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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SIMS Analysis of d18O and d13C of Carbonate Cements in Shale & Mudstone. Final report

This project has had two primary goals: 1) improving new technology for in situ microanalysis of stable isotope ratios by SIMS (secondary ion mass spectrometry) and 2) evaluating the importance of in situ analysis for studies of carbonate cements within shales of the Bakken Petroleum System. The systematic relations of stable isotope ratios provide an important tool to help resolve critical questions in geology. Stable isotope analysis of carbonate cements in shale constrain many topics of interest to DOE including: CO2 sequestration, climate change, and the genesis and quality of rock reservoirs for petroleum, natural gas, and water. However, this evidence is often preserved as fine-scale zonation, which is homogenized by conventional bulk analysis of powders. Recently, analysis of ultra-small spots in polished samples at the University of Wisconsin WiscSIMS Lab. has documented stable isotope zoning in carbonates and other diagenetic cements at smaller scales than previously possible. We have made detailed studies of oxygen and carbon isotope ratios in diagenetic cements from shales of the Bakken Formation from the Williston basin and elsewhere. The Bakken contains both reservoir and source rocks for petroleum. Hydrofracturing has greatly enhanced production of oil in these tight reservoirs. The sediments contain zoned carbonate cements with growth textures that record multiple events. The growth of carbonate (dolomite) cements has been proposed to control reservoir quality, but previous stable isotope studies of homogenized powders could not resolve individual generations of cement and this proposal remains untested. Our better characterization of the multiple growth zones in these carbonates will aid in understanding the genesis of these tight reservoirs and the production of unconventional oil and gas. This study has also developed SIMS standards for analysis of all compositions of Ca-Mg-Fe carbonate and selected Mn-carbonates and hydromagnesite. We have refined techniques for improved accuracy of SIMS stable isotope analysis, and for sub-1-micron spot sizes. We have established protocols for mapping and correlating sample analyses at micron-scale using QGIS software.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2024

Single-Volume Scatter Camera (Final Report)

This document serves as a comprehensive final report for the Single-Volume Scatter Camera (SVSC) project. Most of the work over the course of this project has been documented in journal articles, conference papers, and other reports. We therefore reference those materials for detailed presentation of our technical results. The most recent efforts on the project have not been published and are presented in detail here. We present characterizations of two neutron scatter camera prototypes; one using a monolithic geometry, and one using an optically segmented geometry. Both detectors employ plastic scintillator with SiPM-based readout. For the monolithic prototype, we present calibrations of several detector parameters made using a set of dark counts. In particular, we employ a coincidence analysis to characterize the distribution external optical crosstalk, along with the relative timing of the different SiPMs. For the optically segmented prototype we present the results of calibrations made using a tagged 22 Na source, as well as the results of an imaging measurement made using a tagged AmBe source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Leveraging a Neural Network-Enhanced Reproducing Kernel Particle Method for Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation has been developed to analyze this system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. Here, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RKPM is additionally used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

degradation↗
DOE OSTI2025

Challenges in selecting appropriate electrodes for high-temperature molten salt systems

Based on a specific molten salt (e.g., chloride, fluoride, iodide) investigated, different working and reference electrode materials can be selected considering the chemical and thermal stability of the electrochemical cell components. In this talk, the electrode materials and challenges encountered with a spectro-electrochemical setup installed inside a glovebox, and the solutions implemented to address these challenges, specifically for the chloride and iodide molten salts will be presented. For molten chlorides, the fundamental interactions between neodymium chloride (NdCl3) and Nd metal in lithium chloride-potassium chloride eutectic salt were investigated at 773 K. The electrochemical transitions Nd2+,3+/Nd(s) were analyzed using an inert W electrode with cyclic voltammetry and chronoamperometry techniques, coupled with in-situ UV-Vis spectroscopy to elucidate the kinetic pathways of this disproportionation reaction (eq. 1). Nd(s) + NdCl3 = NdCl2 (1) For molten iodides, the challenges related to working electrode selectivity and present spectro-electrochemical results obtained from cyclic voltammetry measurements conducted at 673 K will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Measuring aerosol collection efficiency for the Bladewerx “New Speclon TM 5” and the older “Speclon TM 5” filter

Bladewerx TM LLC (Rio Rancho, NM) manufactures instrumentation, neutron shielding and activation foils for the radiation protection industry. Specializing in portable alpha/beta air monitors and sample counters, Bladewerx is the source of Speclon TM PTFE filter media that they recommend for high-resolution alpha spectroscopy. Los Alamos National Laboratory (LANL) utilizes Speclon TM filter material in CAM (Continuous Air Monitor) samplers for workplace air monitoring. The LANL Aerosol Engineering Facility received air filter material from Bladewerx, referred to as “New Speclon 5” in this document, in order to distinguish from filter material that was previously received (referred to as “Speclon 5” in this document). In this document, the aerosol collection efficiency and airflow resistance (pressure drop) were measured for the New Speclon 5 filter material.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Wet and dry plastic deposition data for western US National Atmospheric Deposition Program sites (2017-2019)

