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Results for “SURFACES”
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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A Metal-Organic Framework with Nonpolar Pore Surfaces for the One-step Acquisition of C[subscript 2]
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Experimental and numerical study of heat transfer characteristics of single-phase free-surface fan jet impingement with automatic transmission fluid
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A Practical Approach to Wave Function Propagation, Hopping Probabilities, and Time Steps in Surface Hopping Calculations
We compare several established approaches for propagating wave functions and calculating hopping probabilities within the fewest switches surface hopping (FSSH) algorithm for difficult cases with many electronic states and many trivial crossings. If only a single time step (Δt c ) is employed, we find that no published approach can accurately capture the dynamics correctly unless Δt c → 0 (which is not computationally feasible). If multiple time steps are employed, for a fixed classical time step (Δt c ), a robust scheme can be found for dynamically choosing quantum time steps (δt q1 and δt q2 ) and calculating hopping probabilities so that one can systematically reduce all errors and achieve maximally efficient accuracy; scattering calculations confirm that one can choose a fairly large classical time step. Furthermore, the robust scheme presented here uses both the “local diabatic” and adiabatic interpolation and thus borrows elements from both the Granucci/Persico and Meek/Levine algorithms. Our findings should be broadly applicable in the future.
Computational Investigation of the Catalytic Hydrodeoxygenation of Propanoic Acid over a Cu(111) Surface
Cu-based alloy catalysts have recently been investigated experimentally for the hydrodeoxygenation (HDO) of biomass-derived organic acids. Here, the HDO of propanoic acid (PAc) has been studied over Cu(111) by mean-field microkinetic modeling based on parameters obtained from first-principles calculations. Models were developed for the gas- and liquid-phase HDO in condensed water and 1,4-dioxane. In agreement with experimental observations, the gas-phase PAc conversion rate is low at 573 K and increases in liquid water by 1 order of magnitude. In all reaction environments, the decarboxylation mechanism is dominant at low hydrogen partial pressures less than 0.1 bar, and the C–COO bond dissociation is the rate-controlling elementary step. This observation contrasts with the rate-controlling step identified over most group VIII metal surfaces, which is the C–OH bond dissociation in the decarbonylation mechanism. At high hydrogen (H 2 ) partial pressures greater than 10 bar, the HDO of PAc produces propionaldehyde that can readsorb and further react through decarbonylation to produce C 2 alkane products, which is conceptually different from the low H 2 partial pressure scenario. At high H 2 partial pressures, the initial hydrogenation at the carbonyl carbon of PAc becomes the rate-controlling elementary step.
Measuring Relative Energies of Ligand Binding Conformations on Nanocluster Surfaces with Temperature-Dependent FTIR Spectroscopy
We present a method to measure relative energies between binding conformations of carboxylate ligands on InP magic-sized clusters in solution. Using Markov chain Monte Carlo global fitting analysis on temperature-dependent vibrational spectra of cluster-bound ligands, we observe significantly different relative energies between various bidentate and monodentate binding motifs. Relative to the monodentate motif, the chelating conformation is 0.7 ± 0.3 kcal/mol more stable and the syn–syn bridging conformation is 1.1 ± 0.5 kcal/mol more stable, but the syn–anti bridging conformation exhibits no significant difference. Our results demonstrate that the relative energy between monodentate-bound carboxylates and unbound carboxylic acids is 4.52 ± 0.05 kcal/mol, or 1582 ± 19 cm –1 , nearly identical to the carboxylate asymmetric stretching frequency. Here, we suggest that the ligand vibrational energy may play a key role in ligand dissociation by compensating for energy differences between bound and dissociated ligand states. This approach gives important experimental insights into ligand binding and can inform future nanocrystal surface engineering.
Chemical instability at chalcogenide surfaces impacts chalcopyrite devices well beyond the surface
The electrical and optoelectronic properties of materials are determined by the chemical potentials of their constituents. The relative density of point defects is thus controlled, allowing to craft microstructure, trap densities and doping levels. Here, we show that the chemical potentials of chalcogenide materials near the edge of their existence region are not only determined during growth but also at room temperature by post-processing. In particular, we study the generation of anion vacancies, which are critical defects in chalcogenide semiconductors and topological insulators. The example of CuInSe 2 photovoltaic semiconductor reveals that single phase material crosses the phase boundary and forms surface secondary phases upon oxidation, thereby creating anion vacancies. The arising metastable point defect population explains a common root cause of performance losses. This study shows how selective defect annihilation is attained with tailored chemical treatments that mitigate anion vacancy formation and improve the performance of CuInSe 2 solar cells.
Surface decoration accelerates the hydrogen evolution kinetics of a perovskite oxide in alkaline solution
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A hole-transport material that also passivates perovskite surface defects for solar cells with improved efficiency and stability
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Evolution of surface and sub-surface morphology and chemical state of exsolved Ni nanoparticles
Dynamic surface and subsurface morphology and chemistry of socketed nanoparticles is monitored in situ for an important emerging class of nanoparticles.
