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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 91 records · Page 5

Variation in Cation Adsorption Mechanism Controlled by Chemical and Structural Heterogeneities at the Quartz (101)–Water Interface

Mineral–water interfacial reactions are central to chemical processes that control the fate of nutrients and contaminants in natural environments. Mineral surfaces commonly have complex structures and compositions whose impact on interfacial reactivity is poorly understood. Here, in this work, we investigated the effects of surface heterogeneities on Rb + sorption at the quartz (101)–10 mM RbCl solution interface at pH 9.8 using in situ high-resolution X-ray reflectivity. Two surface locales (i.e., Spots A and B) having distinct interfacial structures were chosen: Spot A was characterized by its low defect density (≤20% topmost Si vacancies) and Rb + adsorption occurred predominantly as an inner-sphere complex. In comparison, Spot B had a higher defect density (~50% vacancies) and was covered with poorly crystalline SiO 2 . A substantially larger Rb + uptake (i.e., 7-times higher coverage) was observed on this defective surface where Rb + incorporated in the vacancy sites (confirmed by density functional tight binding-based molecular dynamics simulations) or adsorbed directly on the disordered film. These results provide a direct quantification of how surface heterogeneity influences the geochemical behavior of mineral–water interfaces, in particular highlighting the important role of chemical and structural defects on the sorbate speciation and coverage at silicate mineral surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulation and measurement of the dynamic strain response in a prototypical spallation target

The Second Target Station (STS) at the Spallation Neutron Source (SNS) will address emerging scientific challenges by providing a source of intense cold neutrons to instruments optimized for this source. The STS target will use rotating tungsten blocks and will receive 1.3 GeV proton beam pulses from the SNS accelerator at a repetition rate of 15 Hz. The facility life is planned for 40 years, and each target assembly life is expected to be approximately 10 years. An accurate strain prediction is then critical for fatigue life assessment of STS target blocks because they will be subject to approximately 10 8 beam pulses per lifetime. As an R&D activity, the Los Alamos Neutron Science Center (LANSCE) Weapons Neutron Research (WNR) Target 2 (Blue Room) facility was used to test the strain response of prototypical target blocks to the thermal shock of a proton pulse. The blue room was well suited for a pulsed proton beam impact test of subscale STS target blocks; the 800 MeV proton energy is approximately 60 % of the 1.3 GeV proton energy expected from the SNS accelerator to the STS. The LANSCE Proton Storage Ring (PSR) and SNS are both short-pulse proton beam sources with nominal pulse widths of 250 ns and 661 ns, respectively, so the energy deposition in the target occurs in <1 μs pulse duration. Strain measurements on the outer surface of three target blocks (bare tungsten, tantalum-clad tungsten, niobium-clad tungsten) were recorded for comparison against neutronics and structural simulations. In conclusion, this experiment and the supporting simulations satisfied the following primary research goals for the STS target.

Dynamic strain response↗

Climate Conundrum: A Wet or Dry European and Northern African Climate During the Middle Miocene

Abstract End of 21st‐century hydroclimate projections suggest an expansion of subtropical dry zones, with Mediterranean and Sahel regions becoming much drier. However, paleobotanical assemblage evidence from the middle Miocene (17‐12 Ma), suggests both regions were instead humid environments. Here we show that by modifying regional sea surface temperatures (SST) in an Earth System Model (CESM1.2) simulation of the middle Miocene, the increased ocean evaporation and integrated water vapor flux overrides any drying effects associated with warming‐induced land‐surface evaporation driven by atmospheric CO 2 concentrations. These modifications markedly reduce the bias in the model‐data comparison for this period. A vegetation model (BIOME4) forced with simulated climatologies predicts both regions were dominated by mixed forest, which is largely consistent with the paleobotanical record. This study unveils the potential for wetter subtropical Mediterranean climates associated with warming, presenting an alternative scenario from future drying projections with localized SST warming governing regional climate change.

Acosta, R. P.↗

Comparison of theory with the experimental characterization of the spatial frequency response of interferometers using a binary pseudo-random array sample

Experimental evaluations of the surface height response of an interference microscope using a binary pseudo-random array test sample are compared with a theory based on a Fourier optics model. Measurements of key instrument characteristics, including the illumination, imaging, and obscuring apertures of three different Mirau objectives, support the theoretical calculations. Agreement between experimental and theoretical modeling confirms the predictability of the spatial frequency response for the purpose of specification and optimization of instrument configuration for specific metrology tasks. The results also provide confidence in methods of compensating for the decrease in instrument response with spatial frequency.

