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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthesizing Highly Crystalline Graphite Powder from Bulk Polyethylene Waste for Lithium-Ion Battery Anodes

Upcycling plastic waste into graphite can potentially be used, in conjunction with other methods, to manage existing waste materials and diversify graphite supply chains. However, synthesizing large quantities of crystalline graphite powder from plastic waste, particularly polyethylene (PE), remains a challenge because PE decomposes into light gases during thermal processing and simple methods do not exist at any appreciable size scale to address this challenge. In this work, a method is developed for air processing bulk forms of PE waste to create stable carbon char that does not readily decompose during high-temperature processing. This method employs solid additives in the form of salts, which are combined with the PE melt during air processing to increase the effective surface area of the melt and improve the oxygen-driven chemistry that stabilizes PE for high-temperature processing. After removal of the solid salt additives from the PE-derived char, it is converted into a highly crystalline bulk graphite powder using an Fe-based catalytic process. The PE-derived graphite anode in a lithium-ion coin cell showed a specific capacity of 345 mAh/g at 0.05C with an initial Coulombic efficiency of 87% and reversible capacity retention of ~100% at different current rates. It also showed a specific capacity of up to 313 mAh/g at 0.5 discharge/charge cycles per hour (0.5C) and Coulombic efficiency of 99.9% after 250 cycles, indicating excellent electrochemical performance as an anode material for lithium-ion batteries. This method illustrates that there are opportunities for upcycling large quantities of PE waste to produce graphite powders suitable for use in LIBs.

25 ENERGY STORAGE↗
DOE OSTI2021

Nanoparticle Assembly Induced Ligand Interactions for Enhanced Electrocatalytic CO 2 Conversion

The microenvironment in which the catalysts are situated is as important as the active sites in determining the overall catalytic performance. Recently, it has been found that nanoparticle (NP) surface ligands can actively participate in creating a favorable catalytic microenvironment, as part of the nanoparticle/ordered-ligand interlayer (NOLI), for selective CO 2 conversion. However, much of the ligand–ligand interactions presumed essential to the formation of such a catalytic interlayer remains to be understood. In this study, by varying the initial size of NPs and utilizing spectroscopic and electrochemical techniques, we show that the assembly of NPs leads to the necessary ligand interactions for the NOLI formation. The large surface curvature of small NPs promotes strong noncovalent interactions between ligands of adjacent NPs through ligand interdigitation. This ensures their collective behavior in electrochemical conditions and gives rise to the structurally ordered ligand layer of the NOLI. Thus, the use of smaller NPs was shown to result in a greater catalytically effective NOLI area associated with desolvated cations and electrostatic stabilization of intermediates, leading to the enhancement of intrinsic CO 2 -to-CO turnover. Our findings highlight the potential use of tailored microenvironments for NP catalysis by controlling its surface ligand interactions.

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

Clouds and Radiation Processes in Regional Climate Models Evaluated Using Observations Over the Ice‐free Arctic Ocean

Abstract The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea‐ice surface and the ice‐free ocean. Following several previous field campaigns, the cloud‐radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea‐ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice‐free areas. Using an in situ stationary meteorological observation data set obtained over the ice‐free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low‐level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single‐ and double‐moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower‐tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice‐free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand‐alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air‐ice‐sea coupled system.

Inoue, Jun↗
DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗
DOE OSTI2020

Toroidal modeling of runaway electron loss due to 3-D fields in DIII-D and COMPASS

The 3-D field induced relativistic runaway electron (RE) loss has been simulated for DIII-D, COMPASS and ITER plasmas, utilizing the MARS-F code incorporated with the recently developed and updated RE orbit module (REORBIT). Modeling shows effectively 100% loss of a post-disruption, high-current runaway beam in DIII-D, due to the 1 kG level of magnetic field perturbation produced by a fast growing n = 1 resistive kink instability. The RE loss is shown to be independent of the particle energy or the initial location of particles in the configuration space. Applied resonant magnetic perturbation (RMP) fields from in-vessel coils are not effective for RE beam mitigation in DIII-D, but do produce finite (>10%) RE loss in COMPASS, consistent with experimental observations in above two devices. The major reasons for this difference in RE control by RMP between these two devices are (i) the coil proximity to the RE beam and (ii) the effective coil current scaling versus the machine size and the toroidal magnetic field. About 10% RE loss fraction is also predicted for an ITER 15 MA scenario with pre-disruption plasma, highlighting the role of the plasma response. Up to 30% loss is computed, however, by artificially scaling the equilibrium pressure to zero. This is due to the more resistive plasma response and stronger resulting field line stochasticity. Distributions of the lost REs to the limiting surface show poloidally peaked profile near the high-field-side in both DIII-D and COMPASS, covering about 100o poloidal angle. Higher perturbation field level and/or higher particle energy also result in REs being lost to the low-field-side of the limiting surface of these two devices, increasing the effective wetted area. Finally, for the modeled ITER plasmas, the applied RMP field, with optimal poloidal spectrum that maximizes the edge localized mode control, leads to REs being lost to the lower divertor region of the limiting surface within a narrow poloidal band.

