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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗
DOE OSTI2021

Scattering Matrix Determination in Crystalline Materials from 4D Scanning Transmission Electron Microscopy at a Single Defocus Value

Recent work has revived interest in the scattering matrix formulation of electron scattering in transmission electron microscopy as a stepping stone toward atomic-resolution structure determination in the presence of multiple scattering. Here, we discuss ways of visualizing the scattering matrix that make its properties clear. Through a simulation-based case study incorporating shot noise, we shown how regularizing on this continuity enables the scattering matrix to be reconstructed from 4D scanning transmission electron microscopy (STEM) measurements from a single defocus value. Intriguingly, for crystalline samples, this process also yields the sample thickness to nanometer accuracy with no a priori knowledge about the sample structure. The reconstruction quality is gauged by using the reconstructed scattering matrix to simulate STEM images at defocus values different from that of the data from which it was reconstructed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
DOE OSTI2022

The role of temperature on defect diffusion and nanoscale patterning in graphene

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties through geometric and strain effects, introduce edge states and other local or extended topological defects, and sculpt circuit paths. The focused beam of a scanning transmission electron microscope (STEM) can be used to remove atoms, enabling milling, doping, and deposition. Utilization of a STEM as an atomic scale fabrication platform is increasing; however, a detailed understanding of beam-induced processes and the subsequent cascade of aftereffects is lacking. Here, we examine the electron beam effects on atomically clean graphene at a variety of temperatures ranging from 400 to 1000 °C. We find that temperature plays a significant role in the milling rate and moderates competing processes of carbon adatom coalescence, graphene healing, and the diffusion (and recombination) of defects. The results of this work can be applied to a wider range of 2D materials and introduce better understanding of defect evolution in graphite and other bulk layered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Stochastic Techno Economic Model

The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.

Burli, PralhadH↗
DOE OSTI2020

Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. Further, we evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover-and critical for many applications of these surrogates-inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tailoring P2/P3‐Intergrowth in Manganese‐Based Layered Transition Metal Oxide Positive Electrodes via Sodium Content for Na‐Ion Batteries

High-manganese content sodium-ion positive electrodes have received heightened interest as an alternative to contemporary Li-ion chemistries due to their high abundance, low toxicity, and even geographical distribution. However, these materials typically suffer from poor capacity, unstable cycling performance, and sluggish Na + kinetics. Herein, we explore a manganese-based layered transition metal oxide (Na x N 0.25 Mn 0.75 O 2 ) and show by X-ray diffraction (XRD) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) that careful variation of the sodium content can instigate the formation of a biphasic intergrowth. This intergrown P2/P3 material offered a higher capacity than its monophasic P2 counterpart due to the P3 structure having greater low-voltage Mn 3+/4+ redox. Further, the intergrowth material offers greatly enhanced kinetics and cycling stability when compared to single-phase P3 material, due to the stabilizing nature of the P2 structure, elucidated by galvanostatic intermittent titration technique (GITT) and operando synchrotron X-ray diffraction. These results highlight the beneficial effect that the intergrowth structure has on the electrochemical performance of high-manganese content positive electrode for future sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Synergistic enhancement of nanocellulose foam with dual in situ mineralization and crosslinking reaction

Cellulose nanocrystals (CNCs) foams have recently gained research interests because they are renewable, abundant, biodegradable and exhibit high surface area. However, the application of CNCs-based foams is still challenging, which is attributed to its lack of effective entanglements between the CNCs particles, thus lowering foam properties. In this study, a synergistic enhancement strategy was proposed, based on the in situ mineralization with hydroxyapatite (HAP) layer onto the CNCs surface, followed by a chemical crosslinking reaction. The physical and chemical structures of the composites were analyzed with SEM, STEM, XRD, FTIR, and TGA. By controlling the amount of coated HAP and the crosslinker, it is possible to manufacture a series of CNCs-based foams that are lightweight (50–75 mg/cm 3 ), highly porous (~90%) with high water absorption (>1300%) and outstanding mechanical strength properties (as high as 1.37 MPa). Moreover, our study further indicated that these CNCs/HAP materials could increase the proliferation of rat osteoblast cells. The method developed in this study presents a novel approach to design improved networked CNCs foam, which has the potential to be used in thermal-retardant material, wastewater treatment, tissue engineering, and personal care applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Helping System Engineers Bridge the Peaks

In our experience at NASA, system engineers generally follow the Twin Peaks approach when developing safety-critical systems. However, iterations between the peaks require considerable manual, and in some cases duplicate, effort. A significant part of the manual effort stems from the fact that requirements are written in English natural language rather than a formal notation. In this work, we propose an approach that enables system engineers to leverage formal requirements and automated test generation to streamline iterations, effectively "bridging the peaks". The key to the approach is a formal language notation that a) system engineers are comfortable with, b) is supported by a family of automated V&V tools, and c) is semantically rich enough to describe the requirements of interest. We believe the combination of formalizing requirements and providing tool support to automate the iterations will lead to a more efficient Twin Peaks implementation at NASA.