Calibration↗

BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze the electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain a granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage.

database↗

Resolution of Selectivity Steps of CO Reduction Reaction on Copper by Quantum Monte Carlo

Electrochemical reduction of carbon monoxide to valuable fuels and chemicals on copper surfaces remains a challenging area in catalysis due to a limited understanding of adsorption mechanisms and reaction pathways. Although density functional theory (DFT)-based studies have investigated these processes, their accuracy varies across different functionals. Here, in this study, we present the application of fixed-node diffusion Monte Carlo (FNDMC) to benchmark the adsorption energies of CO*, H*, and key CO reduction reaction (CORR) intermediates, COH* and CHO* on the Cu(111) surface. Our results for CO* and H* adsorption energies closely align with experimentally measured chemisorption reactions, highlighting the limitations of DFT and providing site-specific energy comparisons that are often not available experimentally. Additionally, we explore the effect of explicit solvation, demonstrating how water stabilizes the COH* over CHO*, thus suggesting a critical role of COH* in CORR. Finally, we release our high-accuracy FNDMC benchmarks for testing and developing new DFT functionals for electrocatalysis. Overall, this study underscores the potential of FNDMC for detailed surface chemistry studies and offers new insights into catalytic processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressure Transducer Measurement Variability in Deep Wells Screened Across the Water Table

Abstract Automated water level measurements collected using vented pressure transducers in deep wells screened across the water table may exhibit a greater response to barometric pressure changes than the true water level. The cause was hypothesized to be disequilibrium in barometric pressure between the wellbores and land surface due to air exchange with the deep vadose zone. In this study, vented and nonvented pressure transducers were installed and operated simultaneously in two deep wells screened across the water table. A vent tube open to the atmosphere at land surface allowed for barometric compensation of the vented transducers. Two nonvented transducers were installed in each well, one submerged in the water and one above the water surface. The difference in readings allowed for barometric compensation. Manual measurements were also collected. It was confirmed that measurements from the vented transducers exhibited greater variability in response to barometric pressure changes than the nonvented transducers and manual measurements. Comparison of the downhole barometric pressure measurements to values from a nearby meteorology station showed the response in the wells to changes in barometric pressure was time‐lagged and attenuated. Thus, the reference pressure from land surface supplied to the vented transducers was not representative of the air pressure within the wells. This caused fluctuations of the transducer readings in response to barometric pressure changes to be greater than the true water level change. This issue can be resolved by the use of nonvented pressure transducers.

McDonald, John P.↗

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗

Temperature Dependent Early-Stage Oxidation Dynamics of Cu(100) Film with Faceted Holes

Fundamental understanding of surface oxidation dynamics is critical for rational corrosion protection and advanced manufacturing of nanostructured oxides. In situ environmental TEM (ETEM) provides high spatial (nano- to atomic- scale) and temporal (< 0.1 s) resolution to investigate the early-stage oxidation/corrosion dynamics of metals and alloys. Thin samples with facets are widely used to enable cross-sectional observation of the oxidation dynamics in ETEM. However, how different facet orientations oxidize under the same conditions, and how these facets change the oxidation process, has not been investigated before. Here, using in situ ETEM, we systematically compare the oxidation dynamics of Cu(001) thin films, with faceted holes exposing {100} and {110} facets at temperatures ranging from 250–600 °C under 0.03 Pa O 2 . Oxidation preference is observed to change, from Cu(110) facets at lower temperatures to Cu(100) facets at ~ 500 °C. Oxide growth mechanisms change from outward growth on Cu 2 O surfaces at low temperatures, to inward growth on Cu-Cu 2 O interfaces at high temperatures. At high temperatures (500–600 °C), a rod-like Cu 2 O morphology is observed, with side facets of ~ {024} and top facets of {100} on Cu(100). This differs from the square-shaped Cu 2 O exposing {110} facets formed on Cu(001) surfaces. Rod-like oxides exhibit directional growth along their lengths with linear growth rates, regardless of rod length and width. This suggests that O from Cu(001) surfaces, rather than Cu(100) facets, serves as an O source for oxide growth. These results show a direct comparison of oxidation at different orientations with temperature, underscoring the temperature dependence of oxidation preference. Our results also suggest future in situ ETEM experiments viewing oxidation corrosion cross-sectionally should be cautious when oxide size is comparable with sample thickness, as the oxidizing mechanism may change due to sample thickness.

