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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Dynamically-Spaced Geo-Grid Segmentation for Weighted Point Sampling on a Polygon Map Layer

Geo-grid algorithms divide a large polygon area into several smaller polygons, which are important for studying or executing a set of operations on underlying topological features of a map. The current geo-grid algorithms divide a large polygon in to a set of smaller but equal size polygons only (e.g. is ArcMaps Fishnet). The time to create a geo-grid is typically proportional to number of smaller polygons created. This raises two problems - (i) They cannot skip unwanted areas (such as water bodies, given about 71% percent of the Earth's surface is water-covered); (ii) They are incognizant to any underlying feature set that requires more deliberation. In this work, we propose a novel dynamically spaced geo-grid segmentation algorithm that overcomes these challenges and provides a computationally optimal output for borderline cases of an uneven polygon. Our method uses an underlying topological feature of population distributions, from the LandScan Global 2016 dataset, for creating grids as a function of these weighted features. We benchmark our results against available algorithms and found our approach improves geo-grid creation. Later on, we demonstrate the proposed approach is more effective in harvesting Points of Interest data from a crowd-sourced platform.

Sims, Kelly↗
DOE OSTI2023

Strategies to perform magnetization reversals in ferromagnets

Systems and methods for reversing a magnetization in a ferromagnet include a nanometer-scale cylindrical ferromagnetic sample having a height to diameter aspect ratio on the order of 2 or greater. A temporally-varying external field comprising an r.f. Pi pulse is applied to the ferromagnetic sample to cause a precession magnetization vector inclined at an angle with respect to the longest axis of the ferromagnetic sample to continuously rotate around the longest axis. One or more parameters of the temporally-varying external field is continuously adjusted based on at least magnetization dynamics of the ferromagnetic sample and/or an angular dependence of a precession frequency of the ferromagnetic sample.

Ketterson, John B.↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Free-energy landscape of a hyperstable RNA tetraloop

In this paper, we report the characterization of the energy landscape and the folding/unfolding thermodynamics of a hyperstable RNA tetraloop obtained through high-performance molecular dynamics simulations at microsecond timescales. Sampling of the configurational landscape is conducted using temperature replica exchange molecular dynamics over three isochores at high, ambient, and negative pressures to determine the thermodynamic stability and the free-energy landscape of the tetraloop. The simulations reveal reversible folding/unfolding transitions of the tetraloop into the canonical A-RNA conformation and the presence of two alternative configurations, including a left-handed Z-RNA conformation and a compact purine Triplet. Increasing hydrostatic pressure shows a stabilizing effect on the A-RNA conformation and a destabilization of the left-handed Z-RNA. Finally, our results provide a comprehensive description of the folded free-energy landscape of a hyperstable RNA tetraloop and highlight the significant advances of all-atom molecular dynamics in describing the unbiased folding of a simple RNA secondary structure motif.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Real-time sparse-sampled Ptychographic imaging through deep neural networks

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples.

Cherukara, Mathew J↗
DOE OSTI2023

An interoperable implementation of collective‐variable based enhanced sampling methods in extended phase space within the OpenMM package

Collective variable (CV)-based enhanced sampling techniques are widely used today for accelerating barrier-crossing events in molecular simulations. A class of these methods, which includes temperature accelerated molecular dynamics (TAMD)/driven-adiabatic free energy dynamics (d-AFED), unified free energy dynamics (UFED), and temperature accelerated sliced sampling (TASS), uses an extended variable formalism to achieve quick exploration of conformational space. These techniques are powerful, as they enhance the sampling of a large number of CVs simultaneously compared to other techniques. Extended variables are kept at a much higher temperature than the physical temperature by ensuring adiabatic separation between the extended and physical subsystems and employing rigorous thermostatting. Here, in this work, we present a computational platform to perform extended phase space enhanced sampling simulations using the open-source molecular dynamics engine OpenMM. The implementation allows users to have interoperability of sampling techniques, as well as employ state-of-the-art thermostats and multiple time-stepping. This work also presents protocols for determining the critical parameters and procedures for reconstructing high-dimensional free energy surfaces. As a demonstration, we present simulation results on the high dimensional conformational landscapes of the alanine tripeptide in vacuo, tetra-N-methylglycine (tetra-sarcosine) peptoid in implicit solvent, and the Trp-cage mini protein in explicit water.

