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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Generalizable Porous Aromatic Framework‐Included Polymer Membranes for Diffusion‐Enhanced Gas Separations

Industrial separation processes account for 10-15% of global energy consumption. Membrane-based processes are less energy-intensive than traditional gas separation technologies; however, enhanced material separation performance and stability for numerous gas mixtures are needed for widespread industrial adoption. This work presents a generalizable strategy for preparing mixed-matrix gas separation membranes exceeding the performance upper bounds of existing polymer membranes for a wide variety of industrial gases. By incorporating robust porous aromatic framework (PAF) particles into various dense commercial polymer matrices, gas diffusivity and solubility can be enhanced. For diverse gas mixtures (e.g., CO2/N2, O2/N2, He/CH4, H2/N2, and C2H4/C2H6), the resulting composite membranes exhibit enhanced gas permeabilities-by as much as 520%-and largely unchanged selectivities even after 6 years of aging under simulated flue gas conditions. These improvements arise from the ultrahigh porosity, excellent chemical compatibility, and unique physicochemical properties of the embedded PAF particles. Functionalizing the PAFs with polyamines also enables composite membranes that achieve among the highest reported performances against plasticization, a common obstacle in commercializing gas separation membranes. Significantly, the PAF-1 particles are readily dispersible in various common membrane casting solvents, suggesting their broader utility as a filler for designing high-performance membranes for many industrial gas separations.

Uliana, Adam A↗
DOE OSTI2024

Uncertainty-aware particle segmentation for electron microscopy at varied length scales

Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Models of ultraheavy dark matter visible to macroscopic mechanical sensing arrays

In recent years, the sensitivity of optomechanical force sensors has improved leading to increased interest in using these devices as particle detectors. In this study we consider scenarios where dark matter with mass close to the Planck scale may be probed by a large array of optomechanical accelerometers. We motivate a macroscopic mechanical search for ultraheavy dark matter, exemplified by the efforts of the Windchime Collaboration, by providing a survey of the model space that would be visible to such a search. We consider two classes of models, one that invokes a new long-range unscreened force and another that is only gravitationally interacting. We identify significant regions of well-motivated, potentially visible parameter space for versatile models such as Q-balls, composite dark matter, relics of gravitational singularities, and gravitationally produced ultraheavy particles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Strength mechanisms and tunability in Al-Ce-Mg ternary alloys enabled by additive manufacturing

Al-Ce-based alloys are promising candidates for additive manufacturing (AM) due to their hot-cracking resistance and because they do not require heat treatment to obtain precipitation strengthening. Rapid solidification rates enabled by AM methods can lead to enhanced mechanical properties; however, the strengthening mechanisms over large composition ranges were unclear. Here, combinatorial synthesis by directed-energy deposition (DED) and hardness measurements were used to rapidly map the composition-dependent strength of the ternary Al-Ce-Mg system. Tensile testing and microstructure characterization of selected compositions were performed to elucidate the compositional dependence of the strengthening mechanisms. Al 11 Ce 3 precipitates were present in all cases, and the maximum hardness (1.25 GPa) was measured for the Al-8Ce-10Mg composition. A combination of (i) Hall-Petch strengthening, based on the FCC-matrix-phase cell size; (ii) particle strengthening, based on Al 11 Ce 3 volume fraction and size; and (iii) solid-solution strengthening, based on Mg composition of the matrix phase, were used to account for the measured strengths. Vickers hardness is shown to correlate well with ultimate tensile strength in these alloys, highlighting the value of surface-based techniques for rapid screening.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hardness Measurements and Interface Behavior of SiC-B 4 C-Si Multiple Phase Particulate Composites Made with Melt Infiltration and Additive Manufacturing