36 MATERIALS SCIENCE↗

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗

Detailed simulations of the first deuterium-tritium-filled double shell implosions on the National Ignition Facility

The first indirectly driven, liquid DT-filled double shell inertial confinement fusion (ICF) implosions have recently been successfully performed on the National Ignition Facility (NIF). Double shells are a class of alternative designs that use a low-Z outer shell to compress a foam cushion that accelerates a high-Z inner shell to efficiently compress a liquid DT core. Double shells are challenging to fabricate, field, and model. Important engineering features enabling double shell fabrication include a fill-tube penetrating all shells and a carefully designed and very narrow (few μm) step-joint in the ablator. Due to the higher density materials involved, high Atwood number instabilities are also important at many material interfaces. In this paper, numerical simulations of double shell implosions using the Los Alamos National Laboratory multi-physics radiation-hydrodynamics code xRAGE will be discussed. An extensive effort has been under way for several years to develop the code capabilities for ICF simulations in a common modeling framework to allow ease of simulation setup and standardization of the computational methodology. This paper will present a wide range of simulation results capturing, quantifying, and comparing the impact of all these degradation mechanisms on implosion performance. Brief comparisons with recent experimental results and suggestions for future improvements will also be discussed. Our results suggest that capsule surface roughness and the step-joint gap have the largest impact on implosion performance. Initial experimental data may suggest that the sensitivity to the step-joint gap could provide the dominant explanation for DT-filled double shell experiments that have been fielded on NIF thus far.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Pore-Scale Study on the Positive Feedback Between Stress and Porosity Caused by Pressure Solution in Porous Media

Pressure solution is an important process in the evolution of sedimentary rocks, which provide storage space for most of our petroleum resources. It directly influences the generation, migration, and storage of petroleum fluids in subsurface sedimentary rocks. Here, in this paper, we develop a pore-scale, mechanochemical model to demonstrate a possible positive feedback between the local porosity and pore surface stress, in which a higher local porosity causes a higher local pore surface stress, thus enhancing pressure solution and consequently further increasing the local porosity. Pore surface stress represents stress on a solid grain adjacent to a pore. Specifically, the pore-scale, mechanochemical model directly simulates the stress distribution over solid and pore surfaces using a finite element model. The dissolution of solids at the solid-pore interfaces under a far-from-equilibrium condition is simulated using a first-order kinetics model that accounts for the local stress distribution. The updated pore geometry, caused by pore surface dissolution, is then used in the stress simulation in the next numerical iteration. Two types of porous media, the Oriskany sandstone and an artificial porous medium with spherical pores, were tested in the mechanochemical simulation. The positive stress-porosity feedback during pressure solution was observed in both samples. In addition, the model quantitatively illustrated the distribution of local mineral dissolution rates on all pore surfaces, as well as its relation to the effective mineral dissolution rate of the entire sample. Based on the comparison between the two porous media, the local mineral dissolution was regulated by pore space distribution, geometry, and coalescence during pressure solution. This work is the first that uses direct, pore-scale numerical simulation to demonstrate the positive stress-porosity feedback during pressure solution, which has the potential to advance the understanding of the mechanical-chemical (MC) coupling in many geological processes that are relevant to subsurface energy systems, such as the recovery of petroleum hydrocarbons and geothermal energy.

