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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models

Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's n). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Structure and Sulfur: Tuning the Viscoelastic and Surface Properties of Natural Keratin Fibers

Natural keratin fibers, such as wool, possess a complex hierarchical structure that governs their mechanical properties and surface energy. However, the extent to which these characteristics are influenced by combined contributions of structural variations (e.g., fiber diameter, intermediate filament (IF) packing) and chemical composition (e.g., disulfide bond density) remains poorly understood. In this study, we investigate wool fibers from five sheep breeds (Merino, Polwarth, Cheviot, Eider, and Devon) to elucidate how these factors influence viscoelasticity and surface interactions. Using a multimodal approach integrating interfacial and bulk characterization methods, including inverse gas chromatography (IGC), atomic force microscopy-infrared spectroscopy (AFM-IR), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and synchrotron small-angle X-ray scattering (SAXS), we show that the nanometer-thick 18-methyleicosanoic acid (18-MEA) layer is consistently present across all wool types and plays a key role in governing hydrophobicity and surface heterogeneity. A controlled isothermal treatment at 200 °C, designed to cleave disulfide bonds, results in a nearly 40% reduction in specific surface area across all fiber types, accompanied by a significant decrease in tensile strength and 80% reduction in elongation at break for Merino and Devon wool, but limited influence on the mechanical properties of Eider fibers. Furthermore, rate-dependent tensile testing within the elastic regime reveals distinct viscoelastic responses among the fiber types, suggesting that the sulfur-rich protein matrix surrounding IFs and its structure contribute actively to stress partitioning. Altogether, when combined with conclusions from SAXS measurements of IF spacing, our work offers compelling insights into the role of the keratin-associated protein (KAP) matrix in shaping wool fiber mechanics. Differences in mechanical behavior among wool types, despite similar IF spacing or sulfur content, highlight the importance of matrix composition and cross-linking density, suggesting that the molecular architecture of the KAP network may be a dominant factor in determining fiber performance.

X-ray scattering↗
DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2026

Variation in surface properties as error sources in dynamic temperature measurements

Most temperature measurement methods rely upon the assumption of a single uniform source as part of the analysis in inferring an observed temperature T from the surface of a material. This is true for the radiometric and spectroscopic methods we rely upon in shock physics. However, there are obvious cases where this is a poor assumption that can cause large errors in analysis, such as the measurement of emission from a surface composed of more than one material, such as a rusted surface of Fe and Fe 2 O 3 , or a multi-material surface that could be produced through alloying methods (e.g., mokume gane) or 3D printing. Here we perform an initial examination of the effects of varied surface properties upon the analysis using idealized test data to constrain when we may have better confidence in the resulting calculations. We also examine the structures of the fits to test whether, in principle, comparing the fit with ideal gray bodies would reveal such a structure and enable the researcher to identify when a two-temperature fitting model should be used instead of a single- T model or a wavelength-dependent emissivity model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effects of size of an oxide layer on the surface properties of lithium irradiated by deuterium plasma

We investigate how growth of an oxide film will influence the deuterium recycling properties of Li on plasma facing surfaces. Lithium films on the walls or plasma-facing material surfaces of a fusion vacuum vessel improves plasma performance in part by removing residual impurity atoms from the plasma. Oxygen atoms, from residual water vapor or eroded oxide surfaces, are a prominent ubiquitous impurity that can create a layer of oxide on lithium films. The results of the work herein also indicate a possibility for determining the thickness of the oxide layer on such Li films by measuring the reflection probability of incident deuterium particles from the surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling

High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth system models (ESMs) and ultra-high-resolution urban climate modeling, over large domains. Here, we present U-Surf, a first-of-its-kind 1 km resolution present-day (circa 2020) global continuous urban surface parameter dataset. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for satisfying dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet and canopy level. Generated using a systematically unified workflow, U-Surf ensures internal consistency among key parameters, making it the first globally coherent urban canopy surface dataset. U-Surf significantly improves the representation of the urban land heterogeneity both within and across cities globally; provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs; enables detailed city-to-city comparisons across the globe; and supports next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf can also be used as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to advance the research frontier of urban system science, climate-sensitive urban design, and coupled human–Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247598 (Cheng et al., 2024).

