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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Bias-Modulated ALD of ZnO: Insights into Precursor-Surface Interactions for ZnO Films

Atomic layer deposition (ALD) is widely used to deposit conformal thin films but is often limited in the tunability of the resulting material’s properties. Substrate bias and electric fields alter precursor-surface interactions and provide means to tune material properties. To explore this, we performed zinc oxide (ZnO) ALD using diethylzinc (DEZ) and water on silicon native oxide substrates at 150 °C in a sample holder designed to create a static electrical field by biasing one plate of a parallel plate capacitor-style sample holder during deposition. ZnO films prepared in an electric field/on a biased sample holder were thinner, changed relative crystalline composition, and contained more carbon compared to samples grown in identical sample holders without bias. The thickness was independent of the magnitude of the eletric field between plates, indicating that the primary driver for the change was substrate biasing not the electric field between plates of the parallel plate capacitor-style sample holder. Density functional theory calculations showed enhanced electron migration between dissociatively adsorbed DEZ molecules and the ZnO (002) facet with increasing force from an electric field at the substrate surface, which strengthens the electronic interactions between the surface and the adsorbate. These models offer a compelling explanation for the inhibited growth, changes in the crystallinity, and increase in carbon content of films grown in an electric field/on biased plates.

Jones, Jessica C. (ORCID:0000000174754620)↗
DOE OSTI2026

4D-STEM Coupled with Unsupervised Machine Learning to Reveal at Large-Scale the Microstructural Evolution in Li- and Mn-Rich Cathodes

Li- and Mn-rich (LMR) layered oxides are known to exhibit a thin surface reconstruction layer, which grows during electrochemical cycling in a manner that depends on exposed crystallographic facets, cycling conditions, and electrolyte chemistry. Direct characterization of this layer has traditionally relied on high-resolution electron microscopy, which is inherently limited to small fields of view. Here, we employ four-dimensional scanning transmission electron microscopy (4D-STEM) combined with unsupervised machine-learning clustering to quantitatively map phase distributions over large areas and track their evolution in LMR cathodes during electrochemical aging. Our results show that the surface reconstruction layer consists predominantly of a rocksalt phase, whose thickness varies across different facets following activation cycling and becomes substantially thicker and more uniform during calendar aging. In contrast, a spinel-like phase is observed within the particle bulk. Large-area phase mapping and correlative high-resolution imaging reveal that this spinel-like phase preferentially nucleates at bulk crystallographic defects, including boundaries between 60°-rotated layered domains and associated mixed-phase regions, rather than exclusively at the particle surface. Our findings establish a mechanistic distinction between surface-driven rocksalt formation and bulk-defect-mediated spinel nucleation while demonstrating the unique capability of 4D-STEM to provide statistically robust, mesoscale insight into complex phase-evolution processes in LMR cathodes.

4D-STEM↗
DOE OSTI2020

Atomic structure and grain shape evolution of nanodiamond during annealing in oxidizing atmosphere from neutron diffraction and MD simulations

In this work, real space pair-distribution function (PDF) analysis in conjunction with molecular dynamics (MD) simulations was applied to characterize crystal structure, shape and surface structure of diamond nanoparticles annealed in air up to 880 °C. MD simulated models of individual nanodiamond particles of various shapes and sizes were used to calculate theoretical radial distribution functions G(r) for powders with different grain size distributions. The calculated curves, showing distinct differences for the explored parameter space, were compared to the experimental G(r) functions obtained from neutron scattering for annealed detonated nanodiamond samples in a search for a model best describing the actual powders. It was found that as-synthesized nanodiamond grains are terminated by equally abundant (100), (110) and (111) crystallographic faces and their structure does not change upon annealing in air up to 280 °C. The shape and size of grains annealed above 480 °C changes due to surface etching. The etching rate differs between crystals faces and depends on temperature, resulting in the observed differences in grain shape. Below 680 °C the share of the (110) facets gradually increases and at 680 °C the grains become rhombic dodecahedra terminated solely by (110) surfaces. Further increase of the annealing temperature promotes formation of (111) surfaces and at 880 °C the preferred grain shape becomes an octahedron terminated by a variant of (111) surfaces possessing three dangling sp3 bonds per atom. At lower temperatures all grains become smaller and the size distribution moves towards the lower values. Furthermore, as the annealing temperature increases, the smallest grains disappear entirely and the average grain size grows back.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mechanistic Insights Into Fatigue Life Enhancement of High‐Strength Steel via Ultrasonic Impact Treatment