CT scanning↗

Characterizing model uncertainties in simulated coast-to-offshore wind over the northeast U.S. using multi-platform measurements from the TCAP field campaign

Numerical weather prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, are widely used to provide estimates of the offshore wind energy resource owing to their large spatial coverage compared to available observations. Nevertheless, spatiotemporal distribution of model biases is highly dependent on factors including model configuration, location, and the interplay of multi-scale physical processes. Here, in this study, we focus on the characterization of model uncertainties in simulated coast-to-offshore winds over the northeast U.S., by varying sea surface temperature (SST) forcings, surface layer (SL) and planetary boundary layer (PBL) parameterizations, as well as identifying biases that may be directly passed from initial and boundary conditions. Multiple measurements, including aircraft data collected during the U.S. Department of Energy's Two-Column Aerosol Project (TCAP) experiment, are used to constrain the model results and facilitate quantitative comparisons. Our analysis indicates while SST forcing has notable impacts on simulated air temperature and moisture within PBL, the modeled winds are in general more sensitive to the choices of SL and PBL physics than to SST. The model’s forcing data not only controls the vertical dependence of wind speed errors, but also alters regional variability in wind speed’s spatial correlation. Bias comparisons between ERA5 reanalysis and ensemble simulations revealed significant similarity, particularly in wind speed biases during winter, underscoring their dependency on initial and boundary conditions. Coastal and offshore near-surface wind speed biases tend to exhibit much higher similarity in winter than in summer due to the presence of much stronger and more persistent synoptic wind conditions. This study highlights the importance of accurate atmospheric forcing and parameterization choices in improving wind forecasts and suggests the potential for extrapolating coastal wind biases to offshore locations, aiding wind energy forecasting and informing the Wind Forecast Improvement Project-3 (WFIP3).

17 WIND ENERGY↗

The relative importance of wind and hydroclimate drivers in modulating the interannual variability of dust emissions in Earth system models

Windblown dust emissions are controlled by near-surface wind speed and sediment erodibility, the latter modulated by hydroclimate and land-use conditions. Accurate representations of these drivers are critical for reproducing historical dust variability and projecting future dust changes in Earth system models (ESMs). This study examines the discrepancies among 21 ESMs in the relative importance of wind speed versus five hydroclimate drivers in explaining the historical (1980–2014) variability of dust emissions from global drylands. In hyperarid areas, models show poor agreement in the simulated dust variability, with only 9 % out of 210 inter-model comparisons exhibiting significant positive correlations. In contrast, arid and semiarid areas exhibit a dual pattern driven by a “double-edged sword” effect of land surface memory: models with coherent hydroclimate variability show better agreement, whereas those with divergent hydroclimate representations show larger disagreement. While the ESMs capture the dominant role of wind speed in hyperarid areas, they diverge markedly in the relative contributions of wind and hydroclimate drivers in arid and semiarid areas. Replacing the Zender et al. (2003) dust scheme with the Kok et al. (2014) scheme in CESM and E3SM generally strengthens hydroclimate influences while reducing wind speed contributions to simulated dust variability. MERRA-2 reanalysis produces stronger wind influences than most ESMs across all dryland regions. These results underscore the need for improved near-surface wind simulations in hyperarid areas and more realistic land surface and hydroclimate representations in arid and semiarid areas to reduce uncertainties in global dust emission simulations.

Li, Xinzhu [Michigan Technological University, Hou↗

Nickel hydroxide–nickel carbonate competitive growth on carbonate surfaces

The thermodynamic and kinetic factors controlling the competitive heterogeneous nucleation and growth of ubiquitous metal carbonate and hydroxide phases are poorly understood. In this work, calcite (CaCO 3 ) and magnesite (MgCO 3 ) powders were reacted with NiCl 2 (0–600 μM) for 7 days at 22 °C and 5 °C. The reacted powders were analyzed with X-ray photoelectron spectroscopy (XPS), scanning electron microscopy, and energy-dispersive X-ray spectroscopy to characterize the Ni surface precipitates formed. Evidence from these techniques pointed to the formation of mixed Ni carbonate-Ni hydroxide amorphous surface precipitates. On calcite, XPS detected primarily Ni(OH) 2 despite the initial solutions being more supersaturated with respect to gaspéite (NiCO 3 ) than to theophrastite (Ni(OH) 2 ) by a factor of 17–18. In contrast, NiCO 3 was the dominant component detected by XPS on magnesite in the same conditions. Decreasing the temperature had the effect of increasing the proportion of NiCO 3 to the detriment of Ni(OH) 2 . The experimental observations were consistent with low lattice/cation size mismatch favoring NiCO 3 nucleation and temperature most influencing Ni(OH) 2 nucleation. Comparison to previous work on Co-reacted powders indicated the differences in lattice/cation size mismatch and/or water exchange rate impacted the composition of the surface precipitates more than the relative thermodynamic stabilities of the competing minerals. This work explored the heterogeneous growth regime of Ni carbonate and hydroxide phases on carbonate surfaces and shed light on the factors that control the competition between surface precipitates when mineral surfaces are in contact with aqueous solutions supersaturated with respect to multiple mineral phases. In conclusion, these results contribute to geochemists’ efforts toward interpreting data from geochemical systems with elevated Ni concentrations, improving Ni environmental remediation and recovery strategies, and predicting the fate and transport of Ni in geochemical systems.

