at hydropower facilities can produce environmentally unfavorable supersaturated total dissolved gas (TDG) conditions. Enhanced coordination between adjacent hydropower facilities is required when a large, brief spill creates a pulse of TDG that is transported into a downstream reservoir. A premium is placed on quick and simple methods and relationships that can support short-term decision making under dynamic conditions. This paper presents an empirically-based methodology to quantify and assess the relationship between mean hourly river flow and TDG travel time between an upstream hydropower spillway and a downstream dam. The analysis is conducted for reservoirs in the mid-Columbia River system and is limited to summer months when spill events that create high TDG are most common. A two-step filter and cross-correlation procedure is used to isolate high strength TDG events and characterize the time delay between when the TDG event is initiated upstream and when it is detected downstream. Spill flow, powerhouse flow, and TDG measurements are used to develop a bulk parameter estimation of mean TDG time delay as a function of mean river flow. The approach reveals an inverse power law relationship between mean river flow and mean TDG travel time. The relationship provides hydropower operators with a new, simplified decision support tool. In conclusion, the generalized methodology could be applied to other reservoir systems where TDG minimization is a critical management objective.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Dynamics of Water Associated with Lithium Ions Distributed in Polyethylene Oxide

We studied the dynamics of water in polyethylene oxide (PEO)/LiCl solution with quasielastic neutron scattering experiments and molecular dynamics (MD) simulations. Two different time scales of water diffusion representing interfacial water and bulk water dynamics have been identified. Furthermore, the measured diffusion coefficient of interfacial water remained 5–10 times smaller than that of bulk water, but both were slowed by approximately 50% in the presence of Li + . Detailed analysis of MD trajectories suggests that Li + is favorably found at the surface of the hydration layer, and the probability to find the caged Li + configuration formed by the PEO is lower than for the noncaged Li + -PEO configuration. In both configurations, however, the slowing down of water molecules is driven by reorienting water molecules and creating water-Li + hydration complexes. Moreover, performing the MD simulation with different ions (Na + and K + ) revealed that smaller ionic radius of the ions is a key factor in disrupting the formation of PEO cages by allowing spaces for water molecules to come in between the ion and PEO.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of High-Fidelity and Efficient Modeling Capabilities for Enabling Co-Optimization of Fuels and Multi-Mode Engines

The objective of this closely coordinated research project is to develop improved physical sub-models and innovative numerical algorithms to enable accurate and efficient predictions of multi-mode combustion to support EERE’s Co-Optima program. To this end, a research pro-gram is proposed that seeks • to develop accurate submodels for predicting multi-mode combustion regimes, wall-heat transfer, non-equilibrium plasma ignition, and combustion-mode transition, • to develop dynamic load-rebalancing algorithms and efficient semi-implicit time-integration schemes for enabling exascale computing, • to validate the computational submodels against experiments and direct numerical simulation (DNS) data in conjunction with sensitivity analysis, and • to support the direct transition of the resulting sub-models into other engine-simulation tools through the development of self-contained modules. All sub-models will be integrated into the open-source exascale engine-simulation platform Nek5000.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Transient Catalytic Reaction Analysis Through Signal Defragmentation

The Temporal Analysis of Products (TAP) pulse response technique provides valuable insights into catalytic function and reaction kinetics. However, complex fragmentation patterns in the TAP mass spectrometry signals can complicate precise quantification, particularly when analyzing transient gas flux data typical of TAP experiments. This work demonstrates a standard defragmentation method that deconvolves transient TAP signals while maintaining the temporal resolution of the experiment. First, the integrals of calibration gas fluxes are used to determine the fingerprint fragmentation pattern and construct a fragmentation matrix. This matrix is then used to defragment experimental flux data at each recorded time point via a non-negative least squares regression. The effectiveness of this method is demonstrated using virtual data and control experiments with a TAP reactor system. The defragmentation is then applied to the more complex propane dehydrogenation reaction on a chromia/alumina catalyst, which can contain up to ten significant gas species in the reactor outlet. Initial propane pulsing reveals an induction period during which propane is fully oxidized to CO2, followed by partial reduction to CO. Afterwards, there is a transition in chemistries towards coking and propylene production. Our example illustrates a practical method for the accurate determination of the time-dependent reactant/product concentrations and rates for a thorough analysis of the propane dehydrogenation kinetics. This approach can be broadly applied to any transient mass spectrometry experiment for a better understanding of catalyst-reaction dynamics.