In this work we explore the impact of Ultrasonic Impact Treatment (UIT) on the fatigue performance of high‐strength microalloyed steel commonly used in crankshaft applications. Building on prior observations of fatigue life improvement with UIT, this work focuses on unraveling the process–structure–performance relationships underpinning these enhancements. Microstructural analysis revealed significant grain refinement in the near‐surface layers, with deformation depth increasing at higher impact energies. This led to increased surface hardness and the development of deeper compressive residual stresses, particularly in samples treated with higher impact energy. Rotating bending fatigue testing showed a substantial improvement in fatigue life for UIT‐treated samples, with the endurance limit nearly doubling compared with untreated specimens. Fractographic analysis revealed a transition in crack initiation from surface defects in untreated samples to interior regions in UIT‐treated samples, characterized by the formation of noninclusion‐induced granular bright facets (GBFs). The observed fatigue enhancement is attributed to the synergistic effects of strain hardening and compressive residual stresses, which increase the surface crack threshold and promote interior crack initiation. This study provides new mechanistic insight into UIT‐induced fatigue resistance and interior failure behavior in high‐strength steels.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2021

Precise Identification and Characterization of Catalytically Active Sites on the Surface of γ-Alumina

γ-alumina is one of the oldest and most important commercial catalytic materials with high surface area and stability. These attributes enabled its use as the first commercial large-scale heterogeneous catalyst for ethanol dehydration. Despite progress in materials characterization the nature of the specific sites on the surface of γ-alumina that are responsible for its unique catalytic properties has remained obscure and controversial. By using combined infrared spectroscopy, electron microscopy and solid-state nuclear magnetic resonance measurements we identify the octahedral, amphoteric (O) 5 Al(VI)-OH sites on the (100) segments of massively restructured (110) facets on typical rhombus-platelet γ-alumina as well as the (100) segments of irrational surfaces (invariably always present in all γ-alumina samples) responsible for its unique catalytic activity. Such (O) 5 Al(VI)-OH sites are also present on the macroscopically defined (100) facets of γ-alumina with elongated/rod-like geometry. The mechanism by which these sites lose -OH groups upon thermal dehydroxylation resulting in coordinatively unsaturated penta-coordinate Al +3 O 5 sites is clarified. These coordinatively unsaturated penta-coordinate Al sites produce well-defined thermally stable Al-carbonyl complexes. Overall, our findings contribute to the understanding of the nature of coordinatively unsaturated Al sites on the surface of γ-alumina and their role as catalytically active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Recent Developments in Revealing the Impact of Complex Metal Oxide Reconstruction on Catalysis

