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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 1,783 records · Page 99
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DOE OSTI2021

Structural and Dynamical Roles of Bound Polymer Chains in Rubber Reinforcement

The addition of nanofillers to rubber matrices is a powerful route to improve the mechanical properties. Here, we focus on a molecular understanding of basic mechanisms that are important for the reinforcement in rubbers. The key role in this process is ascribed to bound rubber (BR) that engages with the matrix as well as with adjacent nanofillers. To date, this understanding has been impeded by the lack of experimental tools to directly probe the BR chains buried in a polymer matrix composed of the same polymer. To tackle this challenge, we combine neutron scattering/spectroscopy techniques with isotope-labeling and molecular dynamics simulations. The system is a simplified carbon-black-filled polybutadiene. The combined experimental and computational results provide new insights into the local structural and dynamical heterogeneities of BR chains and their interactions with the matrix polymer, highlighting (i) the structural partition of the bound chains into three components (i.e., trains, loops, and tails) and their fractions; (ii) their dynamical hierarchies, i.e., the trains that remain immobile on the filler surface, the loops that are fairly large and hence allow the interdigitation of matrix chains, and the tails with their unique characteristics to reach far out into the matrix and entangle with matrix chains. These multiple roles of the constituent components of the BR chains promote the formation of a well-developed adhesive polymer–filler interface, enhancing the elastic property of a filled rubber. Finally, the comprehensive understanding derived and validated by the model rubber will be translatable to many other polymer nanocomposites.

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

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical van der Waals heterojunction diodes comprising 2D semiconductors on 3D β-Ga 2 O 3

Wide bandgap semiconductors such as gallium oxide (Ga 2 O 3 ) have attracted much attention for their use in next-generation high-power electronics. Although single-crystal Ga 2 O 3 substrates can be routinely grown from melt along various orientations, the influence of such orientations has been seldom reported. Further, making rectifying p–n diodes from Ga 2 O 3 has been difficult due to lack of p-type doping. In this study, we fabricated and optimized 2D/3D vertical diodes on β-Ga 2 O 3 by varying the following three factors: substrate planar orientation, choice of 2D material and metal contacts. Furthermore, the quality of our devices was validated using high-temperature dependent measurements, atomic-force microscopy (AFM) techniques and technology computer-aided design (TCAD) simulations. Our findings suggest that 2D/3D β-Ga 2 O 3 vertical heterojunctions are optimized by substrate planar orientation (–201), combined with 2D WS 2 exfoliated layers and Ti contacts, and show record rectification ratios (>10 6 ) concurrently with ON-Current density (>10 3 A cm –2 ) for application in power rectifiers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale investigation of the mechanism of biomass deconstruction in the dimethyl isosorbide/water Co-solvent pretreatment system

In the context of promoting a circular bioeconomy, the development of green and efficient lignocellulosic biomass pretreatment technologies so as to realize high value-added biomass utilization is of intense interest. We demonstrated the potential of the bio-based green solvent dimethyl isosorbide (DMI) for the fractionation of Eucalyptus biomass with excellent performance. Here, to investigate the mechanisms involved in biomass fractionation, microimaging and microspectroscopic techniques were employed together with molecular dynamics (MD) simulation and COSMO-RS quantum chemical calculations to derive multiscale information. Both the microstructure and regional chemistry of the cell wall vary significantly with the volume ratio of DMI/H 2 O. The strongest effects were found at DMI/H 2 O = 9:1 and showed visible cell wall tearing cracks and cell wall deformation and collapse as well as the lowest values of cell wall thickness and circularity. From the MD simulations, lignin exhibits collapsed-like structure in pure H 2 O with low solvent accessibility surface area (SASA) and radius of gyration (R g ). In contrast, lignin in DMI/H 2 O shows extended structure with high SASA and solvent interactions dominated by van der Waals forces, with maximal contact in the 9:1 (v/v) system. Further, the COSMO-RS calculated sigma (σ-) potential suggests the intermolecular interactions in DMI and DMI/H 2 O co-solvent are weak, leading to stronger interaction with lignin and correspondingly higher lignin dissolution. The radial distribution functions and σ-potential all show that again DMI/H 2 O at 9:1 is an optimal volume ratio for high lignin dissolution. Finally, this study provides a solvent-ratio dependent mechanism for the action of polar aprotic solvents in the deconstruction of biomass.