36 - MATERIALS SCIENCE↗
DOE OSTI2015

EVOLUTION OF NEAR-SURFACE FLOWS INFERRED FROM HIGH-RESOLUTION RING-DIAGRAM ANALYSIS

Ring-diagram analysis of acoustic waves observed at the photosphere can provide a relatively robust determination of the sub-surface flows at a particular time under a particular region. The depth of penetration of the waves is related to the size of the region, hence the depth extent of the measured flows is inversely proportional to the spatial resolution. Most ring-diagram analysis has focused on regions of extent ∼15° (180 Mm) or more in order to provide reasonable mode sets for inversions. Helioseismic and Magnetic Imager (HMI) data analysis also provides a set of ring fit parameters on a scale three times smaller. These provide flow estimates for the outer 1% (7 Mm) of the Sun only, with very limited depth resolution, but with spatial resolution adequate to map structures potentially associated with the belts and regions of magnetic activity. There are a number of systematic effects affecting the determination of flows from a local helioseismic analysis of regions over different parts of the observable disk, and not all of them are well understood. In this study we characterize those systematic effects with higher spatial resolution so that they may be accounted for more effectively in mapping the temporal and spatial evolution of the flows. Leaving open the question of the mean structure of the global meridional circulation and the differential rotation, we describe the near-surface flow anomalies in time and latitude corresponding to the torsional oscillation pattern in differential rotation and analogous patterns in the meridional cell structure as observed by the Solar Dynamics Observatory/HMI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Equilibration and analysis of first-principles molecular dynamics simulations of water

First-principles molecular dynamics (FPMD) simulations based on density functional theory are becoming increasingly popular for the description of liquids. In view of the high computational cost of these simulations, the choice of an appropriate equilibration protocol is critical. In this study, we assess two methods of estimation of equilibration times using a large dataset of first-principles molecular dynamics simulations of water. The Gelman-Rubin potential scale reduction factor [A. Gelman and D. B. Rubin, Stat. Sci. 7, 457 (1992)] and the marginal standard error rule heuristic proposed by White [Simulation 69, 323 (1997)] are evaluated on a set of 32 independent 64-molecule simulations of 58 ps each, amounting to a combined cumulative time of 1.85 ns. The availability of multiple independent simulations also allows for an estimation of the variance of averaged quantities, both within MD runs and between runs. We analyze atomic trajectories, focusing on correlations of the Kohn-Sham energy, pair correlation functions, number of hydrogen bonds, and diffusion coefficient. The observed variability across samples provides a measure of the uncertainty associated with these quantities, thus facilitating meaningful comparisons of different approximations used in the simulations. We find that the computed diffusion coefficient and average number of hydrogen bonds are affected by a significant uncertainty in spite of the large size of the dataset used. Lastly, a comparison with classical simulations using the TIP4P/2005 model confirms that the variability of the diffusivity is also observed after long equilibration times. Complete atomic trajectories and simulation output files are available online for further analysis.

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

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry↗
DOE OSTI2023

Modified Eigen-Decomposition-based Interval Analysis (MEDIA) for Power System Dynamic State Estimation

The Bayesian approach has been used for the dynamic state estimation (DSE) of a power system. However, due to the complexity of noise resources, it is difficult to quantify measurement and process noise using probability density functions (PDFs). To overcome the difficulty, the authors of this paper propose a modified eigen-decomposition-based interval analysis (MEDIA) method, which employs bounds instead of PDFs to quantify the noise, and uses the eigen decomposition method to reduce the negative impact of the overestimation problem. Using the simulation data generated from IEEE 16-machine and IEEE 10-machine systems, it is shown that the proposed MEDIA method can estimate the hard boundaries of dynamic states in real time. Furthermore, comparison with the forward-backward propagation method and the extended set-membership filter also shows that the proposed MEDIA method performs better by providing narrower boundaries in the DSE.

24 POWER TRANSMISSION AND DISTRIBUTION↗