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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The exit-wave power-cepstrum transform for scanning nanobeam electron diffraction: robust strain mapping at subnanometer resolution and subpicometer precision

Scanning nanobeam electron diffraction (NBED) with fast pixelated detectors is a valuable technique for rapid, spatially resolved mapping of lattice structure over a wide range of length scales. However, intensity variations caused by dynamical diffraction and sample mistilts can hinder the measurement of diffracted disk centers as necessary for quantification. Robust data processing techniques are needed to provide accurate and precise measurements for complex samples and non-ideal conditions. Here we present an approach to address these challenges using a transform, called the exit wave power cepstrum (EWPC), inspired by cepstral analysis in audio signal processing. The EWPC transforms NBED patterns into real-space patterns with sharp peaks corresponding to inter-atomic spacings. We describe a simple analytical model for interpretation of these patterns that cleanly decouples lattice information from the intensity variations in NBED patterns caused by tilt and thickness. With tracking the inter-atomic spacing peaks in EWPC patterns, strain mapping is demonstrated for two practical applications: mapping of ferroelectric domains in epitaxially strained PbTiO 3 films and mapping of strain profiles in arbitrarily oriented core-shell Pt-Co nanoparticle fuel-cell catalysts. The EWPC transform enables lattice structure measurement at sub-pm precision and sub-nm resolution that is robust to small sample mistilts and random orientations.

42 ENGINEERING↗
DOE OSTI2025

Cross slip of extended dislocations in face-centered cubic metals through phase-field modeling

Cross slip is a dislocation mechanism that significantly impacts the mechanical behavior of engineering alloys. Here, in this work, we advance a 3D phase-field dislocation dynamics (PFDD) mesoscale technique to simulate cross slip across a broad range of face-centered cubic (FCC) metals. The formulation incorporates elastic anisotropy, an FCC numerical grid, and a high-fidelity representation of the entire γ -surface from density functional theory for eight FCC metals and no adjustable parameters or rules. The relaxed core structures under zero stress for all metals are predicted to extend in plane. The analytical model for stacking fault width agrees well with the PFDD result under the assumption of elastic isotropy but overestimates it under elastic anisotropy, when the degree of anisotropy is large. The dynamic simulations are designed to elucidate the material parameters that influence the propensity for cross slip. Whether cross slip occurs under a non-Schmid stress or to bypass a hard obstacle, the critical stress to cross slip scales strongly with the anisotropic energy coefficient for a screw dislocation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Recent advances in hybrid metal oxide–zeolite catalysts for low-temperature selective catalytic reduction of NOx by ammonia

A hybrid catalytic system comprised of metal oxide and Cu or Fe exchanged zeolite components represents a potential advancement of state-of-the-art for selective catalytic reduction (SCR) of NOx by ammonia, including an elegant solution to the current challenge of improving the low-temperature efficiency of SCR catalysts. The idea is to enable in-situ NO oxidation over metal oxide component and concomitant fast SCR over zeolite component in the so-called “bifunctional mechanism”. This review is presented in the wake of growing interest in this innovative catalytic system. We begin this review by presenting key parameters that contribute to the synergy between metal oxide and zeolite components. Then, we discuss the materials selection for both components and their possible interactions in the system, followed by a summary of recent NH3-SCR investigations over multiple metal oxide–zeolite pairs and additional discussion on pairing techniques potentially explorable in upcoming studies. Finally, we end the review by providing the perspectives on future challenges in the development of this catalytic system.

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

Unveiling the Redox Noninnocence of Metallocorroles: Exploring K-Edge X-ray Absorption Near-Edge Spectroscopy with a Multiconfigurational Wave Function Approach

X-ray absorption near-edge spectroscopy (XANES) is an advanced technique for probing the local electronic structure of catalysts, effectively identifying the noninnocent nature of ligands in transition-metal complexes. Metallocorroles with noninnocent corrole rings exhibit unusual electronic structures that challenge traditional density functional theory (DFT) methods, necessitating more rigorous approaches to describe electron correlation accurately. We explored K-edge XANES spectra of Fe, Mn, and Co metallocorroles using TDDFT and wave function-based methods. This is the first investigation employing multireference methods, specifically RASSCF, RASPT2, and MC-PDFT, to analyze the redox noninnocent nature of metallocorroles reflected in their XANES spectra. We quantified the noninnocent character of the corrole and the oxidation states of the metals, capturing more than singly excited excitations responsible for the pre-edge peak. Our findings demonstrate the importance of these advanced computational techniques for accurately predicting XANES spectra, providing a reliable understanding of the electronic properties of such complexes. In conclusion, this study offers a new strategy for investigating ligand redox noninnocence via integrated experimental and computational XANES.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Understanding the Stability of Manganese Chromium Antimonate Electrocatalysts through Multimodal In Situ and Operando Measurements

