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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dl-3-n-butylphthalide promotes neurite outgrowth of primary cortical neurons by Sonic Hedgehog signaling via upregulating Gap43

Highlights: • NBP promoted neurite outgrowth in immature primary cortical neurons. • NBP increased axon and dendrite extension in mature primary cortical neurons. • NBP promoted neuritogenesis and neuronal plasticity via Shh signaling pathway. • The Shh signaling pathway increased Gap43 expression in primary cortical neuron. • NBP promoted neurite outgrowth by Shh signaling via upregulating Gap43 expression. Neurite outgrowth is the basis for wiring during the development of the nervous system. Dl-3-n-butylphthalide (NBP) has been recognized as a promising treatment to improve behavioral, neurological and cognitive outcomes in ischemic stroke. However, little is known about the effect and mechanism of NBP on the neurite outgrowth. In this study, we used different methods to investigate the potential effects of NBP on the neurite extension and plasticity of immature and mature primary cortical neurons and explored the underlying mechanisms. Our results demonstrated that in immature and mature cortical neurons, NBP promoted the neurite length and intersections, increased neuritic arborization, elevated numbers of neurite branch and terminal points and improved neurite complexity and plasticity of neuronal development processes. Besides, our data revealed that NBP promoted neurite extension and branching partly by activating Shh signaling pathway via increasing Gap43 expression both in immature and mature primary cortical neurons. The present study provided new insights into the contribution of NBP in neuronal plasticity and unveiled a novel pathway to induce Gap43 expression in primary cortical neurons.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Redox Behaviors in Li-Excess Cation-Disordered Mn-Nb-O-F Rocksalt Cathode

Lithium-excess cation-disordered rocksalt oxide (DRX) is a new choice of high energy Li-ion cathode materials. DRX cathode can deliver an exceptionally high capacity of >250 mAh/g, implying the participation of cationic transition metal and anionic oxygen redox in the electrochemistry. Understanding the explicit roles of both redox reactions in the newly developed cathode is of critical importance to further development of these materials. Herein, we synthesize a representative Mn-redox-based fluorinated DRX material, Li1.2Mn0.625Nb0.175O1.95F0.05 (LMNOF). Using a comprehensive suite of electroanalytical methods, we probe the cationic and anionic redox processes and their evolution upon cycling exclusively from the electrochemical point of view. This work sheds light on understanding of cationic and anionic redox and their roles in the capacity loss for high-capacity fluorinated DRX cathode, meanwhile, showcases an explicit approach to study the electrochemistry of novel electrode materials using such non-disruptive electroanalytical methods.

Li-ion battery, high-capacity cathode, Li-excess m↗
DOE OSTI2020

Selecting Adsorbents to Separate Diverse Near-Azeotropic Chemicals

Industrial separations of near-azeotropic chemicals, species with very similar boiling points, are energy- and capital-intensive. Adsorption-based processes can energy-efficiently separate near-azeotropic mixtures provided suitable adsorbent materials can be found. Among the full diversity of industry-relevant molecules, millions of these mixtures exist, meaning that discovery of mixture-specific adsorbents by direct experiment is infeasible. We show that vast numbers of adsorbents and adsorbing molecules can be explored in a powerful way by coupling atomistic simulations with machine learning. This concept is demonstrated by describing the adsorption of ~54000 industry-relevant chemicals in an experimentally derived set of thousands of metal–organic framework materials. Here, our results identify thousands of near-azeotropic mixtures that can be efficiently separated using adsorption and open possibilities for creating adsorption processes for complex mixtures with many components.

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

Low Melting Temperature Gallium–Indium Liquid Metal Anode for Solid-State Li-Ion Batteries

Solid-state Li-ion batteries are attracting attention for their enhanced safety features, higher energy density, and broader operational temperature range compared to systems based on liquid electrolytes. However, current solid-state Li-ion batteries face performance challenges, such as suboptimal cycling and poor rate capabilities, often due to inadequate interfacial contact between the solid electrolyte and electrodes. To address this issue, we incorporated a gallium–indium (Ga–In) liquid metal as the anode in a solid-state Li-ion battery setup, employing Li 6 PS 5 Cl as the solid electrolyte. Operating at room temperature, this configuration achieved an initial capacity of 389 mAh g –1 and maintained 88% of this capacity after 30 cycles at a 0.05 C rate. It also demonstrated a capacity retention of 66% after 500 cycles at a 0.5 C rate. In comparison to solid anode materials, such as tin, the Ga–In liquid metal exhibited superior cycling stability and rate capacity, which is due to the self-healing and fluid properties of the alloy that ensure stable interfacial contact with solid electrolytes. In situ X-ray diffraction (XRD) and ex situ scanning electron microscope (SEM) analyses revealed that indium does not directly participate in the lithiation/delithiation process. Instead, it helps maintain the alloy’s low melting point, facilitating its return to a liquid state after delithiation. In a comparative analysis of stack pressure during cycling in cells utilizing Ga–In liquid metal and tin, the Ga–In liquid metal cell demonstrated an ability to buffer pressure increases associated with deformation. In conclusion, these findings suggest a promising approach for enhancing solid-state batteries by integrating liquid metal anodes, which improve interfacial contact and stability.

