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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The surface chemistry of cuprous oxide

The chemical and electronic properties of copper combined with its large natural abundance lend this material to impact a wide range of technological applications, including heterogeneous catalysis. The reactivity of copper in its Cu 1+ oxidation state makes this specific configuration relevant in various chemical reactions, but the facile redox properties of copper make the isolation of individual states for fundamental studies difficult. Here, in this study, we review three Cu 2 O model systems used to study the interaction of Cu 1+ with small molecules making use of surface science techniques: Cu 2 O/Cu(111), thin polycrystalline Cu 2 O films on Cu foil, and bulk Cu 2 O crystals. Advantages and disadvantages of each system are discussed and exemplified through case studies of chemical adsorption and reactivity studies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluating Cryo–TEM Reconstruction Accuracy of Self–Assembled Polymer Nanostructures

Cryogenic transmission electron microscopy (cryo–TEM) combined with single particle analysis (SPA) is an emerging imaging approach for soft materials. However, the accuracy of SPA–reconstructed nanostructures, particularly those formed by synthetic polymers, remains uncertain due to potential packing heterogeneity of the nanostructures. In this study, the combination of molecular dynamics (MD) simulations and image simulations is utilized to validate the accuracy of cryo–TEM 3D reconstructions of self–assembled polypeptoid fibril nanostructures. Using CryoSPARC software, image simulations, 2D classifications, ab initio reconstructions, and homogenous refinements are performed. By comparing the results with atomic models, the recovery of molecular details is assessed, heterogeneous structures are identified, and the influence of extraction location on the reconstructions is evaluated. In conclusion, these findings confirm the fidelity of single particle analysis in accurately resolving complex structural characteristics and heterogeneous structures, exhibiting its potential as a valuable tool for detailed structural analysis of synthetic polymers and soft materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mapping of Heterogeneous Catalyst Degradation in Polymer Electrolyte Fuel Cells

Pt catalysts in polymer electrolyte fuel cells degrade heterogeneously as the catalyst particles are exposed to local variations throughout the catalyst layer during operation. State-of-the-art analytical techniques for studying degradation of Pt catalysts do not possess fine spatial resolution to elucidate such non-uniform degradation behavior at a large electrode level. A new methodology is developed to spatially resolve and quantify the heterogeneous Pt catalyst degradation over a large area (several cm ) of aged MEAs based on synchrotron X-ray microdiffraction. PEFC single cells are aged using voltage cycling as an accelerated stress test and the degradation heterogeneity at a micrometer length scale is visualized by mapping Pt catalyst particle size after voltage cycling. It is demonstrated in detail that the Pt catalyst particle size growth is non-uniform and follows the flow field geometry. The Pt particle size growth is greater in the area under the flow field land, while it is minimal in the area under the flow field channel. Additional non-uniformity is observed with the Pt particle size increasing more rapidly at the air outlet area than the Pt particle size at the inlet area.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Addendum to Capability Needs for Irradiated and Radioactive Materials Research (Ad Hoc Committee Summary Report)

Nuclear materials and fuels studies are challenging research and engineering targets because of their inherent radioactivity as well as their heterogeneous microstructure. Advanced light sources have made significant underpinning scientific contributions to the understanding of structural and fuel cladding material microstructure and properties and the development of structure-property relationships. These facilities have the potential to help advance the Department of Energy (DOE) Office of Nuclear Energy (DOE-NE) mission priorities providing underpinning understanding of technically important challenges, including: irradiation induced embrittlement and swelling; stress corrosion cracking and corrosion in extreme environments; ageing of reactor pressure vessels steels; nuclear fuel characterization; and nuclear waste form optimization as well as playing a major role in the development of a materials performance matrix to aid in the design of new materials to meet the needs of advanced reactor concepts. However, the delivery of underpinning understanding is the mission of DOE Office of Science (DOE-SC). While filling such knowledge gaps is important, efforts in this direction should not be confused with the strategic technology focused mission goals of DOE-NE to enable the continued operation of existing U.S. nuclear reactors, to enable the deployment of advanced nuclear reactors, to develop advanced nuclear fuel cycles, and to maintain U.S. leadership in nuclear energy technology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Lithium-Ion Battery Materials as Tunable, “Redox Non-Innocent” Catalyst Supports