09 BIOMASS FUELS↗
DOE OSTI2022

Image segmentation for analyzing galaxy-galaxy strong lensing systems

The goal of this Letter is to develop a machine learning model to analyze the main gravitational lens and detect dark substructure (subhalos) within simulated images of strongly lensed galaxies. Using the technique of image segmentation, we turn the task of identifying subhalos into a classification problem, where we label each pixel in an image as coming from the main lens, a subhalo within a binned mass range, or neither. Our network is only trained on images with a single smooth lens and either zero or one subhalo near the Einstein ring. On an independent test set with lenses with large ellipticities, quadrupole and octopole moments, and for source apparent magnitudes between 17–25, the area of the main lens is recovered accurately. On average, only 1.3% of the true area is missed and 1.2% of the true area is added to another part of the lens. In addition, subhalos as light as 10 8.5 M ⊙ can be detected if they lie in bright pixels along the Einstein ring. Furthermore, the model is able to generalize to new contexts it has not been trained on, such as locating multiple subhalos with varying masses or more than one large smooth lens.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

An implicit-explicit time splitting strategy for the far SOL plasma fluid model with DG-FEM discretization

We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.

Burkovska, Olena [ORNL] (ORCID:0000000163101130)↗
DOE OSTI2014

Free energy of RNA-counterion interactions in a tight-binding model computed by a discrete space mapping

The thermodynamic stability of a folded RNA is intricately tied to the counterions and the free energy of this interaction must be accounted for in any realistic RNA simulations. Extending a tight-binding model published previously, in this paper we investigate the fundamental structure of charges arising from the interaction between small functional RNA molecules and divalent ions such as Mg{sup 2+} that are especially conducive to stabilizing folded conformations. The characteristic nature of these charges is utilized to construct a discretely connected energy landscape that is then traversed via a novel application of a deterministic graph search technique. This search method can be incorporated into larger simulations of small RNA molecules and provides a fast and accurate way to calculate the free energy arising from the interactions between an RNA and divalent counterions. The utility of this algorithm is demonstrated within a fully atomistic Monte Carlo simulation of the P4-P6 domain of the Tetrahymena group I intron, in which it is shown that the counterion-mediated free energy conclusively directs folding into a compact structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Linearized spectrum correlation analysis for line emission measurements

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100–200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

A tungsten-rhenium interatomic potential for point defect studies

A tungsten-rhenium (W-Re) classical interatomic potential is developed within the embedded atom method (EAM) interaction framework. A force-matching method is employed to fit the potential to ab initio forces, energies, and stresses. Simulated annealing is combined with the conjugate gradient technique to search for an optimum potential from over 1000 initial trial sets. The potential is designed for studying point defects in W-Re systems. It gives good predictions of the formation energies of Re defects in W and the binding energies of W self-interstitial clusters with Re. The potential is further evaluated for describing the formation energy of structures in the σ and χ intermetallic phases. The predicted convex-hulls of formation energy are in excellent agreement with ab initio data. In pure Re, the potential can reproduce the formation energies of vacancy and self-interstitial defects sufficiently accurately, and gives the correct ground state self-interstitial configuration. Furthermore, by including liquid structures in the fit, the potential yields a Re melting temperature (3130 K) that is close to the experimental value (3459 K).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

In silico evidence for sequence-dependent nucleosome sliding

Significance The dynamic compaction of DNA into chromatin is essential for gene expression. Errors during compaction are associated with numerous diseases. Several molecular factors are known to affect chromatin dynamics, but their relative importance and the interplay between them are poorly understood. A detailed molecular model is used here to examine chromatin dynamics at the level of its most fundamental building block, namely the nucleosome. Nucleosome dynamics are demonstrated to be encoded in the DNA sequence itself, and key fundamental factors are uncovered that can significantly alter these dynamics at the molecular level. The results serve to complete a hitherto unavailable description of nucleosome dynamics by introducing previously unappreciated molecular processes, with the potential to influence macroscopic chromatin structure and genetics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Conformational free energy landscape of a glutamate transporter and microscopic details of its transport mechanism