Herein, we utilize an on-line electrochemical flow cell coupled with an inductively coupled plasma-mass spectrometer (ICP-MS) to characterize the impact of composition and reactant gas on the multielement dissolution of Mn(-Cr)-Sb-O electrocatalysts. Compared to Mn 2 O 3 and Cr 2 O 3 oxides, we find that the antimonate framework stabilizes Mn at OER potentials and Cr at both ORR and OER potentials. Furthermore, dissolution of Mn and Cr from Mn(-Cr)-Sb-O is found to be driven by ORR reaction rate, with minimal dissolution under N 2 . We observe preferential dissolution of Cr totaling 13% over 10 minutes at 0.3, 0.6, and 0.9 V vs RHE, with only 1.5% loss of Mn, indicating an enrichment of Mn at the surface of the particles. Despite this asymmetric dissolution, in situ X-ray absorption spectroscopy (XAS) showed no measurable changes in the Mn K-edge at comparable potentials. This lack of change could suggest that modification to the Mn oxidation state in the surface layer is too small or that layer is too thin to be measured with the bulk XAS measurement. Lastly, on-line ICP-MS was used to assess the effects of applied potential, scan rate, and current of Mn-Cr-Sb-O during cyclic voltammetry and accelerated stress tests. With this deeper understanding of the interplay between oxygen reduction and dissolution, testing procedures were identified to maximize both activity and stability. This work highlights the use of multi-modal in situ characterization techniques in tandem to build a more complete model of stability and develop protocols for optimizing catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Autonomous design of new chemical reactions using a variational autoencoder

Artificial intelligence based chemistry models are a promising method of exploring chemical reaction design spaces. However, training datasets based on experimental synthesis are typically reported only for the optimal synthesis reactions. This leads to an inherited bias in the model predictions. Therefore, robust datasets that span the entirety of the solution space are necessary to remove inherited bias and permit complete training of the space. In this study, an artificial intelligence model based on a Variational AutoEncoder (VAE) has been developed and investigated to synthetically generate continuous datasets. The approach involves sampling the latent space to generate new chemical reactions. This developed technique is demonstrated by generating over 7,000,000 new reactions from a training dataset containing only 7,000 reactions. The generated reactions include molecular species that are larger and more diverse than the training set.

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

Diazo coupling for surface attachment of small molecules to TiO 2 nanoparticles

Robust surface attachment of molecular species to metal oxide semiconductors is desirable for many applications. In this work, we report the interfacial diazo coupling of surface-bound amines with aromatics to bind them to the surface of TiO 2 nanoparticles via a robust siloxane anchor and a diazo link. The technique shows potential for the inexpensive, stable, modular and tunable attachment of molecules to metal oxide surfaces.

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

Determination of the dehydration pathway in a flexible metal–organic framework by dynamic in situ x-ray diffraction

Understanding guest exchange processes in metal–organic frameworks is an important step toward the rational design of functional materials with tailor-made properties. The dehydration of the flexible metal-organic framework [Co(AIP)(bpy)0.5(H2O)]•2H2O was studied by novel in situ dynamic x-ray diffraction techniques. The complex mechanism of dehydration, along with the as-yet unreported metastable structures, was determined. The structural information obtained by the application of these techniques helps to elucidate the important guest–host interactions involved in shaping the structural landscape of the framework lattice and to highlight the importance of utilizing this technique in the characterization of functional framework materials.