Surface reconstruction of complex metal oxides refers to the alterations of the topmost catalyst surface, relative to the bulk structure, following exposure to pretreatment or reaction conditions during heterogeneous catalysis. (1) This structural and electronic transformation may involve (1) changes of the exposed crystallographic facets, (2) changes in chemical composition, such as the enrichment of specific elements, and, (3) morphological variations, including surface roughness and defects (Scheme 1). Beyond relaxation, surface reconstruction here also encompasses disruptions to the periodicity of the sublayers and changes to its stoichiometry. This change significantly influences the chemical properties of the catalyst surface, such as redox sites, (2) acid/base pairs, hydroxyl groups, (3) and surface defects. Surface reconstruction occurs due to the thermodynamic drive to lower the surface energy of the catalyst under the surrounding environment (e.g., temperature, chemical potential of species present). In addition to the treatment or reaction conditions, the extent of reconstruction also depends on the elements in the metal oxide structure. For instance, annealing ABO 3 perovskites (SrTiO 3 , BaTiO 3 , and BaZrO 3 ) at high temperatures (500 °C) in O 2 has a very different impact on the A/B ratio at the surface (ranging from 0.9 to 2.5), depending on the identity of A and B. (4) Metal oxide surface reconstruction under an electric field and exposure to acidic and alkaline media has recently gained increased attention in electrocatalysis, such as in the oxygen evolution reaction (OER); (5,6) however, in this Viewpoint we focus on the impact of surface reconstruction on thermal catalysis, a critical enduring research theme with ongoing challenges. Here, we start showcasing approaches to characterize surface reconstruction at the topmost surface layer, such as low-energy ion scattering (LEIS), discussing advantages and limitations. Next, we connect characterization of surface reconstruction to site-specific kinetic analysis, enabled via steady-state isotopic transient kinetic analysis (SSITKA), and we express our viewpoint on building structure–performance relationships by deeply understanding reconstructed surfaces. Later, we comment on the potential of tuning surface reconstruction to enhance catalytic performance. Finally, we explore the interplay between surface reconstruction and the “intelligent behavior”.

alcohol conversion↗
DOE OSTI2024

CeO2 Nanoparticle Doping as a Probe of Active Site Speciation in the Catalytic Hydrolysis of Organophosphates

Organophosphate hydrolysis is important for degrading environmentally harmful compounds and recovering phosphate ions in biological molecules. CeO2 nanocrystals have been well-studied for dephosphorylation via hydrolysis owing to the accessible and tunable distribution of Ce3+ and Ce4+ ions. However, there remains uncertainty in the literature regarding which surface defect properties direct catalytic activity, such as the Ce3+/Ce4+ distribution, oxygen vacancies, faceting, and dopants, and to what degree they contribute to efficient hydrolysis. Trivalent (M3+) dopants serve as a tool for manipulating defects, including the concentration of Ce3+ and oxygen vacancies, thereby influencing the hydrolytic activity of CeO2. Herein, trivalent metal ions (M = Y3+, Cr3+, In3+, and Gd3+) were employed to modulate the active sites on the CeO2 nanocrystal surface, and the effects of each metal dopant on the cerium oxide active sites for organophosphate hydrolysis were investigated. M-doped CeO2 nanoparticles were synthesized via hydrothermal methods, followed by annealing to remove ligands and prime the nanocrystal surface for catalysis. Catalytic performance was evaluated using dimethyl-p¬-nitrophenyl phosphate (DMNP) as a model organophosphate substrate, with degradation monitored over time using UV-visible absorption spectroscopy. Powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy revealed successful doping of CeO2 in all cases, albeit with distinctive characteristics demonstrating how M3+ dopants affect catalysis. We show that CeO2 exhibits high sensitivity to dopants that generate lattice strain, Ce3+ ions, and oxygen vacancy defects. Consequently, achieving high catalytic efficiency within CeO2 requires a balanced active site ensemble, wherein defects are maintained at optimal concentrations and distributions on the nanocrystal surface.

Miura-Stempel, Emily L.↗
DOE OSTI2025

Facet-dependent structure and dissociation of water at pristine IrO 2 /water interfaces

Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO 2 , specifically, has shown exceptional activity for electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO 2 impacts water reactivity. In this work, we developed a machine learning potential trained to first-principles accuracy for modeling IrO 2 /water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir–O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and interfacial structure, offering atomistic insights into manipulating reaction chemistry at electrocatalytic interfaces.