Requirements↗
DOE OSTI2025

In Situ Formation of Ripplocations in Hybrid Organic–Inorganic MXenes

Abstract Inorganic–organic hybrid MXenes (h‐MXenes) are a family of 2D transition metal carbides and nitrides functionalized with alkylimido and alkylamido surface groups. Using cryogenic and room temperature scanning transmission electron microscopy (STEM) and electron energy‐loss spectroscopy (EELS), it is shown that ripplocations, a form of a fundamental defect in 2D and layered structures, are abundant in this family of materials. Furthermore, detailed studies of electron probe sample interactions, focusing on structural deformations caused by the electron beam are presented. The findings indicate that at cryogenic temperatures (≈100 K) and below a specific dose threshold, the structure of h‐MXenes remains largely intact. However, exceeding this threshold leads to electron beam‐induced deformation through ripplocations. Interestingly, the deformation behavior, required dose, and resultant structure are highly dependent on temperature. At 100 K, it is demonstrated that the electron beam can induce ripplocations in situ with a high degree of precision.

Chemistry↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
NASA NTRS2001

Simulation of the Effect of Realistic Space Vehicle Environments on Binary Metal Alloys

Simulations that assess the effect of space vehicle acceleration environments on the solidification of Pb-Sb alloys are reported. Space microgravity missions are designed to provide a near zero-g acceleration environment for various types of scientific experiments. Realistically. these space missions cannot provide a perfect environment. Vibrations caused by crew activity, on-board experiments, support systems stems (pumps, fans, etc.), periodic orbital maneuvers, and water dumps can all cause perturbations to the microgravity environment. In addition, the drag on the space vehicle is a source of acceleration. Therefore, it is necessary to predict the impact of these vibration-perturbations and the steady-state drag acceleration on the experiments. These predictions can be used to design mission timelines. so that the experiment is run during times that the impact of the acceleration environment is acceptable for the experiment of interest. The simulations reported herein were conducted using a finite element model that includes mass, species, momentum, and energy conservation. This model predicts the existence of "channels" within the processing mushy zone and subsequently "freckles" within the fully processed solid, which are the effects of thermosolutal convection. It is necessary to mitigate thermosolutal convection during space experiments of metal alloys, in order to study and characterize diffusion-controlled transport phenomena (microsegregation) that are normally coupled with macrosegregation. The model allows simulation of steady-state and transient acceleration values ranging from no acceleration (0 g). to microgravity conditions (10(exp -6) to 10(exp -3) g), to terrestrial gravity conditions (1 g). The transient acceleration environments simulated were from the STS-89 SpaceHAB mission and from the STS-94 SpaceLAB mission. with on-orbit accelerometer data during different mission periods used as inputs for the simulation model. Periods of crew exercise, quiet (no crew activity), and nominal conditions from STS-89 were used as simulation inputs as were periods of nominal. overboard water-dump, and free-drift (no orbit maneuvering operations) from STS-94. Steady-state acceleration environments of 0.0 and 10(exp -6) to 10(exp -1) g were also simulated, to serve as a comparison to the transient data and to assess an acceptable magnitude for the steady-state vehicle drag

Westra, Douglas G.↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2023

Optimization of peptide amphiphile-lipid raft interaction by changing peptide amphiphile lipophilicity

Various peptide amphiphile (PA) molecules have been developed to promote bone regeneration. Previously we discovered that a peptide amphiphile with a palmitic acid tail (C 16 ) attenuates the signaling threshold of leucine-rich amelogenin peptide (LRAP)-mediated Wnt activation by increasing membrane lipid raft mobility. In the current study, we found that treatment of murine ST2 cells with an inhibitor (Nystatin) or Caveolin-1-specific siRNA abolishes the effect of C 16 PA, indicating that Caveolin-mediated endocytosis is required. Here, to determine whether hydrophobicity of the PA tail plays a role in its signaling effect, we modified the length of the tail (C 12 , C 16 and C 22 ) or composition (cholesterol). While shortening the tail (C 12 ) decreased the signaling effect, lengthening the tail (C 22 ) had no prominent effect. On the other hand, the cholesterol PA displayed a similar function as the C 16 PA at the same concentration of 0.001% w/v. Interestingly, a higher concentration of C 16 PA (0.005%) is cytotoxic while cholesterol PA at the higher concentration (0.005%) is well-tolerated by cells. Use of the cholesterol PA at 0.005% enabled a further reduction of the signaling threshold of LRAP to 0.20 nM, compared to 0.25 nM at 0.001%. Caveolin-mediated endocytosis is also required for cholesterol PA, as evidenced by Caveolin-1 siRNA knockdown experiments. We further demonstrated that the noted effects of cholesterol PA are also observed in human bone marrow mesenchymal stem cells (BMMSCs). Taken together, these results indicate that the cholesterol PA modulates lipid raft/caveolar dynamics, thereby increasing receptor sensitivity for activation of canonical Wnt signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Resolving Enhanced Mn 2+ Luminescence near the Surface of CsPbCl 3 with Time-Resolved Cathodoluminescence Imaging