Alloys↗
DOE OSTI2020

Establishing structure-sensitivity of ceria reducibility: real-time observations of surface-hydrogen interactions

The first layer of atoms on an oxide catalyst provides the first sites for adsorption of reactants and the last sites before products or oxygen are desorbed. We employ a unique combination of morphological, structural, and chemical analyses of a model ceria catalyst with different surface terminations under an H 2 environment to unequivocally establish the effect of the last layer of atoms on surface reduction. (111) and (100) terminated epitaxial islands of ceria are simultaneously studied in situ allowing for a direct investigation of the structure–reducibility relationship under identical conditions. Kinetic rate constants of Ce 4+ to Ce 3+ transformation and equilibrium concentrations are extracted for both surface terminations. Unlike the kinetic rate constants, which are practically the same for both types of islands, more pronounced oxygen release, and overall higher reducibility were observed for (100) islands compared to (111) ones. The findings are in agreement with coordination-limited oxygen vacancy formation energies calculated by density functional theory. The results point out the important aspect of surface terminations in redox processes, with particular impact on the catalytic reactions of a variety of catalysts.

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

Impact of the newly revised gravitational redshift of x-ray burster GS 1826-24 on the equation of state of supradense neutron-rich matter

Thanks to the recent advancement in producing rare isotopes and measuring their masses with unprecedented precision, the updated nuclear masses around the waiting-point nucleus 64 Ge in the rapid-proton capture process have led to a significant revision of the surface gravitational redshift of the neutron star (NS) in GS 1826-24 by refitting its x-ray burst light curve using Modules for Experiments in Stellar Astrophysics (MESA). The resulting NS compactness ξ is between 0.183 and 0.259 at 95% confidence level, and its upper boundary is significantly smaller than the maximum ξ previously known. Incorporating these new data within a comprehensive Bayesian statistical framework, we investigate its impact on the Equation of State (EOS) of supradense neutron-rich matter and the required spin frequency for GW190814’s minor m 2 with mass 2.59 ± 0.05⁢M ⊙ to be a rotationally stable pulsar. We found that the EOS of high-density symmetric nuclear matter (SNM) has to be softened significantly while the symmetry energy at supersaturation densities stiffened compared to our prior knowledge from earlier analyses using data from both astrophysical observations and terrestrial nuclear experiments. In particular, the skewness J 0 characterizing the stiffness of high-density symmetric nuclear matter (SNM) decreases significantly, while the slope L, curvature K sym , and skewness Jsym of nuclear symmetry energy all increase appreciably compared to their fiducial values. Here, we also found that the most probable spin rate for the m 2 to be a stable pulsar is very close to its mass-shedding limit once the revised redshift data from GS 1826-24 is considered, making the m 2 unlikely the most massive NS observed so far.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Robust Containment Queries over Collections of Trimmed NURBS Surfaces via Generalized Winding Numbers

Here, we propose a containment query that is robust to the watertightness of regions bound by trimmed NURBS surfaces, as this property is difficult to guarantee for in-the-wild CAD models. Containment is determined through the generalized winding number (GWN), a mathematical construction that is indifferent to the arrangement of surfaces in the shape. Applying contemporary techniques for the 3D GWN to trimmed NURBS surfaces requires some form of geometric discretization, introducing computational inefficiency to the algorithm and even risking containment misclassifications near the surface. In contrast, our proposed method leverages properties of the 3D solid angle to solve the relevant surface integral using a boundary formulation with rapidly converging adaptive quadrature. Batches of queries are further accelerated by memoizing (i.e., caching and reusing) quadrature node positions and tangents as they are evaluated. We demonstrate that our GWN method is robust to complex trimming geometry in a CAD model, and is accurate up to arbitrary precision at arbitrary distances from the surface. The derived containment query is therefore robust to model non-watertightness while respecting all curved features of the input shape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Impact of Nickel Ions on the Oxygen Reduction Reaction Kinetics of Pt and on Oxygen Diffusion through Ionomer Thin Films