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

Off-Equilibrium Reactivity of Boron-Enriched Metal Diboride Surfaces in Electroreduction Conditions

Boron-based materials, featuring B-dependent reactivity and diverse phases, are emerging as promising catalyst systems. However, the catalytic mechanism on many borides remains poorly understood due to complex surface reconstructions under reaction conditions. Here, we investigate the MoB 2 surface in conditions of hydrogen evolution reaction in acidic media, using grand canonical global optimization, grand canonical density functional theory, ab initio molecular dynamics, free energy surface sampling, and an analytical model for electrochemical barrier evaluation. We propose a boron-enrichment strategy to tune the surface reactivity of the hexagonal face of MoB 2 . We reveal the dynamic nature of the B-enriched surface under H coverage and kinetic trapping of the system in the metastable regime with an extensive examination of the deactivation pathways. The metastable center B site on B-enriched surfaces, featuring buckled-up configuration and a usual relaxation effect, is found to be highly active toward HER via the Volmer–Heyrovsky mechanism. In conclusion, this work demonstrates how off-equilibrium behaviors can arise from the interplay between adsorbate coverage and surface reconstruction on a seemingly simple surface, and we present a theoretical framework and computational workflows to address these behaviors, along with other realistic complexities, in kinetics simulations.

Adsorption↗
DOE OSTI2012

X-RAY PROPERTIES OF INTERMEDIATE-MASS BLACK HOLES IN ACTIVE GALAXIES. III. SPECTRAL ENERGY DISTRIBUTION AND POSSIBLE EVIDENCE FOR INTRINSICALLY X-RAY-WEAK ACTIVE GALACTIC NUCLEI

We present a systematic X-ray study, the third in a series, of 49 active galactic nuclei with intermediate-mass black holes (IMBH; {approx}10{sup 5}-10{sup 6} M{sub Sun }) using Chandra observations. We detect 42 out of 49 targets with a 0.5-2 keV X-ray luminosity 10{sup 41}-10{sup 43} erg s{sup -1}. We perform spectral fitting for the 10 objects with enough counts (>200), and they are all well fit by a simple power-law model modified by Galactic absorption, with no sign of significant intrinsic absorption. While we cannot fit the X-ray spectral slope directly for the rest of the sample, we estimate it from the hardness ratio and find a range of photon indices consistent with those seen in more luminous and massive objects. The X-ray-to-optical spectral slope ({alpha}{sub ox}) of our IMBH sample is systematically flatter than in active galaxies with more massive black holes, consistent with the well-known correlation between {alpha}{sub ox} and UV luminosity. Thanks to the wide dynamic range of our sample, we find evidence that {alpha}{sub ox} increases with decreasing M{sub BH} as expected from accretion disk models, where the UV emission systematically decreases as M{sub BH} decreases and the disk temperature increases. We also find a long tail toward low {alpha}{sub ox} values. While some of these sources may be obscured, given the high L{sub bol}/L{sub Edd} values in the sample, we argue that some may be intrinsically X-ray-weak, perhaps owing to a rare state that radiates very little coronal emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Image-derived and arterial blood sampled input functions for quantitative PET imaging of the angiotensin II subtype 1 receptor in the kidney