organic↗
DOE OSTI2020

Stable Surface Terminations of a Perovskite Oxyhydride from First-Principles

Successful synthesis of some perovskite oxyhydrides and their unique catalytic properties have recently attracted researchers’ attention. However, their surface structure remains unclear. Here we identify stable surface terminations of a prototypical perovskite oxyhydride, BaTiO 2.5 H 0.5 , under catalytically relevant temperatures and pressures by using first-principles thermodynamics based on density functional theory. Five low-index facets, including (100), (010), (210), (011), and (211), and their various terminations for a total of 47 different surfaces have been examined for relative stability at different temperatures (700, 500, 300 K) and gas environments (10 –15 ≤ P O2 ≤ 1 atm, 10–15 ≤ PH2 ≤ 100 atm). The most stable ones are found to be (010)-Ba 2 O 2 , (210)-Ti 2 O 2 , and (211)-Ba 2 O 4 H surface terminations. These polar surfaces are stabilized by charge compensation. This work provides important insights into the stable surfaces of perovskite oxyhydrides for future studies of their catalytic properties.

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

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

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

Controlling the Phase Transformation of Alumina for Enhanced Stability and Catalytic Properties

Current transition alumina catalysts require the presence of significant amounts of toxic, environmentally deleterious dopants for their stabilization. Herein, we report a simple and novel strategy to engineer transition aluminas to withstand aging temperatures up to 1200 °C without inducing the transformation to low-surface-area α-Al 2 O 3 and without requiring dopants. By judiciously optimizing the abundance of dominant facets and the interparticle distance, we can control the temperature of the phase transformation from θ-Al 2 O 3 to α-Al 2 O 3 and the specific surface sites on the latter. These specific surface sites provide favorable interactions with supported metal catalysts, leading to improved metal dispersion and greatly enhanced catalytic activity for hydrocarbon oxidation. Further, the results presented herein not only provide molecular-level insights into the critical factors causing deactivation and phase transformation of aluminas but also pave the way for the development of catalysts with improved activity for catalytic hydrocarbon oxidation.

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

Molecular-scale Insights into Cooperativity Switching of x TAB Adsorption on Gold Nanoparticles

Quantifying adsorption behaviors is crucial for various applications such as catalysis, separation, and sensing, yet it is generally challenging to access in solution. Here, we report a combined experimental and computational study of the adsorption behaviors of alkyl-trimethylammonium bromides (xTAB), a class of ligands important for colloidal nanoparticle stabilization and shape control, with various alkyl chain lengths x on Au nanoparticles. We use density functional theory (DFT) to calculate xTAB binding energies on Au{111} and Au{110} surfaces with standing-up and lying-down configurations, which provides insights into the adsorption affinity and cooperativity differences of xTAB on these two facets. We demonstrate the key role of van der Waals interactions in determining the xTAB adsorption behavior. These computational results predict and explain the experimental discovery of xTAB’s adsorption behavior switch from stronger affinity, negative cooperativity to weaker affinity, positive cooperativity when the concentration of xTAB increases in solution. We also show that in the standing-up configuration, bilayer adsorption may occur on both facets, which can lead to different differential binding energies and consequently adsorption crossover between the two facets when the ligand concentration increases. Our combined experimental and computational approaches demonstrate a paradigm for gaining molecular-scale insights into adsorbate–surface interactions.

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

Elucidating Hydrogen Reaction-Induced Water Desorption from Oxide-Passivated Metal Surfaces for Plasma Applications