3-D field↗
DOE OSTI2020

Seven-core fibre Raman laser with intercore coupling

This paper reports results of a study aimed at producing a Raman fibre laser based on a multicore fibre with high-reflectivity fibre Bragg gratings inscribed in its peripheral cores using femtosecond laser pulses. We present spectral and power characteristics of a Raman laser whose output power at a wavelength of 1090 nm is 2.5 W. The laser emission linewidth has been shown to decrease as a result of the reduction in nonlinear effects owing to the larger effective mode area in the multicore fibre in comparison with a standard single-mode fibre Raman laser. (paper)

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of activation temperature on quantum efficiency and lifetime of NEA truncated nanocone array GaAs photocathode

This study investigates the quantum efficiency (QE) and operational lifetime of a negative electron affinity GaAs truncated nanocone array (TNCA) photocathode benchmarked against a conventional flat GaAs photocathode under varying activation temperatures. The TNCA structure demonstrated a QE of up to 13.6% at 590 nm with room temperature (RT) activation—approximately 1.5 times higher than its flat counterpart. This enhancement is due to Mie resonance effects within the nanostructure, as confirmed by finite-difference time-domain simulations. Moreover, the TNCA photocathode exhibits significantly extended charge lifetime, with enhancement factors of ∼6.1 and ∼19.8 under RT and 50 °C activations, respectively. These gains are primarily attributed to increased effective surface area and optimized dipole layer formation at elevated temperatures. In addition, shorter excitation wavelengths further contribute to lifetime improvements. These findings underscore the TNCA GaAs photocathode’s potential as a high QE, long lifetime electron source for many large-scale electron accelerators.

Cs-NF3 activation↗
DOE OSTI2023

Plasma surface ionization wave interactions with single channels

Abstract The study of plasma surface ionization waves (SIWs) in recent years has primarily focused on planar surfaces and periodic two dimensional structures. In application, substrates are likely to have non-planar morphology such as cracks, pores, and steps. Additionally, targets for the applications of medicine or catalysis may have targets with heterogeneous composition. This classification of targets are brought under the umbrella of complex interfaces. In this work, plasma SIWs were incident on a complex target consisting of a single channel cut into glass slides. The SIW velocities for the in-channel portion of the wave and radially propagating portion of the wave were tracked. It was found that surface wave velocities are not significantly affected by channel geometry, but primarily increase with pulse energy. A third propagation direction for the SIW is characterized in the azimuthal direction relative to the radial portion of the wave. Channel geometry is found to greatly effect the area treated by the plasma but not the propagation velocity of the surface wave. Surface wave morphology and the impact on application is also discussed. A simple model was introduced to understand the mechanisms behind SIW escape from a channel. It was found that the ratio of pulse energy to a geometry dependent minimum energy can predict the escape angle of a SIW from single channels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Time-of-flight methodologies with large-area diamond detectors for the effectively characterization of tens MeV protons

A novel detector based on a polycrystalline diamond sensor is here employed in an advanced time-of-flight scheme for the characterization of energetic ions accelerated during laser-matter interactions. The optimization of the detector and of the advanced TOF methodology allow to obtain signals characterized by high signal-to-noise ratio and high dynamic range even in the most challenging experimental environments, where the interaction of high-intensity laser pulses with matter leads to effective ion acceleration, but also to the generation of strong Electromagnetic Pulses (EMPs) with intensities up to the MV/m order. These are known to be a serious threat for the fielded diagnostic systems. Here we report on the measurement performed with the PW-class laser system Vega 3 at CLPU (~30 J energy, ~10 21 W/cm 2 intensity, ~30 fs pulses) irradiating solid targets, where both tens of MeV ions and intense EMP fields were generated. The data were analyzed to retrieve a calibrated proton spectrum and in particular we focus on the analysis of the most energetic portion (E > 5.8 MeV) of the spectrum showing a procedure to deal with the intrinsic lower sensitivity of the detector in the mentioned spectral-range.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Astrometry in two-photon interferometry using an Earth rotation fringe scan

Optical interferometers may not require a phase-stable optical link between the stations if instead sources of quantum-mechanically entangled pairs could be provided to them, enabling long baselines. We developed a new variation of this idea, proposing that photons from two different astronomical sources could be interfered at two decoupled stations. Interference products can then be calculated in post-processing or requiring only a slow, classical connection between stations. In this work, we investigated practical feasibility of this approach. We developed a Bayesian analysis method for the earth rotation fringe scanning technique and showed that in the limit of high signal-to-noise ratio it reproduced the results from a simple Fisher matrix analysis. Here we identify candidate stair pairs in the northern hemisphere, where this technique could be applied. With two telescopes with an effective collecting area of ~ 2 m 2 , we could detect fringing and measure the astrometric separation of the sources at ~100 μas precision in a few hours of observations, in agreement with previous estimates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2021

Towards replacing physical testing of granular materials with a Topology-based Model