Removing glutamate from the synaptic cleft is vital for proper function of the brain. Excitatory amino acid transporters mediate this process by uptaking the neurotransmitter from the synaptic cleft back to the cell after its release. The archaeal homolog, Glt Ph , an aspartate transporter fromPyrococcus horikoshii, presents the best structurally characterized model for this family of transporters. In order to transport, Glt Ph undergoes elevator-like conformational changes between inward-facing (IF) and outward-facing (OF) states. Here, we characterize, at an atomic level, the OF⇌IF transition of Glt Ph in differentapo/bound states using a combination of ensemble-based enhanced sampling techniques, employing more than two thousand of coupled simulation replicas of membrane-embedded Glt Ph . The resulting free-energy profiles portray the transition ofapo/bound states as a complex four-stage process, while sodium binding alone locks the structure in one of its states. Along the transition, the transport domain (TD) disengages from the scaffold domain (SD), allowing it to move as a piston sliding vertically with respect to the membrane during the elevator-like motion of TD. Lipid interactions with residues comprising the SD–TD interface directly influence the large-scale conformational changes and, consequently, the energetics of transport. Structural intermediates formed during the transition leak water molecules and may correlate to the uncoupled Cl − ion conductance observed experimentally in both prokaryotic and mammalian glutamate transporters. Mechanistic insights obtained from our study provide a structural framework for better development of therapeutic for neurological disorders.

Science & Technology - Other Topics↗
DOE OSTI2025

A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics

The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.

computational combustion↗
DOE OSTI2013

MEASURING THE MASS DISTRIBUTION IN GALAXY CLUSTERS

Cluster mass profiles are tests of models of structure formation. Only two current observational methods of determining the mass profile, gravitational lensing, and the caustic technique are independent of the assumption of dynamical equilibrium. Both techniques enable the determination of the extended mass profile at radii beyond the virial radius. For 19 clusters, we compare the mass profile based on the caustic technique with weak lensing measurements taken from the literature. This comparison offers a test of systematic issues in both techniques. Around the virial radius, the two methods of mass estimation agree to within {approx}30%, consistent with the expected errors in the individual techniques. At small radii, the caustic technique overestimates the mass as expected from numerical simulations. The ratio between the lensing profile and the caustic mass profile at these radii suggests that the weak lensing profiles are a good representation of the true mass profile. At radii larger than the virial radius, the extrapolated Navarro, Frenk and White fit to the lensing mass profile exceeds the caustic mass profile. Contamination of the lensing profile by unrelated structures within the lensing kernel may be an issue in some cases; we highlight the clusters MS0906+11 and A750, superposed along the line of sight, to illustrate the potential seriousness of contamination of the weak lensing signal by these unrelated structures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A comprehensive method of estimating electric fields from vector magnetic field and Doppler measurements

Photospheric electric fields, estimated from sequences of vector magnetic field and Doppler measurements, can be used to estimate the flux of magnetic energy (the Poynting flux) into the corona and as time-dependent boundary conditions for dynamic models of the coronal magnetic field. We have modified and extended an existing method to estimate photospheric electric fields that combines a poloidal-toroidal decomposition (PTD) of the evolving magnetic field vector with Doppler and horizontal plasma velocities. Our current, more comprehensive method, which we dub the 'PTD-Doppler-FLCT Ideal' (PDFI) technique, can now incorporate Doppler velocities from non-normal viewing angles. It uses the FISHPACK software package to solve several two-dimensional Poisson equations, a faster and more robust approach than our previous implementations. Here, we describe systematic, quantitative tests of the accuracy and robustness of the PDFI technique using synthetic data from anelastic MHD (ANMHD) simulations, which have been used in similar tests in the past. We find that the PDFI method has less than 1% error in the total Poynting flux and a 10% error in the helicity flux rate at a normal viewing angle (θ = 0) and less than 25% and 10% errors, respectively, at large viewing angles (θ < 60°). We compare our results with other inversion methods at zero viewing angle and find that our method's estimates of the fluxes of magnetic energy and helicity are comparable to or more accurate than other methods. We also discuss the limitations of the PDFI method and its uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Optimized blind gamma-ray pulsar searches at fixed computing budget