Heterogeneous nucleation↗

Surface Energy Balance System (SEBS) Instrument Handbook

A Surface Energy Balance System (SEBS) has been installed collocated with each deployed ECOR system at the Southern Great Plains (SGP), North Slope of Alaska (NSA), Tropical Western Pacific (TWP), ARM Mobile Facility 1 (AMF1), and ARM Mobile Facility 2 (AMF2). The surface energy balance system consists of upwelling and downwelling solar and infrared radiometers within one net radiometer, a wetness sensor, and soil measurements. The SEBS measurements allow the comparison of ECOR sensible and latent heat fluxes with the energy balance determined from the SEBS and provide information on wetting of the sensors for data quality purposes.

54 ENVIRONMENTAL SCIENCES↗

Estimation of the radiation budget during MOSAiC based on ground-based and satellite remote sensing observations

An accurate representation of the radiation budget is essential for investigating the impact of clouds on the climate system, especially in the Arctic, an environment highly sensitive to complex and rapid environmental changes. In this study, we analyse a unique dataset of observations from the central Arctic made during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in conjunction with state-of-the-art satellite products from CERES (Clouds and the Earth's Radiant Energy System) to investigate the radiative effect of clouds and radiative closure at the surface and the top of the atmosphere (TOA). We perform a series of radiative transfer simulations using derived cloud macro- and microphysical properties as inputs to the simulations for the entire MOSAiC period, comparing our results to collocated satellite products and ice-floe observations. The radiative closure biases were generally within the instrumental uncertainty, indicating that the simulations are sufficiently accurate to reproduce the radiation budget during MOSAiC. Comparisons of the simulated radiation budget relative to CERES show similar values in the terrestrial flux but relatively large differences in the solar flux, which are attributed to a lower surface albedo and a possible underestimation of atmospheric opacity by CERES. While the simulation results were consistent with the observations, more detailed analyses reveal an overestimation of simulated cloud opacity for cases involving geometrically thick ice clouds. In the annual mean, we found that, during the MOSAiC expedition, the presence of clouds leads to a loss of 5.2 W m −2 of the atmosphere–surface system to space, while the surface gains 25.0 W m −2 and the atmosphere is cooled by 30.2 W m −2 .

54 ENVIRONMENTAL SCIENCES↗

Atomic scale etching of diamond: insights from molecular dynamics simulations

Diamond is a promising material for multiple applications in quantum information processing and sensing as well as applications in microelectronics. However, diamond devices can be limited by surface defects that compromise charge stability and spin coherence, among others. Improved strategies in plasma etching of diamond could play an important role in minimizing or eliminating these defects. In this work, we explore plasma-assisted atomic scale etching of diamond using argon ions (Ar + ), hydrogen ions (H + ) and hydrogen atoms (H). We employ classical molecular dynamics (MD) simulations and test several interatomic potentials based on the Reactive Empirical Bond Order (REBO) form with comparisons to a variety of published experimental results. We performed MD simulations of low-energy hydrogen ($\leqslant$50 eV) and argon ( $\leqslant$200 eV) ion bombardment of diamond surfaces. Ar + bombardment can be used to locally smooth initially rough diamond surfaces via the formation of an amorphous C layer, the thickness of which increases with argon ion energy. Subsequent exposure with hydrogen ions (or fast neutrals) will selectively etch this amorphous C layer, leaving the underlying diamond layer mostly intact if the H energy is maintained below about 10 eV. The simulations suggest that combining Ar + smoothing with selective, near threshold energy H removal of amorphous C can be an effective strategy for diamond surface engineering, leading to more reliable and sensitive diamond color center devices.

74 ATOMIC AND MOLECULAR PHYSICS↗