Raw plastic counts and calculated plastic deposition rates for 11 National Atmospheric Deposition Program (NADP) sites in the western USA recorded from 2017-2019. Samples were collected to determine plastic deposition rates in remote locations and identify the potential sources of plastic to the atmosphere. Samples were collected using an Aerochem Metrics Wet and Dry sampler. Wet deposition refers to the material retained on a 0.45-micron filter. Dry deposition refers to the dry only deposition collected using a Dry Side Insert (DSI) (Brahney et al. 2020). Plastics are identified as either fibers or particles (includes small colored films). Wet deposition rates are recorded weekly and dry plastic deposition rates are based on monthly sampling intervals. Sites included are Grand Canyon National Park (AZ03), Joshua Tree National Park (CA67), Rocky Mountain National Park (CO98), Niwot Ridge (CO02), Ashley National Forest (UT95), East River SFA (CO10)), Craters of the Moon National Park (ID03), Great Basin National Park (NV05), Canyonlands National Park (UT09), Bryce Canyon Nationa Park (UT99), and Wind River Range (WY06). Data collection is being published in collaboration with the Department of Energy's research project, "Constraining physical understanding of aerosol loading, biogeochemistry, and snowmelt hydrology from hillslope to watershed scale in the East River Scientific Focus Areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Statistical Distributions for Mesh Independent Solutions in ALEGRA

The representation of material heterogeneity (also referred to as "spatial variation") plays a key role in the material failure simulation method used in ALEGRA. ALEGRA is an arbitrary Lagrangian-Eulerian shock and multiphysics code developed at Sandia National Laboratories and contains several methods for incorporating spatial variation into simulations. A desirable property of a spatial variation method is that it should produce consistent stochastic behavior regardless of the mesh used (a property referred to as "mesh independence"). However, mesh dependence has been reported using the Weibull distribution with ALEGRA's spatial variation method. This report describes efforts towards providing additional insight into both the theory and numerical experiments investigating such mesh dependence. In particular, we have implemented a discrete minimum order statistic model with properties that are theoretically mesh independent.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Guidelines for Nuclear Structure Evaluators

This document sets forth the policies and procedures for preparing mass chain evaluations for the Evaluated Nuclear Structure Data File (ENSDF). Also included are some appendices which are referred to or augment material in the guidelines. See section on Appendices for details and references to additional material.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Leaf isoprene and monoterpene emission data-set across hyperdominant tree genera in the Amazon basin

This data package contains the analyzed data used to support the publication "Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin," Phytochemistry, in-press. Data was collected from 162 trees across four sites in the Amazon. For all leaf samples studied for volatile isoprenoid emissions, branch cuttings were conducted in the upper canopy with sun exposed leaves with the assistance of a tree climber utilizing a pole pruner or directly accessed from flux towers. Large branches were removed from the upper canopy (up to 0.5-1.0 meter in length) and rapidly recut on the ground under water to maintain the transpiration stream. Net photosynthesis and isoprene and monoterpene emission rates were quantified from leaves during controlled changes in photosynthetically active radiation (PAR) using a commercial leaf photosynthesis system (LI-6400XT, LI-COR Inc., USA) interfaced with a gas chromatograph-mass spectrometer (GC-MS, 5975C series, Agilent Technologies, USA). For detailed methods and raw data, refer to the publication and related material cited in Dataset References.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Raw leaf gas exchange data in the Amazon basin, 2014-2016

This data package contains raw leaf gas exchange data used to support the publication "Leaf isoprene and monoterpene emission distribution across hyperdominant tree genera in the Amazon basin," Phytochemistry, in-press. Data was collected from 162 individuals, distributed among 25 botanical families and 113 species, from four sites in the Amazon. The data was collected using a modified portable photosynthesis system for environmental control coupled to a thermal desorption tube for volatile isoprenoid collections. Collected TD tube samples were analysed in Manaus, Brazil, using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). The dataset includes both photosynthesis and isoprene/monoterpene emission rates from leaves under standard environmental conditions as well as controlled light response curves. For detailed methods and raw data, refer to the publication and related material cited in Dataset References.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Post-irradiation Examination Plan for the ORNL and University of California Santa Barbara Assessment of the UCSB ATR-2 Irradiation Experiment and a Reference Document for the Irradiated Archival RPV Materials Stored in the NSUF Nuclear Fuels and Materials Library

The Reactor Pressure Vessel task of the LWRS Program works with various organizations to obtain archival surveillance materials from commercial nuclear power plants to allow for comparisons of the irradiation-induced microstructural features from reactor surveillance materials with those from similar materials irradiated under high flux conditions in test reactors, such as the UCSB ATR-2 experiment. This report, originally submitted as a Level 3 Milestone M3LW-14OR0402012 – “Complete report on post-irradiation examination plan for ORNL and University of California Santa Barbara assessment of ATR-2 capsules,” has been expanded to providing a reference to access and / or perform characterization of irradiated archival RPV materials that were transferred to the Nuclear Science User Facility (NSUF), Nuclear Fuels and Materials Library (NFML).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