The sensitivity of blind gamma-ray pulsar searches in multiple years worth of photon data, as from the Fermi LAT, is primarily limited by the finite computational resources available. Addressing this 'needle in a haystack' problem, here we present methods for optimizing blind searches to achieve the highest sensitivity at fixed computing cost. For both coherent and semicoherent methods, we consider their statistical properties and study their search sensitivity under computational constraints. The results validate a multistage strategy, where the first stage scans the entire parameter space using an efficient semicoherent method and promising candidates are then refined through a fully coherent analysis. We also find that for the first stage of a blind search incoherent harmonic summing of powers is not worthwhile at fixed computing cost for typical gamma-ray pulsars. Further enhancing sensitivity, we present efficiency-improved interpolation techniques for the semicoherent search stage. Via realistic simulations we demonstrate that overall these optimizations can significantly lower the minimum detectable pulsed fraction by almost 50% at the same computational expense.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Modeling the power spectra of active galactic nuclei with Markov Chain Monte Carlo

We present a new method for calculating the power spectral density (PSD) of a light curve using Markov Chain Monte Carlo principles. This method allows for a faster estimation of PSD parameters, along with more robust estimates of the uncertainties for each parameter. We show that this technique is valid by applying it to a simulated light curve, where it correctly estimates the PSD parameters. We then analyze the light curves of two nearby AGNs, NGC 4593 and Mkn 79. Breaks in the PSD are detected at timescales of 3.3{sub −1.9}{sup +4.4} and 1.8{sub −1.4}{sup +5.5} days, respectively. These values agree with the predicted breaks based on scaling relationships with other AGNs and galactic black hole binary systems. The break timescale for each object agrees with the viscous timescale for a geometrically thick accretion disk, supporting the idea that a propagating fluctuation model may be responsible for variations in the X-ray flux.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

MEASURING THE DIRECTION AND ANGULAR VELOCITY OF A BLACK HOLE ACCRETION DISK VIA LAGGED INTERFEROMETRIC COVARIANCE

We show that interferometry can be applied to study irregular, rapidly rotating structures, as are expected in the turbulent accretion flow near a black hole. Specifically, we analyze the lagged covariance between interferometric baselines of similar lengths but slightly different orientations. For a flow viewed close to face-on, we demonstrate that the peak in the lagged covariance indicates the direction and angular velocity of the emission pattern from the flow. Even for moderately inclined flows, the covariance robustly estimates the flow direction, although the estimated angular velocity can be significantly biased. Importantly, measuring the direction of the flow as clockwise or counterclockwise on the sky breaks a degeneracy in accretion disk inclinations when analyzing time-averaged images alone. We explore the potential efficacy of our technique using three-dimensional, general relativistic magnetohydrodynamic simulations, and we highlight several baseline pairs for the Event Horizon Telescope (EHT) that are well-suited to this application. These results indicate that the EHT may be capable of estimating the direction and angular velocity of the emitting material near Sgr A*, and they suggest that a rotating flow may even be utilized to improve imaging capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

CMB constraint on non-Gaussianity in isocurvature perturbations

We study the CMB constraints on non-Gaussianity in CDM isocurvature perturbations. Non-Gaussian isocurvature perturbations can be produced in various models at the very early stage of the Universe. Since the isocurvature perturbations little affect the structure formation at late times, CMB is the best probe of isocurvature non-Gaussianity at least in the near future. In this paper, we focus on non-Gaussian curvature and isocurvature perturbations of the local-type, which are uncorrelated and in the form ζ = ζ{sub G}+(3/5)f{sub NL}(ζ{sub G}{sup 2}−(ζ{sub G}{sup 2})) and S = S{sub G}+f{sub NL}{sup (ISO)}(S{sub G}−(S{sub G}{sup 2})), and constrain the non-linearity parameter of isocurvature perturbations, f{sub NL}{sup (ISO)}, as well as the curvature one f{sub NL}. For this purpose, we employ several state-of-art techniques for the analysis of CMB data and simulation. Assuming that isocurvature perturbations are subdominant, we apply our method to the WMAP 7-year data of temperature anisotropy and obtain constraints on a combination α{sup 2}f{sub NL}{sup (ISO)}, where α is the ratio of the power spectrum of isocurvature perturbations to that of the adiabatic ones. When the adiabatic perturbations are assumed to be Gaussian, we obtained a constraint α{sup 2}f{sub NL}{sup (ISO)} = 40±66 assuming the power spectrum of isocurvature perturbations is scale-invariant. When we assume that the adiabatic perturbations can also be non-Gaussian, we obtain f{sub NL} = 38±24 and α{sup 2}f{sub NL}{sup (ISO)} = −8±72. We also discuss implications of our results for the axion CDM isocurvature model.

79 ASTRONOMY AND ASTROPHYSICS↗