Cheng, Yifan [Univ. of Illinois at Urbana-Champaig↗
DOE OSTI2025

Snow ALbedo eVOlution (SALVO) Campaign Snow Depth and Related Surface Properties from April - June, 2024 in Utqiagivk, AK

Detailed transects of snow depths and related measurements were made with a magnaprobe along fixed lines in Utqiagvik, AK. The operator measures snow depth by plunging a rod with a sliding basket into the snow and pressing a trigger. At this point, the data logger records the distance between the tip of the rod and the height of the basket, the measurement number, the time, and the geographic location of the measurement. To measure snow depth, the rod tip must be placed at the snow-ground or snow-sea ice interface. The interface can be hard or soft; in the latter case, it is possible to “over-probe”, producing a snow depth that is too high. At times, the probe was also used to measure the depths of other interfaces within the snowpack (for example, the depth to persistent ice lenses) or the water depths of ponds atop the tundra or sea ice. When these alternative depth measurements were made, the operator recorded the location, measurement number, and composition of the alternative depth measurement in a field notebook. The data logger on the probe stores several thousand points. Data is downloaded to a computer at the end of a day or several days. Probes: We used 2 magnaprobes identified as GEO1 and GEODEL with the following serial numbers: S/N 20240416 (GEO1) and S/N P48066 (GEODEL). Note : There are three data levels available with this dataset: b3, b4, and a6. New users of these data are strongly encouraged to use the level a6 or b4 data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗
DOE OSTI2025

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.

58 GEOSCIENCES↗
DOE OSTI2025

Probing Alkylpolyglycoside Hydrogen Bonding and Its Destabilization by Sulfonate Hydrotropes with X‑ray and Vibrational Spectroscopy

It has been proposed that intersurfactant H-bonding networks can produce highly stable foams, specifically those generated from solutions containing alkylpolyglycoside surfactants. In this work, we aim to characterize the presence and destabilization of these networks by introducing a hydrotrope (sodium p-toluene sulfate) at various concentrations into an alkylpolyglycoside (Glucopon 225 DK) surfactant containing solution. Solution surface properties are probed by using aerosol velocity map imaging X-ray photoelectron spectroscopy (A-VMI-XPS) and tensiometer measurements. Bulk properties below the surface are probed using Fourier transform infrared spectroscopy (FTIR) and C-edge near-edge X-ray fine structure spectroscopy (NEXAFS). The surface measurements provide the framework to describe the destabilization of the solution H-bonding network, while the bulk solution measurements provide hints about the disruption of the hydrogen bonding network upon hydrotrope addition. The collected data support the hypothesis that the destabilization of the intersurfactant H-bonding network frees surfactant molecules from the bulk, increasing surfactant population at the air/water interface. This was quantified through an increase in peak area and width in XPS measurements as well as a decrease in surfactant critical micelle concentration. Three regimes with increasing amounts of hydrotrope addition are suggested, described as (1) a hydrotrope affecting only surfactant surface properties, (2) a hydrotrope affecting surfactant surface and bulk properties, and (3) hydrotrope-dominated surface and bulk properties. Future studies will characterize foam stability across the hydrotrope concentration regimes to better define correlations between intersurfactant H-bonding networks and foam stability.

Molecules↗
DOE OSTI2024

Enhanced rare earth element recovery with cross-linked glutaraldehyde-lanthanide binding peptides in foam-based separations

Lanthanide Binding Tag (LBT) peptides that coordinate selectively with lanthanide ions can be used to replace the energy intensive processes used for the separation of rare earth elements (REEs). These surface-active biomolecules, once selectively complexed with the trivalent REE cations, can adsorb to air/aqueous interfaces of bubbles for foam-based REEs recovery. Glutaraldehyde, an organic compound that is a homobifunctional crosslinker for proteins and peptides, can be used to enhance the adsorption and interfacial stabilization of lanthanide-bound peptides films. The stability of the interfacial cross-linked films was tested by measuring their dilational and shear surface rheological properties. Surface activity of the adsorbed species was analyzed using pendant drop tensiometry, while surface density and molecular arrangement were determined using x-ray reflectivity and x-ray fluorescence near total reflection. Glutaraldehyde cross-linked REE-peptide complexes enhance the adsorption of lanthanides to air-water interfaces, resulting in thicker interfacial structures. Subsequently, these thicker layers enhance the dilational and shear interfacial rheological properties. The interfacial film stabilization and REEs extraction promoted by the cross-linker presented in this work provides an approach to integrate glutaraldehyde as a substitute of common foam stabilizers such as polymers, surfactants, and particles to optimize the recovery of REEs when using biomolecules as extractants.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dynamic control of molecular transport MXene transistor membranes

Controlled spatial confinement and surface properties of lamellar 2D nanomaterial membranes could enhance many precision separation processes. Traditionally, researchers view channel dimensions, surface properties, and permeation rates of these membranes as intrinsic properties that cannot be modulated in operando. We report that gate voltage applied to the conducting laminar MXene membrane can modulate the permeation rate of ions and neutral solutes, as well as its effective size rejection. In operando wide-angle x-ray scattering measurements reveal that these changes are not driven by electrically induced variations in the d spacing of the MXene layers. Instead, experimental data and continuum electrokinetic modeling reveal that ion transport through the MXene channels is primarily affected by Donnan equilibrium at the membrane-solution interface. We also report a strong increase in the permeation rates through the membrane under a low-frequency ac voltage gating regime that we attribute to diffusioosmotic flow oscillations induced in the membrane. Overall, MXene “transistor” membranes provide a previously unidentified approach to dynamic control of molecular separations.