Purpose: The radioligand {sup 11}C-KR31173 has been introduced for positron emission tomography (PET) imaging of the angiotensin II subtype 1 receptor in the kidney in vivo. To study the biokinetics of {sup 11}C-KR31173 with a compartmental model, the input function is needed. Collection and analysis of arterial blood samples are the established approach to obtain the input function but they are not feasible in patients with renal diseases. The goal of this study was to develop a quantitative technique that can provide an accurate image-derived input function (ID-IF) to replace the conventional invasive arterial sampling and test the method in pigs with the goal of translation into human studies. Methods: The experimental animals were injected with [{sup 11}C]KR31173 and scanned up to 90 min with dynamic PET. Arterial blood samples were collected for the artery derived input function (AD-IF) and used as a gold standard for ID-IF. Before PET, magnetic resonance angiography of the kidneys was obtained to provide the anatomical information required for derivation of the recovery coefficients in the abdominal aorta, a requirement for partial volume correction of the ID-IF. Different image reconstruction methods, filtered back projection (FBP) and ordered subset expectation maximization (OS-EM), were investigated for the best trade-off between bias and variance of the ID-IF. The effects of kidney uptakes on the quantitative accuracy of ID-IF were also studied. Biological variables such as red blood cell binding and radioligand metabolism were also taken into consideration. A single blood sample was used for calibration in the later phase of the input function. Results: In the first 2 min after injection, the OS-EM based ID-IF was found to be biased, and the bias was found to be induced by the kidney uptake. No such bias was found with the FBP based image reconstruction method. However, the OS-EM based image reconstruction was found to reduce variance in the subsequent phase of the ID-IF. The combined use of FBP and OS-EM resulted in reduced bias and noise. After performing all the necessary corrections, the areas under the curves (AUCs) of the AD-IF were close to that of the AD-IF (average AUC ratio =1 ± 0.08) during the early phase. When applied in a two-tissue-compartmental kinetic model, the average difference between the estimated model parameters from ID-IF and AD-IF was 10% which was within the error of the estimation method. Conclusions: The bias of radioligand concentration in the aorta from the OS-EM image reconstruction is significantly affected by radioligand uptake in the adjacent kidney and cannot be neglected for quantitative evaluation. With careful calibrations and corrections, the ID-IF derived from quantitative dynamic PET images can be used as the input function of the compartmental model to quantify the renal kinetics of {sup 11}C-KR31173 in experimental animals and the authors intend to evaluate this method in future human studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗
DOE OSTI2015

Dynamics of tetrahydrofuran as minority component in a mixture with poly(2-(dimethylamino)ethyl methacrylate): A neutron scattering and dielectric spectroscopy investigation

We have investigated a mixture of poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA) and tetrahydrofuran (THF) (70 wt. % PDMAEMA/30 wt. % THF) by combining dielectric spectroscopy and quasielastic neutron scattering (QENS) on a labelled sample, focusing on the dynamics of the THF molecules. Two independent processes have been identified. The “fast” one has been qualified as due to an internal motion of the THF ring leading to hydrogen displacements of about 3 Å with rather broadly distributed activation energies. The “slow” process is characterized by an Arrhenius-like temperature dependence of the characteristic time which persists over more than 9 orders of magnitude in time. The QENS results evidence the confined nature of this process, determining a size of about 8 Å for the volume within which THF hydrogens’ motions are restricted. In a complementary way, we have also investigated the structural features of the sample. This study suggests that THF molecules are well dispersed among side-groups nano-domains in the polymer matrix, ruling out a significant presence of clusters of solvent. Such a good dispersion, together with a rich mobility of the local environment, would prevent cooperativity effects to develop for the structural relaxation of solvent molecules, frustrating thereby the emergence of Vogel-Fulcher-like behavior, at least in the whole temperature interval investigated.

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

Mapping valence electron distributions with multipole density formalism using 4D-STEM

Recent advancement in aberration correction and detector technology opened a door to various applications using 4D-STEM, which yields a diffraction pattern for each scanning position within a crystal unit-cell in scanning transmission electron microscopy (STEM) and generates incredible amounts of data in momentum space. Currently 4D-STEM analysis relies on the center-of-mass of the diffraction patterns in electric field and charge density mapping. It only derives the total projected charge density and is limited to phase objects, e.g. extremely thin samples. Here, we propose a new analytical method to accurately map aspherical valence electron distributions with atom-centered multipolar functions formalism using the whole 4D-STEM dataset. We demonstrate that, with the full dynamical calculations for various sample thicknesses, the method is sensitive not only to the miniscule charge transfer, but also to the atomic site symmetry and aspherical electron orbitals. The process of the refinement is much more robust and reliable than quantitative convergent beam electron diffraction.