The effects of dissolved nickel on the oxygen reduction reaction (ORR) kinetics and oxygen transport properties of perfluorosulfonic acid (PFSA) thin films were investigated using rotating disk electrode (RDE) measurements of ORR on a PFSA-coated platinum electrode. The electrochemical characterization in 0.1 M perchloric acid (HClO 4 ) with and without added Ni 2+ quantitatively measured the impact of ionic interactions between the Ni 2+ cations and sulfonate (SO 3 - ) anions on oxygen transport through the PFSA thin film. Cyclic voltammetry (CV) curves in deaerated electrolyte showed that Ni 2+ cations diffusing through the PFSA thin film interact with the Pt surface altering the hydrogen underpotential deposition and stripping processes and decreasing ORR kinetics. The RDE limiting current results point to reduced permeability of oxygen through PFSA-Ni 2+ compared to PFSA-H + . Furthermore, the results indicate that transition metals leached from Pt alloy catalyst may be detrimental not only to the intrinsic ORR kinetics of the PEFC cathode catalyst through loss of the ORR-enhancing transition metal, but may also inhibit the diffusion of oxygen to the catalytic sites and poison the ORR.

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

Onslow Beach Washover Fan Morphology from 2012 to 2015

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.These grid files were created from data collected using a Riegl 3-D laser scanner. Millions of x, y, and z points from the F2 Washover Fan on Onslow Beach were processed using the MARS software package to define a bare-earth model. Grid files were imported into Golden Software Surfer version 19 for editing and exported from that application as .grd files. Files can be opened in Surfer or ArcMap, but the coordinate system information will be lost if opened in ArcMap. These data were collected to quantify the morphological changes that occur on a washover fan through time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗
DOE OSTI2020

GoldSim E-Area Low-Level Waste Facility Aquifer Zone Model Calibration Methodology

This report documents the development and calibration of the E-Area Low-Level Waste Facility (ELLWF) Gold Sim aquifer model. It provides a methodology on how a Gold Sim aquifer model can be calibrated to specific PORFLOW-based aquifer predictions. The calibration activity presented within this report focuses on the Slit Trench #06 (ST06) location that resides within the center set of Slit Trenches. This Gold Sim-based aquifer model is a generic model capable of being calibrated to any of the other trench locations within E-Area. In addition, subsequent activities (beyond the scope of this effort) will couple this GoldSim-based aquifer model to various GoldSim-based trench models, with the intent of performing stochastic analyses that couple all pertinent fate and transport processes from the ground surface up to the 100-m point of assessment (POA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

GoldSim E-Area Low-Level Waste Lacility Vadose Zone Model Benchmarking

This report documents the development and benchmarking of the E-Area Low-Level Waste Facility (ELLWF) GoldSim Engineered and Slit Trench (ET and ST) vadose zone models. Subsequent activities (beyond the scope of this effort) will couple the GoldSim-based vadose zone models to the GoldSim aquifer model, with the intent of performing stochastic analyses that couple all pertinent fate and transport processes from the ground surface up to the 100-m Point of Assessment (POA). The benchmarking presented within this report focuses on the Slit Trench 06 (ST06) bydrostratigraphic location that resides within the center set of slit trenches. These GoldSim-based vadose zone models are generic models capable of being benchmarked to any of the other trench locations within E-Area.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Proton Tunable Analog Transistor for Low Power Computing

This project was broadly motivated by the need for new hardware that can process information such as images and sounds right at the point of where the information is sensed (e.g. edge computing). The project was further motivated by recent discoveries by group demonstrating that while certain organic polymer blends can be used to fabricate elements of such hardware, the need to mix ionic and electronic conducting phases imposed limits on performance, dimensional scalability and the degree of fundamental understanding of how such devices operated. As an alternative to blended polymers containing distinct ionic and electronic conducting phases, in this LDRD project we have discovered that a family of mixed valence coordination compounds called Prussian blue analogue (PBAs), with an open framework structure and ability to conduct both ionic and electronic charge, can be used for inkjet-printed flexible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. Retention of programmed states is improved by nearly two orders of magnitude compared to the extensively studied organic polymers, thus enabling in-memory compute and avoiding energy costly off-chip access during training. We demonstrate dopamine detection using PBA synapses and biocompatibility with living neurons, evoking prospective application for brain - computer interfacing. By application of electron transfer theory to in-situ spectroscopic probing of intervalence charge transfer, we elucidate a switching mechanism whereby the degree of mixed valency between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by density functional theory (DFT) .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Advancing Electric System Resilience with Distributed Energy Resources: Key Questions and Resources