Rotational Dynamics and Transition Mechanisms of Surface-Adsorbed Proteins
Assembly of biomolecules at solid-water interfaces requires molecules to traverse complex orientation-dependent energy landscapes through processes that are poorly understood, largely due to the dearth of in-situ single molecule measurements and statistical analyses of the rotational dynamics that define directional selection. Emerging capabilities in high-speed atomic force microscopy and machine learning have allowed us to directly determine the orientational energy landscape and observe and quantify the rotational dynamics for protein nanorods on the surface of muscovite mica under a variety of conditions. Comparisons with kinetic Monte Carlo simulations show that the transition rates between adjacent orientation-specific energetic minima can largely be understood through traditional models of in-plane Brownian rotation across a biased energy landscape, with resulting transition rates that are exponential in the energy-barriers between states. However, transitions between more distant angular states are decoupled from barrier height, with jump-size distributions showing a power-law decay that is characteristic of a non-classical Levy-flight random walk, indicating that large jumps are enabled by alternative modes of motion via activated states. The findings provide new insights into the dynamics of biomolecules at solid-liquid interfaces that lead to self-assembly, epitaxial matching and other orientationally anisotropic outcomes and define a general procedure for exploring such dynamics with implications for hybrid biomolecular-inorganic materials design.
Studies of Reactive Amorphous Compounds and Surfaces: Their Pathways to Crystallinity and Surface Functionality
This project was originally headed by Dr. Abraham Clearfield (Texas A&M University, ret.) and focused on developing structural models of zirconium phosphate (ZrP) based materials at different stages of crystalline order using PDF techniques developed by co-PI Dr. Simon Billinge (Columbia University). When Dr. Clearfield retired, the project was taken over by Dr. Hong-Cai Zhou (Texas A&M University). The project proposed looking at defective metal-organic frameworks (MOFs) supported on the surface of the ZrP materials. During the project, the personnel conducted studies of the dispersion of different phosphate ligands in mixed organic phosphonates, and how they could be utilized to incorporate different metals within the ZrP interlayer spacing.
Impact of surface growth method and surface treatment in niobium-based superconducting devices
We explore the comparison between two growth methods for niobium film - sputtering and electron-cyclotron resonance growth - for niobium-based superconducting resonators. We discuss some of the key properties of the films, including surface characterization and residual resistance measurements metrics. We present our design of various devices used in this study including superconducting resonators and qubits, both in planar configurations and integrated in 3D cavities, as well as experimental characterization of coherence metrics.
Surface Meteorological Station - BAO West of Tower, Surface - Processed Data
Proving basic surface meteorology, soil hydrology and temperature, and fluxes of energy (radiation and turbulent fluxes) and water (precipitation, evaporation, and soil moisture).
Synthesis of ARM User Facility Surface Rainfall Datasets to Construct a Best Estimate Value Added Product (PrecipBE)
Surface precipitation measurements are essential for Earth system model (ESM) evaluation and understanding cloud processes. An ever-growing need for robust, temporally evolving, and easy-to-use statistical datasets provides motivation for a baseline ground-based precipitation properties data product. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility operates an extensive suite of precipitation instruments with various sensitivities and operating mechanisms, which render the decision of which instrument to use based on one or more fixed thresholds challenging and prone to errors and bias. Using a long-term instrument inter-comparison from a unique per-precipitation event perspective, rather than instantaneous sample comparison, we demonstrate that ARM rainfall-measuring instruments are generally consistent with each other at the statistical level. Inter-instrument deviations at the single event level can be large, especially for specific rainfall event properties such as maximum precipitation rates. A machine-learning (ML) analysis using a random forest regressor indicates that in some cases, depending on instrument, local site climatology, and/or specific deployment configuration, certain atmospheric state variables influence the measured quantities in an unpredictable manner. Thus, a-priori weighting of different instruments does not necessarily lead to more accurate and less biased synthesis of instrument data. These results motivate the design of the ARM precipitation best-estimate (PrecipBE) value-added product, which incorporates all valid precipitation data while considering data quality and other instrument limitations. PrecipBE consists of time series and tabular statistics datasets in an easy-to-use and insightful per-precipitation event format. It provides a large set of precipitation event properties supplemented with ancillary data from ARM datasets that correspond to the detected precipitation events. We describe the PrecipBE algorithm and demonstrate its use via the examination of a single-day output as well as a long-term trend analysis of precipitation events at the ARM Southern Great Plains (SGP) site, covering more than 30 years of data. The trend analysis tentatively suggests a long-term temporal tendency for mainly shorter and less intense precipitation events at the SGP site, but a long-term increase in annual rainfall by more than 36 mm (5 %) per decade. This rainfall trend is catalyzed primarily by more extreme event properties of relatively rare, intense precipitation events, with event total and 1 min maximum precipitation rate at a 1 year timeframe increasing up to 5 mm and 9 mm h −1 (several percent) per decade, respectively. While the currently available PrecipBE datasets (at https://adc.arm.gov/discovery/, last access: 8 December 2025) cover rainfall from multiple ARM deployments up to March 2025, PrecipBE is planned to be expanded to include solid-phase precipitation and will soon become an operational product with a several-day lag from real-time. We invite the ARM user community to leverage this new product and welcome user feedback to further enhance the dataset.
Investigation of Nano-fin Effect (NFE) for Pool Boiling on Nanostructured Surfaces Using Surface Micromachined Temperature Nanosensors
Study of subcooled pool boiling experiments performed using a dielectric coolant to test effects of variations in heater surface configuration on pool boiling characteristics.