4D-STEM↗
DOE OSTI2019

Quantitative infrared spectroscopy of environmentally sensitive and rough materials

Fourier transform infrared (FTIR) spectroscopy is a widely used characterization technique for studying chemical compositions and lightmatter interactions in the infrared range. However, it remains challenging to use conventional FTIR equipment to characterize materials that are environmentally sensitive and/or have rough surfaces due to their dynamic response to external stimuli (e.g., humidity) and light scattering from the sample surface. Here, we describe an approach enabling quantitative infrared spectroscopy measurements of these challenging samples, including transmittance, reflectance, and emissivity. We designed and 3D-printed a miniaturized environmental chamber that can be directly inserted into the sample holder of a conventional integrating sphere to perform total transmission and reflection measurements in controlled environments. Moreover, a calibration method was developed to exclude light scattering from rough surfaces of the sample and the distortion created by infrared windows. To illustrate the potential application of this method, we have performed quantitative infrared measurements, both specular and diffusive, on a sapphire standard reference with a specular surface, as well as a textile sample that has a rough surface and is dynamically responsive to changes in humidity. The calibrated results measured with the equipped chamber match those measured without the IR windows, demonstrating the viability of our environmental chamber and the proposed calibration method. This quantitative infrared spectroscopy measurement technique may help advance fields such as metasurfaces and adaptive textiles, where samples are often rough, dynamically responsive, and/or environmentally sensitive.

3D printing↗
DOE OSTI2015

Communication: Quantitative multi-site frequency maps for amide I vibrational spectroscopy

An accurate method for predicting the amide I vibrational spectrum of a given protein structure has been sought for many years. Significant progress has been made recently by sampling structures from molecular dynamics simulations and mapping local electrostatic variables onto the frequencies of individual amide bonds. Agreement with experiment, however, has remained largely qualitative. Previously, we used dipeptide fragments and isotope-labeled constructs of the protein G mimic NuG2b as experimental standards for developing and testing amide I frequency maps. Here, we combine these datasets to test different frequency-map models and develop a novel method to produce an optimized four-site potential (4P) map based on the CHARMM27 force field. Together with a charge correction for glycine residues, the optimized map accurately describes both experimental datasets, with average frequency errors of 2–3 cm{sup −1}. This 4P map is shown to be convertible to a three-site field map which provides equivalent performance, highlighting the viability of both field- and potential-based maps for amide I spectral modeling. The use of multiple sampling points for local electrostatics is found to be essential for accurate map performance.

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

Coherent amplification of X-ray scattering from meso-structures

Small-angle X-ray scattering (SAXS) often includes an unwanted background, which increases the required measurement time to resolve the sample structure. This is undesirable in all experiments, and may make measurement of dynamic or radiation-sensitive samples impossible. Here, we demonstrate a new technique, applicable when the scattering signal is background-dominated, which reduces the requisite exposure time. Our method consists of exploiting coherent interference between a sample with a designed strongly scattering `amplifier'. A modified angular correlation function is used to extract the symmetry of the interference term; that is, the scattering arising from the interference between the amplifier and the sample. This enables reconstruction of the sample's symmetry, despite the sample scattering itself being well below the intensity of background scattering. Thus, coherent amplification is used to generate a strong scattering term (well above background), from which sample scattering is inferred. We validate this method using lithographically defined test samples.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Ultrafast Laser Diagnostics for Energetic-Material Ignition Mechanisms: Tools for Physics-Based Model Development.

We present the results of an LDRD project to develop diagnostics to perform fundamental measurements of material properties during shock compression of condensed phase materials at micron spatial scales and picosecond time scales. The report is structured into three main chapters, which each focus on a different diagnostic devel opment effort. Direct picosecond laser drive is used to introduce shock waves into thin films of energetic and inert materials. The resulting laser - driven shock properties are probed via Ultrafast Time Domain Interferometry (UTDI), which can additionally be used to generate shock Hugoniot data in tabletop experiments. Stimulated Raman scattering (SRS) is developed as a temperature diagnostic. A transient absorption spectroscopy setup has been developed to probe shock - induced changes during shock compressio n. UTDI results are presented under dynamic, direct - laser - drive conditions and shock Hugoniots are estimated for inert polystyrene samples and for the explosive hexanitroazobenzene, with results from both Sandia and Lawrence Livermore presented here. SRS a nd transient absorption diagnostics are demonstrated on static thin - film samples, and paths forward to dynamic experiments are presented.

Kearney, Sean Patrick↗