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

A semi-analytical model for laser induced densification in fused silica at elevated temperatures

A semi-analytical model for deterministic surface smoothing of fused silica below the evaporation temperature threshold is presented. Using this model, a method for calculating deterministic track depths for laser polishing fused silica is derived and validated with experiments. In this work, model predictions were in good agreement with experiment across varying laser preheating temperature and power. With the semi-analytical method presented here, deterministic laser smoothing can be achieved in the densification regime to close the process loop of laser polishing.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atmospheric Pressure Plasma Deposition of TiO2: A Review

Atmospheric pressure plasma (APP) deposition techniques are useful today because of their simplicity and their time and cost savings, particularly for growth of oxide films. Among the oxide materials, titanium dioxide (TiO2) has a wide range of applications in electronics, solar cells, and photocatalysis, which has made it an extremely popular research topic for decades. Here, we provide an overview of non-thermal APP deposition techniques for TiO2 thin film, some historical background, and some very recent findings and developments. First, we define non-thermal plasma, and then we describe the advantages of APP deposition. In addition, we explain the importance of TiO2 and then describe briefly the three deposition techniques used to date. We also compare the structural, electronic, and optical properties of TiO2 films deposited by different APP methods. Lastly, we examine the status of current research related to the effects of such deposition parameters as plasma power, feed gas, bias voltage, gas flow rate, and substrate temperature on the deposition rate, crystal phase, and other film properties. The examples given cover the most common APP deposition techniques for TiO2 growth to understand their advantages for specific applications. In addition, we discuss the important challenges that APP deposition is facing in this rapidly growing field.

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

40th Eastern Regional Photosynthesis Conference

Photosynthesis has shaped global biochemistry and geochemistry in its production of almost all atmospheric oxygen, and almost every electron that supports the processes of life on Earth was extracted from water by the light-dependent reactions, many of which were then used to fix carbon in the dark reactions. To humans, that fixed carbon is the originator of all fossil fuels and a critical step in conversion of solar photons to human-usable energy. The Eastern Regional Photosynthesis Conference (ERPC) serves as a forum for advancement of science in this field. As a regional-level conference, it specializes in providing developmental opportunities for early-career researchers from undergraduates to pre-tenure professors, as well as broadening the field in terms of participating scholars and research approaches to produce new interdisciplinary collaborations. Funding from the Department of Energy is used to mitigate registration and attendance costs for junior (non-PI) researchers. The ERPC is one of the three regional conferences in the field of photosynthesis research in the United States, alongside the Western Photosynthesis Conference (currently in California) and the Midwestern Photosynthesis Conference (Turkey Run, Indiana). A longstanding incubator for scientific discourse, discovery, and collaborations, this conference has spawned many collaborations which led to Department of Energy-funded projects and brought two full generations of scientists into the field. In 2023 the landmark 40th such conference was held at the Woods Hole Marine Biological Laboratory in Massachusetts. The conference was held April 14th-16th, 2023. The majority of the total attendees are traditionally undergraduates, graduate students, and postdoctoral researchers, whose scientific development greatly benefits from conferences like these. Almost all talks besides the ones given by invited speakers were given by young scientists who benefited from this award. Many posters presented at this conference were also the work of junior scientists. This conference is many young scientists' first exposure to the photosynthesis research community and its primary goal is to provide a positive atmosphere for those attendees, as exemplified by the three poster sessions and dedicated interactions between senior and junior scientists. Additionally, this was the first year of a successful equitable outreach and speaker recruitment plan to provide fair representation at the conference in line with Department of Energy policies and mission. The central focus of the ERPC is the understanding of energy flow from photons to usable chemical products in both natural and artificial photosynthesis. We support the DOE-BES aim of understanding of the biochemical/biophysical processes of photosynthesis to inform new technology development and field applications. This year’s theme, “Photosynthesis Across Scales,” reflected the scope of work being done from the individual exciton to the crop scale. This research encompasses applied biology, chemistry, physics, and materials engineering. The aim of this conference is to present new discoveries, techniques, and questions which can be sourced from any of these disciplines and provide an audience which is broadly qualified to use or respond to these developments.

08 HYDROGEN↗
DOE OSTI2026

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗
DOE OSTI2025

Neutron Total Scattering Analysis of Materials for the Nuclear Fuel Cycle

Here, this paper reviews recent experimental efforts at the University of Tennessee and Oak Ridge National Laboratory to comprehensively characterize the structural details of materials relevant for the nuclear fuel cycle by employing advanced neutron scattering techniques. For the study of nuclear ceramics, neutron scattering offers distinct advantages over traditional laboratory or synchrotron X-ray diffraction, including enhanced sensitivity to elements with a low atomic mass, such as oxygen, nitrogen, and carbon. The key to these efforts is the recent advancement in the neutron scattering infrastructure at the high-flux diffractometers at the Spallation Neutron Source. The high neutron flux at these instruments enables neutron total scattering, a nondestructive bulk technique that simultaneously captures both short-range structural effects through pair distribution function analysis and long-range order through diffraction pattern analysis. This approach is particularly important for a comprehensive description of defective, disordered, or amorphous nuclear materials. The case studies presented here include analyses of the local defect structure in hyperstoichiometric uranium oxides and short-range order of ion-irradiated ceramics. This advanced analytical methodology will improve our understanding of the behavior of materials in extreme environments and contribute to the development of more resilient nuclear materials.