Elucidating the mechanisms responsible for sub-microsecond desorption of water and other impurities from electrode surfaces at high heating rates is crucial for understanding pulsed power behavior. Ionization of desorbed impurities in the vacuum regions causes power or current loss; devising methods to limit such desorption during the short time scale of pulsed power is needed to improve corresponding applications. Previous molecular modeling studies have strongly suggested that, under high vacuum conditions, the amount of water impurity desorbing from oxide surfaces on metal electrodes is at a sub-monolayer level at room temperature, which appears insufficient to explain observed pulsed power energy losses at high current densities. In this work, we apply Density Functional Theory (DFT) techniques to show that hydrogen trapped inside iron metal can diffuse into hematite (α-Fe 2 O 3 ) on the metal surface, ultimately reacting with the oxide to form Fe(II) and H 2 O. The latter desorbs at elevated temperature and may explain the anomalous amount of desorbed impurity inferred from pulsed-power experiments. We also apply a suite of characterization techniques to demonstrate that when iron metal is heated to 650 °C, the dominant surface oxide component becomes α-Fe 2 O 3 . The oxide facets exposed are found to be a mixture of (0001), (10-10), and others, in agreement with the DFT models used.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Highly Active Rutile TiO 2 Nanocrystalline Photocatalysts

The controllable synthesis of rutile TiO 2 single crystal particles with the preferential orientation of {111} facets still remains a scientific and technological challenge. Here, we developed a facile route for fabrication of rutile TiO 2 nanorod crystals (RTiO 2 NRs) having high ratios of oxidative {111} to reductive {110} surfaces. RTiO 2 NRs were synthesized using a peroxo-titanium complex (PTC) approach, which was controlled by changing the Ti/H 2 O 2 ratio. The thus obtained RTiO 2 NRs revealed a high tendency to agglomerate through orientation-dependent attachment along the {110} facets. This resulted in an increased {111}/{110} surface ratio and led to a markedly improved photocatalytic activity of RTiO 2 NR aggregates. The reported findings illustrate the rich potential of the herein proposed facile and energy-efficient synthesis of nanostructured rutile TiO 2 -based photocatalysts.

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

NO Degradation on the Anatase TiO 2 (001) Surface in the Presence of Water

Nitric oxide (NO) is known to degrade to nitric acid (HNO 3 ) on anatase TiO2 facets under visible light irradiation in the presence of water. However, the exact role that water plays in this photoreaction is not fully understood. Here, by employing the density functional theory (DFT) and time-dependent density functional tight binding (TD-DFTB), we show the viability of two suggested degradation pathways involving water. Both reaction pathways are triggered by a charge transfer excitation from the NO molecule to the TiO 2 surface. In one of them, NO interacts with dissociated water molecules adsorbed on the surface to form HONO + , whereas for the second pathway, NO is oxidized to NO 2 + by capturing one oxygen atom from the substrate. Both HONO and NO 2 are known byproducts in the photodegradation of NO, which further react with adsorbed water to finally produce HNO 3 . We also demonstrate by means of nudged elastic band calculations that these reactions are unlikely to happen without illumination.

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

Conservation management decreases surface runoff and soil erosion

Conservation management practices – including agroforestry, cover cropping, no-till, reduced tillage, and residue return – have been applied for decades to control surface runoff and soil erosion, yet results have not been integrated and evaluated across cropping systems. In this study we collected data comparing agricultural production with and without conservation management strategies. We used a bootstrap resampling analysis to explore interactions between practice type, soil texture, surface runoff, and soil erosion. We then used a correlation analysis to relate changes in surface runoff and soil erosion to 13 other soil health and agronomic indicators, including soil organic carbon, soil aggregation, infiltration, porosity, subsurface leaching, and cash crop yield. Across all conservation management practices, surface runoff and erosion had respective mean decreases of 67% and 80% compared with controls. Use of cover cropping provided the largest decreases in erosion and surface runoff, thus emphasizing the importance of maintaining continuous vegetative cover on soils. Coarse- and medium-textured soils had greater decreases in both erosion and runoff than fine-textured soils. Changes in surface runoff and soil erosion under conservation management were highly correlated with soil organic carbon, aggregation, porosity, infiltration, leaching, and yield, showing that conservation practices help drive important interactions between these different facets of soil health. This study offers the first large-scale comparison of how different conservation agriculture practices reduce surface runoff and soil erosion, and at the same time provides new insight into how these interactions influence the improvement or loss of soil health.

58 GEOSCIENCES↗