Reaction-bonded SiC-B 4 C-Si ceramic composites were binder jet 3D-printed and subsequently pressureless-melt-infiltrated with molten Si. The addition of B 4 C aided the Si infiltration to produce a highly dense composite. The microstructures and phases of these composites were examined. The measured hardness values of each constituent with Vickers and nanoindentation matched the bulk values, and the macro-hardness values with Knoop and spherical indentation represented the bulk, composite hardness values of all three phases together, which was close to a rule of mixtures value. For particulate-based composites, this is a significant finding. The interfacial bonds of SiC and Si were imaged using scanning transmission electron microscopy to view intimacy, whereas the crack propagation was examined with carefully placed indents. This work demonstrated that pressureless melt infiltration with a reactive particle provides a method to shape non-wetting reaction-bonded ceramic composites with limited shrinkage and high density and provides insights into the mechanical behavior with numerous indentation techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of Ligand Polarity on the Internal Dipoles and Ferroelectric Distortion in BaTiO 3 Nanocubes

Here, surface adsorbates and surrounding matrix species have been demonstrated to affect the properties of nanoscale ferroelectrics and nanoscale ferroelectric composites; potentially counteracting performance losses that can occur in small particle sizes. In this work, the effects of nonpolar oleic acid (OA) and polar tetrafluoroborate (BF 4 - ) ligand capping on the surface of various sizes of BaTiO 3 nanocubes have been investigated with combined neutron diffraction and neutron pair distribution function (PDF), density functional theory (DFT), and ab initio molecular dynamics (AIMD) methods. The low real space PDF region provides an unobstructed view of rhombohedral (split short and long) Ti-O distances in BaTiO 3 nanocubes, mimicking the well-established order-disorder local structure found in bulk BaTiO 3 . Interestingly, the intermediate-range order in nanocubes is found to be orthorhombic, rather than tetragonal. It is concluded that polar ligands adsorbed at BaTiO 3 surfaces stabilize the correlation length scale of local rhombohedral distortions in ferroelectric nanoparticles relative to nonpolar ligands.

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

A deep insight on the coal ash-to-slag transformation behavior during the entrained flow gasification process

Recent research provided deep insight on the coal ash-to-slag transformation characterization during the entrained flow gasification process, with experimentation on a 40 kg/hr (dry basis) coal-fed opposed multi-burner (OMB) entrained flow gasifier and simulation via FactSage™ software. A general mechanism is presented to relate the gasifier design temperature, ash fluid temperature, and operating temperature with the degree of the slag polymerization. The change of the high temperature zone, the corresponding particle residence time in the high temperature zone, and syngas composition have obvious effects on the slag mineral transformation behavior. Mineral types formed on the wall of the gasifier chamber were mainly anorthite (CaAl 2 Si 2 O 8 ), aluminum oxide (Al 2 O 3 ), and calcium sulfide (CaS). These minerals transformed to anorthite and diopside (CaMgSi 2 O 6 ) at the slag hole zone, while the minerals at the lock hopper were anorthite, orthoclase (KAlSi 3 O 8 ), quartz (SiO 2 ), gypsum (CaSO 4 ), calcite (CaCO 3 ), and halite (NaCl). FactSage™ predicted minerals as anorthite, diopside, orthoclase, and albite (NaAlSi 3 O 8 ), etc., where the slag temperature was below the ash fluid temperature and when the ratios of CO/CO 2 and (CO + H 2 )/CO 2 were lower than 1.0 and 2.0, respectively. By simulation, residual carbon was found to be the dominant factor over syngas composition to cause mineral transformation, and this was verified experimentally. The Ca-based crystals, typically anorthite, was shifted to diopside, near the slag hole zone, and a linear relationship was found between the content ratios of diopside/(anorthite + diopside), CaO/SiO 2 , and (CaO + MgO)/SiO 2 . A dimensionless number, θ, was defined to characterize the changing chemical composition and the degree of slag polymerization, with temperature deviation from the design condition. Three zones of θ were identified and related to the deviation between the actual gasification condition from the design condition. Finally, a low slag polymerization degree corresponded with a higher temperature deviation between the actual condition and design condition, and this proved that increased residual carbon content and changing iron valence state increased the mineral types when the slag temperature was below the ash fluid temperature.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Global organic and inorganic aerosol hygroscopicity and its effect on radiative forcing