Neutron scattering↗
DOE OSTI2020

Metabolite, Protein, and Lipid Extraction (MPLEx): a method that simultaneously inactivates Middle East respiratory syndrome coronavirus and allows analysis of multiple host cell components following infection

Mass spectrometry (MS)-based, integrated proteomics, metabolomics, and lipidomics (collectively, multi-omics) studies provide a very detailed snap shot of virus-induced changes to the host following infection and can lead to the identification of novel prophylactic and therapeutic targets for preventing or lessening disease severity. Multi-omics studies with Middle East respiratory syndrome coronavirus (MERS-CoV) are challenging as the requirements of Biosafety Level 3 containment limit the numbers of samples that can be safely managed. To address these issues, the multi-omics sample preparation technique MPLEx (metabolite, protein, and lipid extraction) was developed to partition a single sample into three distinct parts (metabolites, proteins and lipids) for multi-omics analysis, while simultaneously inactivating MERS-CoV by solubilizing and disrupting the viral envelope and denaturing viral proteins. Here we describe the MPLEx protocol, highlight the step of inactivation, and describe the details of downstream processing, instrumental analysis of studies with Middle East respiratory syndrome coronavirus (MERS-CoV) are challenging as the requirements of Biosafety Level 3 containment limit the numbers of samples that can be safely managed. To address these issues, the multi-omics sample preparation technique MPLEx (metabolite, protein, and lipid extraction) was developed to partition a single sample into three distinct parts (metabolites, proteins and lipids) for multi-omics analysis, while simultaneously inactivating MERS-CoV by solubilizing and disrupting the viral envelope and denaturing viral proteins. Here we describe the MPLEx protocol, highlight the step of inactivation, and describe the details of downstream processing, instrumental analysis of the three separate analytes and their subsequent informatics pipelines.

Nicora, Carrie D.↗
DOE OSTI2021

Synthesis and Characterization of Magnesium Vanadates as Potential Magnesium-Ion Cathode Materials through an Ab Initio Guided Carbothermal Reduction Approach**

Many technologically relevant materials for advanced energy storage and catalysis feature reduced transition-metal (TM) oxides that are often nontrivial to prepare because of the need to control the reducing nature of the atmosphere in which they are synthesized. In this report, we show that an ab initio predictive synthesis strategy can be used to produce multi-gram-scale products of various MgV x O y -type phases (δ-MgV 2 O 5 , spinel MgV 2 O 4 , and MgVO 3 ) containing V 3+ or V 4+ relevant for Mg-ion battery cathodes. Characterization of these phases using 25 Mg solid-state NMR spectroscopy illustrates the potential of 25 Mg NMR for studying reversible magnesiation and local charge distributions. Rotor-assisted population transfer (RAPT) is used as a much-needed signal-to-noise enhancement technique. The ab initio guided synthesis method is seen as a step forward towards a predictive synthesis strategy for targeting specific complex TM oxides with variable oxidation states of technological importance.

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

Mechanistic Studies of Continuous Partial Methane Oxidation on Cu−Zeolites Using Kinetic and Spectroscopic Methods

Abstract Over the past few decades, a significant amount of research effort has focused on investigating the active site requirements and reaction mechanisms for partial methane oxidation (PMO) to methanol over copper–exchanged zeolites during stoichiometric and stepwise chemical looping routes. More recently, research efforts have expanded to include investigating the PMO reaction in a continuous catalytic regime, primarily focusing on determining the influence of catalyst composition on Cu speciation and structure and, in turn, on PMO rate and selectivity. The structures of candidate Cu active sites are commonly studied using a combination of ex situ and in situ spectroscopic approaches. In this perspective, we critically examine the prior literature on catalytic PMO over Cu–zeolites to identify key knowledge gaps that remain in our understanding as motivation for future research efforts. We identify opportunities for future research to address these gaps by adapting analogous interrogation techniques that have been successfully used to elucidate the active site requirements and mechanistic details of another catalytic redox reaction cycle on Cu–zeolites, the selective catalytic reduction (SCR) of nitrogen oxides (NO x ).

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

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design↗
DOE OSTI2022

Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