Pendse, Aaditya [Lawrence Livermore National Labor↗
DOE OSTI2025

Oxygen Evolution on Mechanically Strained TiO2/NiTi: Implications of Compositional Heterogeneity at (Photo)Electrocatalytic Interfaces

The adsorption and activation energetics underpinning small molecule conversion on heterogeneous (photo)electrocatalysts are intrinsically tied to catalyst surface properties. Absent compositional characterization techniques with sufficient interface sensitivity, however, (photo)electrochemical performance can be misinterpreted in the context of bulk or near-surface material properties. Here we provide a fundamental investigation of the convoluting role of near-surface compositional heterogeneity in the interpretation of (photo)electrochemical alkaline oxygen evolution reaction (OER) activity, highlighting challenges in correlating composition measured by surface- and near-surface-sensitive probes. TiO2 thin films grown by air-annealing the superelastic alloy Nitinol (TiO2/NiTi) crack under tensile mechanical strain, increasing the number of electrochemically active Ni sites (Ni site density) that are probed via voltammetric features corresponding to Ni3+/Ni2+ redox events. (Photo)electrochemical OER kinetics trend with Ni site density, with overpotentials and Tafel slopes decreasing for Ni site densities < 1013 Ni/cm2geo and asymptotically approaching the performance of the base NiTi substrate for Ni site densities > 1013 Ni/cm2geo. Photoelectrochemical fill factors follow similar Ni site density dependent trends. When probing unstrained TiO2/NiTi, Ni site densities are two orders of magnitude higher when comparing near-surface-sensitive techniques (e.g., X-ray photoelectron spectroscopy (XPS), time of flight secondary ion mass spectrometry (TOF-SIMS), and scanning transmission electron microscopy-energy dispersive X-ray spectroscopy (STEM-EDS)) to surface-sensitive electrochemical measurements. This result highlights the challenge of correlating kinetic performance with intrinsic surface properties of electrochemical interfaces in the presence of near-surface compositional heterogeneity. Further, it reinforces the importance of fundamental investigations of surfaces with well-controlled composition and structure and the need for physically grounded and self-consistent interpretation of multiple near-surface characterization techniques.

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

Decoupling plasma, catalyst, and gaseous mechanisms for non-oxidative methane conversion

Direct non-oxidative methane (CH 4 ) conversion to value-added hydrogen (H 2 ) and C 2 products remains hindered by fundamental catalytic scaling constraints and rapid surface deactivation at elevated temperatures. Plasma-enabled catalysis offers a promising route to overcome the thermodynamic and kinetic barriers of direct non-oxidative methane upgrading at mild conditions, yet control over C–C product selectivity and catalyst stability remains elusive. Here, we establish a unified mechanistic framework including Langmuir–Hinshelwood (L–H) and Langmuir–Rideal (L–R) mechanisms that disentangles the roles of plasma excitation (including vibrationally activated species and radicals), surface temperature (T sur ), and catalyst binding energy in steering CH 4 conversion to H 2 and C 2 hydrocarbons. Through a combination of density functional theory (DFT) informed microkinetic modeling, in situ and ex situ surface characterization, and product quantification under dielectric barrier discharge conditions, we show that vibrationally excited CH 4 lowers activation barriers selectively for dissociative chemisorption, enabling surface activation across a wide range of transition metal catalysts at low thermal energy input. We find that once CH 4 is dissociatively chemisorbed, the branching between C 2 H 2 , C 2 H 4 , and C 2 H 6 is governed by surface properties (carbon binding energy, T sur , etc), regardless of plasma excitation. The DFT informed microkinetic model decouples the effects of molecular activation from surface properties and indentifies operating windows that maximize target yields while suppressing carbon accumulation and subsequent catalytic inactivation. Experiments on polycrystalline Cu/Al 2 O 3 , Ni/Al 2 O 3 , and Pt/Al 2 O 3 validate these predictions, revealing catalyst-dependent branching toward ethane or ethylene and distinct deactivation profiles. We unify these trends into a generalized three-dimensional plasma-thermal-catalytic design space, from which reduced descriptors such as T vib /T sur in the limit of vibrationally excited L–H pathways emerge as predictive metrics. These results enable rational tuning of methane conversion pathways and unlock selective C 2 formation using earth-abundant metals under mild plasma conditions.