The development of general strategies for the electronic tuning of a catalyst’s active site is an ongoing challenge in heterogeneous catalysis. To this end, herein, we describe the application of Li-ion battery cathode and anode materials as redox non-innocent catalyst supports that can be continuously modulated as a function of lithium intercalation. A zero-valent nickel complex was oxidatively grafted onto the surface of lithium manganese oxide (Li x Mn 2 O 4 ) to yield isolated Ni2+ occupying the vacant interstitial octahedral site in the Li diffusion channel on the surface and subsurface of the spinel structure (Ni/Li x Mn 2 O 4 ). Additionally, the activity of Ni/Li x Mn 2 O 4 for olefin hydrogenation, as a representative probe reaction, was found to increase monotonically as a function of support reductive lithiation. Simulation of Ni/Li x Mn 2 O 4 reveals the dramatic impact of surface redox states on the viability of the homolytic oxidative addition mechanism for H 2 activation. Catalyst control through support lithiation was extended to an organotantalum complex on Li x TiO 2 , demonstrating the generality of this phenomenon.

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

Predicting Elastic Properties of Materials from Electronic Charge Density Using 3D Deep Convolutional Neural Networks

Materials representation plays a key role in machine learning-based prediction of materials properties and new materials discovery. Currently both graph and three-dimensional (3D) voxel representation methods are based on the heterogeneous elements of the crystal structures. Here, we propose to use electronic charge density (ECD) as a generic unified 3D descriptor for materials property prediction with the advantage of possessing close relation with the physical and chemical properties of materials. We developed an ECD-based 3D convolutional neural networks (CNNs) for predicting the elastic properties of materials, in which CNNs can learn effective hierarchical features with multiple convolving and pooling operations. Extensive benchmark experiments over 2170 $Fm\bar3m$ face-centered-cubic materials show that our ECD-based CNNs can achieve good performance for elasticity prediction. Especially, our CNN models based on the fusion of elemental Materials-Agnostic Platform for Informatics and Exploration features and ECD descriptors achieved the best fivefold cross-validation performance. More importantly, we showed that our ECD-based CNN models can achieve significantly better extrapolation performance when evaluated over nonredundant data sets, where there are few neighbor-training samples around test samples. As an additional validation, we evaluated the predictive performance of our models on 329 materials of space group $Fm\bar3m$ by comparing to density functional theory calculated values, which shows a better prediction power of our model for bulk modulus than shear modulus. Because of the unified representation power of ECD, it is expected that our ECD-based CNN approach can also be applied to predict other physical and chemical properties of crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thermodynamic non-ideality and disorder heterogeneity in actinide silicate solid solutions

Non-ideal thermodynamics of solid solutions can greatly impact materials degradation behavior. We have investigated an actinide silicate solid solution system (USiO 4 –ThSiO 4 ), demonstrating that thermodynamic non-ideality follows a distinctive, atomic-scale disordering process, which is usually considered as a random distribution. Neutron total scattering implemented by pair distribution function analysis confirmed a random distribution model for U and Th in first three coordination shells; however, a machine-learning algorithm suggested heterogeneous U and Th clusters at nanoscale (~2 nm). The local disorder and nanosized heterogeneous is an example of the non-ideality of mixing that has an electronic origin. Partial covalency from the U/Th 5f–O 2p hybridization promotes electron transfer during mixing and leads to local polyhedral distortions. The electronic origin accounts for the strong non-ideality in thermodynamic parameters that extends the stability field of the actinide silicates in nature and under typical nuclear waste repository conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Prediction of Probabilistic Shock Initiation Thresholds of Energetic Materials Through Evolution of Thermal-Mechanical Dissipation and Reactive Heating