169 Tm(n,$\gamma$) cross section measured at DANCE

During the US nuclear testing program, known tracer materials could be loaded into the device prior to detonation. If those materials had activation products from nuclear reactions, they could be recovered and counted post-test to study how they transmuted during the neutron exposure. This information may be used to try to infer information about the physical conditions during the detonation. These materials are often referred to as “radiochemical detectors” or “radiochemical tracers”. Thulium, which has only one stable isotope, thulium-169, is one such material that may be employed as a detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Chemical and Radiological Compatibility Testing of 3D Printed Materials

To dramatically increase the adaptability, performance, and safety of processes in support of the Defense Waste Processing Facility (DWPF), Savannah River National Lab (SRNL) plans to perform chemical and radiological compatibility testing on a wide variety of 3D printed materials of interest. The 3D printing process provides numerous strategic operational benefits such as rapid prototyping of complex designs and geometry specific to the needs of the nuclear waste disposition process, as well as on-demand rapid prototyping and iteration with materials that aren’t as accessible through traditional manufacturing methods. Reaction chemistry in simulated waste batches can be matched closely to its radioactive counterpart, but glass reactor vessels have limitations. Vessel geometry can play a big factor in mixing transport limitations, process chemistry, and degradation reaction kinetics. In addition, additive manufacturing allows for much more detailed vessel design than traditional alternatives. Waste processing techniques in DWPF also encounter extreme chemical environments including high pH, strong acids, abrasive slurries, and significant irradiation. To meet these challenges, a matrix of various polymer, ceramic, and metal additive manufacturing materials have been exposed to a suite of chemical environments of interest as well as radioactive dose (such as gamma radiation from 60 Co) to properly test their durability under these conditions. Mass change has been monitored over a period of up to a week in these conditions, as well as added characterization for surface modification through Scanning Electron Microscopy/Electron Dispersive X-ray analysis (SEM/EDX). Further chemical characterization has been monitored through Fourier-Transform InfraRed Spectroscopy (FTIR), with planned investigation via thermal and tensile strength degradation. While the direct product of this research is identification of material(s) that can withstand specific hazardous environments encountered by the mercury water wash tank in DWPF process simulation experiments, the reference base of materials will be used for many other nuclear processes in the pursuit of rapidly developed, cost-efficient, and highly specific devices for environmental remediation and much more.

Wilson, Nathan W. [Savannah River National Laborat↗
DOE OSTI2023

Long-Term Stability of Mullite and Magnesia-encased Ag|Ag + Reference Electrodes in Molten MgCl 2 -KCl-NaCl

In this study, the stability of Ag|Ag + molten chloride reference electrodes was studied using mullite and magnesia tubes as reference electrode membrane materials in molten MgCl 2 -KCl-NaCl for continuous immersion up to 31 d. Two electrochemical methods were used to characterize the long-term performance of the reference electrodes at 500 °C in an inert atmosphere using a Mg rod as the working electrode: open circuit potential (OCP) and onset of Mg(II) reduction as measured by cyclic voltammetry (CV). There was only a 3% difference between the average OCP measured versus the mullite and MgO reference electrodes. Potential drift was higher for mullite (−1.34 mV d −1 ) than MgO (0.22 mV d −1 ). But both drift rates were very low compared to the OCP data standard deviation, indicating that no significant drift was measured for us to 31 d.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Material Frame: Hard Recoils from Slow Force Carriers

We modify the Standard Model by making the longitudinal component of the photon physical, propagating with small speed $c_L \ll 1$. This modification breaks gauge invariance and Lorentz symmetry, defining a preferred reference frame. No new fields or scales are introduced, and the photon mass is protected by a Galilean higher-form symmetry. The theory has a smooth $c_L\to0$ limit: the new modes decouple from standard matter and ordinary gauge theory predictions are recovered. Experimental constraints are severe. Charged particles Cherenkov-emit these slow modes, experiencing hard recoils against the preferred frame. The recoil rate decreases with $c_L$, but the momentum transfer remains of the order of the particle's momentum. Dark matter detectors, sensitive to keV-scale nuclear recoils, imply an order-of-magnitude bound $c_L \lesssim 10^{-60}$, tens of orders of magnitude stronger than speed-difference bounds. At such values, $c_L$ is better understood as a recoil-rate factor rather than a physically relevant speed. The slow modes, practically fixed in space, make the reference frame a material medium capable of absorbing momentum from charged particles.

Serra, Francesco [Johns Hopkins U.]↗
DOE OSTI2024

Analysis of nickel sulfoselenide materials by XPS

Metal chalcogenides are of interest as electrocatalysts, battery materials, and more. XPS is a valuable tool for studying changes to these materials before and after catalysis, making reference spectra for the pristine materials valuable. Here, we present XPS spectra for a family of nickel sulfoselenide (NiSSe) materials based on the Ni 3 X 2 crystal structure, Ni 3 S 2-x Se x . XPS surveys and high-resolution spectra of Ni 2p, S 2p, S 2s, Se 3d, Se 3p, and Se 3s were recorded using Al K α radiation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