catalyst inactivation↗
DOE OSTI2025

Investigating the Global Biogeophysical Impact of Area and Mass Based Wood Harvest in a Vegetation Demography Model

Wood harvesting alters land surface properties and energy redistribution, but there is a lack of studies estimating these changes on a global scale. We coupled a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator, with the E3SM land model to perform offline model simulation to investigate the land biogeophysical responses, including canopy coverage, leaf area index, albedo, surface roughness length, and energy fluxes, to historical wood harvest on the global scale. In this study, we found 50% less harvested carbon (C) when choosing the area-based harvest rate as driving data that has not been spatially harmonized, compared to reharmonized mass-based harvesting. By considering the uncertainty from reconstruction of historical wood harvest time series and the choice of wood harvest approach in the model, continuous wood harvest (1850–2015) results in 5%–10% of canopy coverage loss, contributing 0.5%–1% increase of albedo over disturbed land, which is much stronger than a non-demographic land surface model. Changes in energy flux from the wood harvest are negligible (<1%), but the responses of land surface properties vary (up to 30%) due to differences in model structure between the single canopy, sun-shade leaf model and vegetation demographic model.

Shu, Shijie [Lawrence Berkeley National Laboratory↗
DOE OSTI2024

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet. Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction. Plain Language Summary: Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions. Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optical and photoelectric properties of surface barrier diodes based on n- Hg3In2Te6 crystals

The high radiation resistance of Hg3In2Te6 (MIT) single crystals to large doses of ionizing radiation makes devices quite attractive. Such a feature of the crystal structure has not only important advantages, but also causes serious technological difficulties in doping and controlling the specific resistance within the required limits and type of conductivity of single crystals. These technological difficulties create serious problems when creating structures with a potential barrier, especially with a p-n junction. At the moment, there are no publications on the creation of a p-n junction based on MIT. The only alternative is to create a potential barrier such as a Schottky diode or a metal-dielectric-semiconductor structure. This limits the use of MIT to produce, for example, rectifier diodes that can operate at relatively high reverse bias voltages. The typical resistivity of single crystals of MIT of n-type conductivity, which are used for the manufacture of diodes and photodiodes, is approximately equal to ρ≈103-104 Ω×cm. Such a specific resistance leads to a relatively large resistance of the neutral part of the single crystal, which in turn limits the direct currents of the rectifier diodes and significantly limits an important parameter of photodiodes - the dynamic range of the watt-ampere characteristic. This problem arises from the relatively high series resistance of the substrate. For rectifier diodes, this relatively large series resistance leads to a significant forward bias voltage drop, which reduces both the rectification factor and the amount of rectified current. We have already created diodes and photodiodes on Cr/MIT/Cr single crystals with a specific resistance of ρ≈103-104 Ω×cm. The diodes had relatively small dark currents but had the disadvantage of a relatively large specific resistance of the substrate, which we have already discussed above [1,2,3].

Sklyarchuk, V.↗
DOE OSTI2024

Atomic structure of different surface terminations of polycrystalline ZnPd

The intermetallic compound ZnPd has been found to have desirable characteristics as a catalyst for the steam reforming of methanol. The understanding of the surface structure of ZnPd is important to optimize its catalytic behavior. However, due to the lack of bulk single-crystal samples and the complexity of characterizing surface properties in the available polycrystalline samples using common experimental techniques, all previous surface science studies of this compound have been performed on surface alloy samples formed through thin-film deposition. In this study, we present findings on the chemical and atomic structure of the surfaces of bulk polycrystalline ZnPd studied by a variety of complementary experimental techniques, including scanning tunneling microscopy (STM), x-ray photoelectron spectroscopy (XPS), low energy electron microscopy (LEEM), photoemission electron microscopy (PEEM), and microspot low-energy electron diffraction ( μ -LEED). These experimental techniques, combined with density functional theory (DFT)-based thermodynamic calculations of surface free energy and detachment kinetics at the step edges, confirm that surfaces terminated by atomic layers composed of both Zn and Pd atoms are more stable than those terminated by only Zn or Pd layers. DFT calculations also demonstrate that the primary contribution to the tunneling current arises from Pd atoms, in agreement with the STM results. The formation of intermetallics at surfaces may contribute to the superior catalyst properties of ZnPd over Zn or Pd elemental counterparts. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