The ignition threshold of an energetic material (EM) quantifies the macroscopic conditions for the onset of self-sustaining chemical reactions. The threshold is an important theoretical and practical measure of material attributes that relate to safety and reliability. Historically, the thresholds are measured experimentally. In this work, we present a new Lagrangian computational framework for establishing the probabilistic ignition thresholds of heterogeneous EM out of the evolutions of coupled mechanical-thermal-chemical processes using mesoscale simulations. Furthermore, the simulations explicitly account for microstructural heterogeneities, constituent properties, and interfacial processes and capture processes responsible for the development of material damage and the formation of hotspots in which chemical reactions initiate. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, heat conduction, reactive chemical heating, gaseous product generation, and convective heat transfer. To determine the ignition threshold, the minimum macroscopic loading required to achieve self-sustaining chemical reactions with a rate of reactive heat generation exceeding the rate of heat loss due to conduction and other dissipative mechanisms is determined. Probabilistic quantification of the processes and the thresholds are obtained via the use of statistically equivalent microstructure sample sets (SEMSS). The predictions are in agreement with available experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Active Sites in a Heterogeneous Organometallic Catalyst for the Polymerization of Ethylene

Heterogeneous derivatives of catalysts developed by Ziegler and Natta are important for the industrial production of polyolefin plastics. However, the interaction between precatalysts, alkylaluminum activators, and oxide supports to form catalytically active materials is poorly understood. This is in contrast to homogeneous or well-defined heterogeneous catalysts that 20 contain resolved molecular structures that relate to activity and selectivity in polymerization reactions. This study describes the reactivity of triisobutylaluminum with high surface area aluminum oxide and a zirconocene precatalyst. Triisobutylaluminum reacts with the zirconocene precatalyst to form hydrides and passivates –OH sites on the alumina surface. The combination of passivated alumina and zirconium hydrides formed in this mixture generate ion-pairs that 25 polymerize ethylene.

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

Comparison of amplification via the acousto-electric effect of Rayleigh and Leaky-SAW modes in a monolithic surface InP:InGaAs/lithium niobate heterostructure

This work demonstrates a monolithic surface acoustic wave amplifier fabricated by state-of-the-art heterogenous integration of a III-V InGaAs-based epitaxial material stack and LiNbO 3 . We compare amplification of Raleigh-SAW and leaky-SAW modes on a on Y-cut, X-propagating delay line amplifier. Due to the superior properties of the materials employed, we observe a net terminal gain of 3dB for an LSAW overtone mode This platform enables further advances in active and non-reciprocal piezoelectric acoustic devices.

42 ENGINEERING↗
DOE OSTI2021

Opposing Effects of Impurity Ion Sr 2+ on the Heterogeneous Nucleation and Growth of Barite (BaSO 4 )

Nucleation of barite (BaSO 4 ) has broad implications in geological, environmental, and materials sciences. While impurity metals are common, our understanding of how they impact nucleation remains dim. In this work, we used classical optical microscopy compared to fast X-ray nanotomography (XnT) to investigate heterogeneous nucleation of barite on silica in situ with Sr 2+ as an impurity ion. The observed barite nucleation rates were consistent with classical nucleation theory (CNT), where barite crystals displayed a nonuniform size distribution, exhibiting distinct morphologies and incubation periods in Sr-free solutions. While undetectable with optical microscopy, nanotomography revealed that addition of Sr2+ enhances nucleation rates driven by the pre-factor in CNT, likely because both adsorbed Ba 2+ and Sr 2+ act as precursor sites on which nucleation occurs. Sr 2+ simultaneously inhibits growth, however, leading to a homogeneous distribution of smaller crystals. This finding will enable an improved predictive understanding of nucleation in natural and synthetic environments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Enantioselective catalysts based on metal-organic framework-supported nucleotides

Adenosine triphosphate (ATP) and other nucleotides can be irreversibly bound to the metal-organic framework (MOF) MIL-101(Cr). Analysis of X-ray diffraction data suggests that the location of the adsorbed ATP molecule is in proximity of the Cr 3 clusters. Solid-state NMR and DFT calculations indicate that ATP is bound to MIL-101(Cr) through linkages of the terminal phosphate group with Cr(III) of the framework. In the presence of Cu(II) ions, the MOF-supported nucleotides can function as stable and reusable enantioselective heterogeneous catalysts for reactions like Diels-Alder and Michael addition. In conclusion, compared to the corresponding homogeneous nucleotide-based artificial metalloenzymes (ArMs), the MOF-supported nucleotide-based ArMs exhibit significantly enhanced activity and selectivity in certain cases, demonstrating their potential as a new class of enantioselective heterogeneous catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Isotopic Heterogeneity Imaged in a Uranium Fuel Pellet with Extreme Ultraviolet Laser Ablation and Ionization Time-of-Flight Mass Spectrometry