The climate effects of atmospheric aerosol particles serving as cloud condensation nuclei (CCN) depend on chemical composition and hygroscopicity, which are highly variable on spatial and temporal scales. Here we present global CCN measurements, covering diverse environments from pristine to highly polluted conditions. We show that the effective aerosol hygroscopicity, κ, can be derived accurately from the fine aerosol mass fractions of organic particulate matter (ϵ org ) and inorganic ions (ϵ inorg ) through a linear combination, κ = ϵ org · κ org + ϵ inorg · κ inorg . In spite of the chemical complexity of organic matter, its hygroscopicity is well captured and represented by a global average value of κ org = 0.12 ± 0.02 with κinorg = 0.63 ± 0.01 as the corresponding value for inorganic ions. By showing that the sensitivity of global climate forcing to changes in κ org and κ inorg is small, we constrain a critically important aspect of global climate modelling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Thermal processing to modulate surface chemistry and bulk charge distribution in nickel-rich layered lithium positive electrodes

The broader application of nickel-rich layered oxides as positive electrode materials for lithium-ion batteries has been hindered by their high manufacturing cost and inferior cycling stability. Thermal processing, which is integral to electrode materials manufacturing and fundamental in materials science, has not been fully utilized to design advanced positive electrode materials. Herein, we demonstrate the capability of using quenching heat treatment to regulate Li distribution and modulate electronic structure near particle surface. The resulting materials exhibit less parasitic reactions with the electrolyte and an improved charge distribution homogeneity in secondary particles, leading to more stable cycling performance at high voltages (4.5 V vs Li/Li + ). Our synchrotron X-ray analyses reveal the underlying interplay between surface structure and bulk charge distribution in positive electrode materials particles. While strategies used to stabilize positive electrode materials through compositional control, surface modification, and electrolyte engineering have become mature, thermal processing can be advantageous to further improve positive electrode materials manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Continuous flow photochemical synthesis of metal–ceramic composite microparticles

We developed a UV-assisted microfluidic system to synthesize FeCrAl–Al 2 O 3 composite microparticles for additive manufacturing. Here, the system ensures precise particle size, morphology, and elemental distribution control. Increasing the dispensing pressure while keeping the oil flow rate constant resulted in larger microparticles. Laser fusing revealed FeCrAl and Al 2 O 3 phases, showing their potential as feedstocks for 3D printed heterogeneous materials such as FeCrAl/Al 2 O 3 bi-phase materials.

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

Demonstrating Agreement between Radio and Fluorescence Measurements of the Depth of Maximum of Extensive Air Showers at the Pierre Auger Observatory

We show, for the first time, radio measurements of the depth of shower maximum ( X max ) of air showers induced by cosmic rays that are compared to measurements of the established fluorescence method at the same location. Using measurements at the Pierre Auger Observatory we show full compatibility between our radio and the previously published fluorescence dataset, and between a subset of air showers observed simultaneously with both radio and fluorescence techniques, a measurement setup unique to the Pierre Auger Observatory. Furthermore, we show radio X max resolution as a function of energy and demonstrate the ability to make competitive high-resolution X max measurements with even a sparse radio array. With this, we show that the radio technique is capable of cosmic-ray mass composition studies, both at Auger and at other experiments. Published by the American Physical Society 2024

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Solar Modulation of Cosmic Nuclei over a Solar Cycle: Results from the Alpha Magnetic Spectrometer

We report the properties of precision time structures of cosmic nuclei He, Li, Be, B, C, N, and O fluxes over an 11-year solar cycle from May 2011 to November 2022 in the rigidity range from 1.92 to 60.3 GV. The nuclei fluxes show similar but not identical time variations with amplitudes decreasing with increasing rigidity. In particular, below 3.64 GV the Li, Be, and B fluxes, and below 2.15 GV the C, N, and O fluxes, are significantly less affected by solar modulation than the He flux. We observe that these differences in solar modulation are linearly correlated with the differences in the spectral indices of the cosmic nuclei fluxes. This shows, in a model-independent way, that solar modulation of galactic cosmic nuclei depends on their spectral shape. In addition, solar modulation differences due to nuclei velocity dependence on the mass-to-charge ratio (𝐴/𝑍) are not observed.