In the study of packed granular materials, the performance of a sample (e.g., the detonation of a high-energy explosive) often correlates to measurements of a fluid flowing through it. The “effective surface area,” the surface area accessible to the airflow, is typically measured using a permeametry apparatus that relates the flow conductance to the permeable surface area via the Carman-Kozeny equation. This equation allows calculating the flow rate of a fluid flowing through the granules packed in the sample for a given pressure drop. However, Carman-Kozeny makes inherent assumptions about tunnel shapes and flow paths that may not accurately hold in situations where the particles possess a wide distribution in shapes, sizes, and aspect ratios, as is true with many powdered systems of technological and commercial interest. To address this challenge, we replicate these measurements virtually on micro-CT images of the powdered material, introducing a new Pore Network Model based on the skeleton of the Morse-Smale complex. Pores are identified as basins of the complex, their incidence encodes adjacency, and the conductivity of the capillary between them is computed from the cross-section at their interface. We build and solve a resistive network to compute an approximate laminar fluid flow through the pore structure. Here, we provide two means of estimating flow-permeable surface area: (i) by direct computation of conductivity, and (ii) by identifying dead-ends in the flow coupled with isosurface extraction and the application of the Carman-Kozeny equation, with the aim of establishing consistency over a range of particle shapes, sizes, porosity levels, and void distribution patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2023

GT2023 Front Matter

Abstract The front matter for this proceedings is available by clicking on the PDF icon.

08 HYDROGEN↗
DOE OSTI2025

Anomalous electroweak physics unraveled via evidential deep learning

The ever-growing ecosystem of beyond standard model (BSM) calculations and parametrizations has motivated the development of systematic methods for making quantitative cross-comparisons over the wide range of possible models, especially with controllable uncertainties. In this setting, the language of uncertainty quantification (UQ) furnishes useful metrics for assessing statistical overlaps and discrepancies among BSM and related models. In this study, we leverage recent machine learning (ML) developments in evidential deep learning (EDL) for UQ to separate data (aleatoric) and knowledge (epistemic) uncertainties in a model-discrimination setting. We construct several potentially BSM-motivated scenarios for the anomalous electroweak interaction (AEWI) of neutrinos with nucleons in deep inelastic scattering ( v DIS). These scenarios are then quantitatively mapped, as a demonstration, alongside Monte Carlo replicas of the CT18 PDFs used to calculate the $\varDelta \chi ^{2}$ statistic for a typical multi-GeV v DIS experiment, CDHSW. Our framework effectively highlights areas of model agreement and provides a classification of out-of-distribution (OOD) samples. By offering the opportunity to quantitatively understand model overlaps, the approach presented in this work can help facilitate efficient BSM model exploration and exclusion for future New Physics searches.

AI↗
DOE OSTI2020

Empirical Validation of Multi-Zone HVAC System Model: Evaluation of Existing Infiltration Models used in Building Energy Simulation

Infiltration can have a significant impact on building loads. Studies have shown that infiltration can account for 15-40% of annual space conditioning needs in commercial buildings (Emmerich et al. 2019; Younes et al. 2012). The driving force of infiltration is the pressure difference across the building envelope caused by wind, the stack effect (known as buoyancy effect), and the operation of ventilation equipment. Wind pressure is governed by wind direction, speed, building shape, and other structures around the building. The stack effect is a function of the building height and air density differences of ambient air (Han, 2015). The effect of wind is dominant in low-rise residential buildings, and the stack effect is dominant in highrise buildings (ASHRAE 2017). In building energy simulation programs (e.g., EnergyPlus), various empirical infiltration models (e.g., the effective leakage area model, the flow coefficient model) are available to simulate infiltration rates. To help users in selecting a proper infiltration model for modeling of the two-story Flexible Research Platform (FRP), the team evaluates the existing infiltration models in EnergyPlus based on field measurements from the FRP. The blower door and tracer gas decay tests were performed in the FRP. The blower door test result was used to estimate input parameters required in the infiltration models. The actual infiltration rates were estimated with the tracer gas decay test results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Fluorinated Covalent Organic Frameworks: A Novel Pathway to Enhance Hydrogen Sorption and Control Isosteric Heats of Adsorption; HyMARC Seed Project Final Report

Organic framework materials, as a unique sub-class of carbon-based sorbents, have gained increasing attention for promising attributes toward gas storage. Calculations of the hydrogen capacity of optimized frameworks show potential to achieve greater than 60 g/L storage of hydrogen, placing metal-organic frameworks (MOFs) and COFs near the top of the class of porous materials. However, at the ensemble level, poor stacking creates a quasi-amorphous material with low structural integrity and low effective surface area. The chemical versatility of COFs allows for additional methods for producing long-range order that specifically target the inter-layer interactions in COFs but that leave key pore-accessible linker sites open. These modifications (either during synthesis or post-synthetic) enable a host of strategies to both improve crystalline order for more stable and higher surface, as well as add metals with open coordination for enhanced H 2 binding enthalpy.

08 HYDROGEN↗