We use extreme ultraviolet laser ablation and ionization time-of-flight mass spectrometry (EUV TOF) to map uranium isotopic heterogeneity at the nanoscale (=100 nm). Using low-enriched uranium fuel pellets that were made by blending two isotopically distinct feedstocks, we show that EUV TOF can map the 235U/238U content in 100 nm-sized pixels. The two-dimensional (2D) isotope maps reveal U ratio variations in sub-microscale to =1 µm areas of the pellet that had not been fully exposed by microscale or bulk mass spectrometry analyses. Compared to the ratio distribution measured in a homogeneous U reference material, the ratios in the enriched pellet follow a ~3× wider distribution. These results indicate U heterogeneity in the fuel pellet from incomplete blending of the different source materials. EUV TOF results agree well with those obtained on the same enriched pellets by nanoscale secondary ionization mass spectrometry (NanoSIMS), which reveals a comparable U isotope ratio distribution at the same spatial scale. EUV TOF’s ability to assess and map isotopic heterogeneity at the nanoscale makes it a promising tool in fields such as nuclear forensics, geochemistry, and biology that could benefit from uncovering sub-microscale sources of chemical modifications.

Rush, Lydia A.↗
DOE OSTI2020

Development of an MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete

Abstract Although contactless ultrasonic wavefield imaging shows potential for effective nondestructive inspection of various engineering materials, it has been rarely applied to concrete materials owing to technical challenges including low signal-to-noise ratio (SNR) caused by inherent heterogeneity of concrete. This paper presents development of a multi-channel MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete materials. The developed multi-channel MEMS ultrasonic microphone array system contains eight MEMS ultrasonic microphone elements and a signal conditioning circuit that enables measurements of ultrasonic signals with high SNR. A compressed sensing approach, based on the multiple measurement vector (MMV) concept, is applied to reconstruct a full dense ultrasonic wavefield data from sparsely sampled ultrasonic wavefield data. Experiments are carried out on a laboratory concrete sample to verify the performance of the developed MEMS microphone array system and proposed compressed sensing approach and then large-scale concrete samples to demonstrate practical application. The experimental results demonstrate that the developed MEMS microphone array system provides high-quality (SNR > 20 dB) ultrasonic data collected from concrete elements; furthermore, the proposed compressed sensing approach provides accurate reconstruction of dense wavefield data, as determined by peak signal-to-noise ratio (PSNR), from sparsely measured wavefield data with compression ratios up to 85% and PSNR above 25 dB in data collected form realistic large-scale concrete samples. By combining the MEMS array system and compressed sensing approach, the total ultrasonic data acquisition time needed to produce dense wavefield data can be significantly reduced.

Instruments & Instrumentation↗
DOE OSTI2022

Exploring Structure-Sensitive Relations for Small Species Adsorption Using Machine Learning

Accurate prediction of adsorption energies on heterogeneous catalyst surfaces is crucial to predicting reactivity and screening materials. Adsorption linear scaling relations have been developed extensively but often lack accuracy and apply to one adsorbate and a single binding site type at a time. These facts undermine their ability to predict structure sensitivity and optimal catalyst structure. Using machine learning on nearly 300 density functional theory calculations, we demonstrate that generalized coordination number scaling relations hold well for oxygen- and high-valency carbon-binding species but fail for others. Here we reveal that the valency and the electronic coupling of a species with the surface, along with the site type and its coordination environment, are critical for small species adsorption. The model simultaneously predicts the adsorption energy and preferred site and significantly outperforms linear scalings in accuracy. It can expose the structure sensitivity of chemical reactions and enable enhanced catalyst activity via engineering particle shape and facet defects. The generality of our methodology is validated by training the model with transition metal data and transferring it to predict adsorption energies on single-atom alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