cosmic ray composition & spectra↗
DOE OSTI2025

Neutron and Gamma-Ray Imaging of Th-232 and Cm-244 Using Organic Glass Scintillators

Modern nuclear safeguards require detection and characterization capabilities suitable for a wide variety of radiation sources and applications. Field-deployable detection systems have also had to modernize to meet changing needs. Recent developments in organic scintillator technology have resulted in the creation of an organic glass scintillator (OGS) at Sandia National Laboratory which is composed of a 9:1 mixture of glass compounds C42H36Si and C51H44Si. The novel scintillator composition was implemented into the design for a dual-particle capable imaging system at the University of Michigan. This work presents new results from two experiments demonstrating the gamma-ray and fast-neutron imaging capabilities of the organic glass system. Gamma spectroscopy was also performed using CeBr3 scintillators that are part of the imager design. Measurements were performed at Lawrence Livermore National Laboratory using 232Th metal hemishells and an encapsulated 244Cm oxide source. Successful gamma-ray imaging of the 232Th distributed sources is demonstrated with the glass imager, but there were no appreciable neutrons from the 232Th for neutron imaging. Promising neutron and gamma-ray imaging results of 244Cm are demonstrated despite limited imaging event statistics available in this measurement. Gamma-ray spectroscopy results were able to identify 232Th using prominent emissions at 239, 338, 583, and 911 keV. 244Cm was identified from emissions of 43, 99, and 153 keV. These results demonstrate the potential of organic glass imaging for nuclear nonproliferation or characterization efforts.

Lopez, Ricardo [Univ. of Michigan, Ann Arbor, MI (↗
DOE OSTI2023

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗
DOE OSTI2023

Evaluation of High Level Waste Sludge Processing Behavior

The U.S. Department of Energy’s (DOE) Hanford Site has 177 underground storage tanks that contain wastes from past nuclear fuel reprocessing and waste-management operations. Over 20% of this waste is in the form of an insoluble sludge that will require slurry modification before its transfer to the Waste Treatment and Immobilization Plant (WTP). Specific WTP acceptance criteria for waste feed delivery describe the physical and chemical characteristics of the waste that must be met before the waste is transferred to the WTP. One challenging requirement relates to the undissolved solids (UDS) composition in a waste feed because the waste contains solid particles that settle, and their concentration and relative proportion can change during the transfer of the waste in individual batches. A key uncertainty is the ability to transfer and mix wastes with large variations in UDS concentrations and resulting settling rates. To address this uncertainty, a number of small scale mixing and settling tests have been conducted to determine the mobilization performance of variable chemistry simulants. Comparison of the size and density of the particulate for each simulant to that of southeast area Hanford sludge was made using metrics for particle mobilization, suspension, settling, and pipeline transfer where dependance on particle size and density may be different, including: 1. Settling velocity, 2. Critical shear stress for erosion, 3. Just-suspended impeller speed, and 4. Pipeline critical transport velocity. Existing high-level waste sludge data has shown the effect that increasing Al concentration has on resulting settled solids. This differential settling of particles in the sludge has the possibility of resulting in solids segregation during feed preparation and uneven particle distribution during pipeline transportation or mixer jet pump operations. Understanding the predictive capabilities of HLW solids settling and transport as well as potential remedies for addressing disparate sludge behaviors can help provide technical guidance during HLW flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES)

This report presents the physical and chemical characterization of breaker and sorter reject materials sourced from the Prairie State Generation facility, as part of the Illinois Rare Earth Novel Extraction and Supply (IRENES) project. Key analyses include particle size distribution, density, angle of repose, proximate and ultimate composition, mineralogy, and elemental content. Breaker reject material was found to be coarser and higher in ash content (~80%) with lower calorific value, while sorter reject showed finer distribution, lower ash (~68%), and higher carbon and energy content. XRD and XRF analyses confirmed the presence of REE-bearing minerals and relevant oxides, supporting process design and beneficiation strategy development for critical mineral recovery.

01 COAL, LIGNITE, AND PEAT↗