This resource has two complementary parts: (1) A list of questions that offers an initial starting point for state public utility commissions (commissions) to frame how they review proposed utility investments and considerations that could offer resilience benefits; (2) A list of relevant resources to improve a regulator's ability to oversee resilience investments and obtain the best possible solutions for customers. The list of resources includes a synopsis of relevant topics covered in each resource. This document is not intended to offer a complete picture of resilience literature, but instead suggests strategies for state regulators to convene conversations and make decisions to achieve better resilience outcomes for customers. It is meant to serve as a starting point for commissions to understand and incorporate resilience into regulatory processes. The list of questions and resources will not be perfectly suited to the particular needs of each commission. As the resilience conversation advances, regulators will need to take advantage of available resources to build their capacity to assess resilience risks, compare investment options, and evaluate performance.

14 SOLAR ENERGY↗
DOE OSTI2025

Defect Detection Model Development for Large Scale Thermoplastic Printing

Large-format additive manufacturing (LFAM) offers several advantages, including high throughput, cost-effective pellet-fed extrusion, and the capability to produce large-scale structures. The main pain points of LFAM include start and stops during the printing process, warpage, long layer times that lead to bead freezing, and bead separation due to shrinkage. These issues can lead to overfill, underfill and buildup of material in different sections of a print. This can lead to hidden defects embedded within the printed layers, or even ultimate failure of the printed structure. This ensures these defects can only be identified through nondestructive testing (NDT) inspection methods after printing, which can be timely and costly. Aligned Vision work specializes in 2D projectors with visual inspection systems and machine learning. Traditionally system is used for composite layup and layup inspections. In this work we used the LFAM system at Oak Ridge National Laboratory to create defect rich samples. The Aligned Vision inspection system then performed in-situ monitoring of the print process after each part was printed. This in-situ vision inspection system was used to develop a layer-by-layer inspection model that looks for overfill, underfill, and the buildup of defects using only a camera-based vision system. This leads to the assurance of high-quality production components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Designing Recyclable Biomass-Based Polyesters (Final Technical Report)

This project successfully demonstrated the production of sustainable polyesters from biomass-derived monomers, offering properties on par with or superior to fossil-based plastics such as LLDPE and PBAT. Using renewable chemical platforms like furfural and HMF, we synthesized over eight novel monomers and nearly 100 aliphatic-aromatic polyesters. Among these, PPeAT and PDDF emerged as highly promising candidates for flexible packaging applications, exhibiting excellent mechanical performance, tunable thermal properties, and enhanced barrier characteristics. Key advances included the development of ring-opening polymerization strategies using cyclic monomer intermediates to produce high molecular weight materials with excellent control. The resulting polymers achieved biobased content of at least 44 wt.%. We also implemented chemical recycling via catalytic methanolysis, recovering over 90% of monomers from PPeAT at semi-pilot scale. This supports a circular economy approach by enabling material reuse without performance loss. Techno-economic and life cycle assessments confirmed that these polyesters can reduce greenhouse gas emissions by up to 50% compared to petroleum-derived alternatives. Favorable mechanical properties may further reduce material demand, and cost competitiveness was demonstrated under specific market conditions. Feedstock cost and environmental footprint were identified as primary levers for future optimization. In summary, the project met or closely approached all technical targets, including biodegradability, strength, and processing compatibility. While minor issues such as color and melting point variation remain, the results strongly support continued development and scale-up of these sustainable materials.

09 BIOMASS FUELS↗
DOE OSTI2019

Application and Evaluation of Surrogate Models for Radiation Source Search

Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous derivatives preclude the use of gradient-based optimization or data assimilation algorithms. We consider the problem of inferring the 2D location and intensity of a radiation source in an urban environment using a ray-tracing model based on Boltzmann transport theory. Whereas the code implementing this model is relatively efficient, extension to 3D Monte Carlo transport simulations precludes subsequent Bayesian inference to infer source locations, which typically requires thousands to millions of simulations. Additionally, the resulting likelihood exhibits discontinuous derivatives due to the presence of buildings. To address these issues, we discuss the construction of surrogate models for optimization, Bayesian inference, and uncertainty propagation. Specifically, we consider surrogate models based on Legendre polynomials, multivariate adaptive regression splines, radial basis functions, Gaussian processes, and neural networks. We detail strategies for computing training points and discuss the merits and deficits of each method.

Cook, Jared A.↗