Mn 2+ doping of lead halide perovskites has garnered recent interest because it produces stable orange luminescence in tandem with perovskite emission. In this work, we observe enhanced Mn 2+ luminescence at the edges of Mn 2+ -doped CsPbCl 3 perovskite microplates and suggest an explanation for its origin using the high spatiotemporal resolution of time-resolved cathodoluminescence (TRCL) imaging. We reveal two luminescent decay components that we attribute to two different Mn 2+ populations. While each component appears to be present both near the surface and in the bulk, the origin of the intensity variation stems from a higher proportion of the longer lifetime component near the perovskite surface. Overall, we suggest that this higher emission is caused by an increased probability of electron-hole recombination on Mn 2+ near the perovskite surface due to an increased trap concentration there. This observation suggests that such surface features have yet untapped potential to enhance emissive properties via control of surface-to-volume ratio.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2020

On Orbit Flight Testing of the Roll-Out Solar Array

The Roll-Out Solar Array (ROSA) is an innovative, lightweight solar array with a flexible substrate that makes use of the stored strain energy in its composite structural members to provide deployment without the use of motors while still packaging efficiently. The ROSA flight experiment was launched to the International Space Station (ISS)on June 3rd, 2017 as a part of the eleventh SpaceX commercial resupply mission. After two weeks of storage, ROSA was extracted from the Dragon spacecraft, deployed, and put through a week of tests to verify its structural characteristics as well as the performance of photovoltaics. The structural dynamics experiments included active excitation of out-of-plane bending modes, and a study of the thermal-structural interaction of the structure during day-night transitions. Data was gathered from a small number of accelerometers located at key points on the solar array and from cameras observing numerous photogrammetry targets spread out over the structure and the photovoltaic blanket. The goal in this effort was to better understand the performance of ROSA and to improve modeling efforts for future designs of similar solar arrays. Of particular interest are the first few system modes and mode shapes of the array, the amount of structural damping present, and degree of structural-thermal interaction seen during eclipse exit.

ROSA↗
DOE OSTI2025

Pathways for Sustainable Reaction Kinetics in Li-CO2 Batteries

Lithium-carbon dioxide (Li-CO2) batteries hold great promise for high-energy-density storage applications. However, advancing this technology as a sustainable alternative to Li-ion systems requires a deeper understanding of the underlying reaction mechanisms, which remain elusive. A key challenge stems from the added complexity introduced by the presence of oxygen (O2) in CO2 environment. In this study, we employed a stable Cu3(VBi)0.5Se4 mid-entropy catalyst and conducted a comprehensive investigation to uncover the underlying reaction mechanisms in Li-CO2 batteries under varying CO2/O2 ratios. Under pure CO2 conditions, the battery exhibits excellent rechargeability, sustaining up to 1200 cycles. However, at high current densities, the discharge potential drops significantly (below 2.0 V), primarily due to sluggish reaction kinetics caused by solid carbon formation. Interestingly, introducing O2 mitigates this limitation, leading to a 58% increase of the discharge potential (from 1.7 V to 2.7 V) at the high current density of 0.8 mA/cm2, signifying a substantial boost in energy output. Our results reveal that the reactions follow distinct pathways, shifting from surface- to solution-based mechanism, and may even exhibit coexistence of both mechanisms, depending on the CO2/O2 ratio. These findings offer new insights for designing high-performance and sustainable Li-gas batteries utilizing CO2 and O2 mixtures.

Ngo, Anh [University of illinois Chicago]↗
NASA NTRS2007

Simulation Studies of Forest Structure using 3D Lidar and Radar Models

The use of lidars and radars to measure forest structure attributes such as height and biomass are being considered for future Earth Observation missions. Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield information about the vertical profile of the canopy. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and is useful for estimating biomass. Interferometric SAR (InSAR) has been shown to yield forest canopy height information. For example, the height of scattering phase retrieved from InSAR data is considered to be correlated with the three height and the spatial structure of the forest stand. There is much interest in exploiting these technologies separately and together to get important information for carbon cycle and ecosystem science. More detailed information of the electromagnetic radiation interactions within forest canopies is needed. And backscattering models can be of much utility here. As part of a NASA funded project to explore data fusion, a three-dimensional (3D) coherent radar backscattering model and a 3D lidar backscatter models were used to investigate the use of large footprint lidar, SAR and InSAR for characterizing realistic forest scenes. For this paper, we use stem maps and other forest measurements to develop a realistic spatial structure of a spruce-hemlock forest canopy found in Maine, USA. The radar and lidar models used measurements of the 3D forest scene as input and simulated the coherent radar backscattering signature and 1064nm energy backscatter, respectively. The relationships of backscatter derived forest structure were compared with field measurements. In addition, we also had detailed airborne lidar (Laser Imaging Vegetation Sensor, LVIS) data available over the stem map sites that was used to study the accuracies of tree height derived from modeled SAR backscatter and the scattering phase center retrieved from the simulated InSAR data will be compared with the height indices, or other structure parameters derived from the lidar data. These results will address the possible synergies between lidar and radar in data in terms of forest structural information.

Sun, Guoqing↗