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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of Single-Phase Convection in Additive Manufactured Versus Traditional Metal Foams

Abstract Metal foams have been often used for thermal management due to their favorable characteristics including high specific surface area (SSA), high thermal conductivity, and low relative density. However, they are accompanied by shortcomings including the significant contact resistances due to attachment method, as well as the need for characterization of foam parameters such as pore diameter and SSA. Additive manufactured (AM) metal foams would eliminate the substrate/foam thermal resistance, decrease the need for pre-usage characterization, and allow for tailoring structures, while also taking advantage of the characteristics of traditionally manufactured foams. A commercial, aluminum foam (nominally 5 pores per inch (PPI), 86.5% porosity) was analyzed using X-ray microcomputed tomography, and a custom-designed metal foam based on the cell diameter and porosity of the commercial sample was subsequently manufactured. Reduced domain computational fluid dynamics/heat transfer (CFD-HT) models were compared against experimental data. Postvalidation, the flow behavior, effect of varying attachment thermal conductivities, and thermal performance were numerically investigated, demonstrating the usefulness of validated pore-scale models, as well as the potential for improved performance using AM metal foams over traditionally manufactured foams.

Engineering↗
DOE OSTI2021

Estimating Surface Solar Irradiance Using Meteosat-8 Satellite for India and Surrounding Regions (2017-2019)

Using the Physical Solar Model, Version 3 (PSM V3), the National Renewable Energy Laboratory—in collaboration with the University of Wisconsin, the National Oceanic and Atmospheric Administration, and Solar Consulting Services—produced modeled surface solar irradiance based on Meteosat-8 satellite cloud information. PSM V3 implements a physics-based radiative transfer approach to model surface solar irradiance using cloud properties processed from raw satellite data and ancillary data such as aerosol optical depth and precipitable water vapor from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Further, the modeled surface solar irradiance was validated using 10 high-quality ground measurement data from the Baseline Surface Radiation Network. The modeled data showed good correlation with the ground measurement, and the overall uncertainty is less than 35% for all validation locations. Because of the satellite viewing geometry, the Indian and European locations demonstrated higher uncertainties than the African locations, where the Meteosat-8 satellite has a more nadir viewing geometry. Further, instruction on how to access the data is provided.

14 SOLAR ENERGY↗
DOE OSTI2022

Explosion Detection using Transfer Learning via YAMNet [Poster]

The acoustic data of explosions and noise collected on smartphones were fed to the YAMNet model to obtain the scores of each class. The data was split 60/20/20 for training, validation, and testing. A single-layered neural network was trained using the computed scores to predict if the data was an explosion or noise. The trained model was then combined with the YAMNet model. The combined model was tested with the ESC-50 dataset to investigate overall accuracy and class based false positive rates.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2026

AI-driven Neutrino Beam Diagnostics for Next-Generation Neutrino Experiments

The accelerator-driven beam uncertainty limits oscillation measurements in long-baseline neutrino experiments. Spill-resolved beam diagnostics and real-time inference are necessary to address these neutrino flux systematics. As such, we present a machine-learning-based beam monitoring framework developed and validated using data from the T2K experiment. Our approach uses downstream, spill-by-spill muon monitor observables to predict upstream parameters such as proton beam position and width. We achieve high predictive accuracy on nominal runs, demonstrating robust baseline performance whether the model is trained on stable runs or systematically varied conditions. The framework is designed to be robust against domain shifts, allowing the neural network architectures and inference strategies developed with T2K data to be retrained and validated using LBNF simulations, with the goal of eventual deployment under real LBNF/DUNE operating conditions. This scalable approach to real-time beam inference offers a pathway toward reducing flux systematics for next-generation neutrino experiments such as DUNE.

Aney, Noah [Fermilab; U. Chicago (main)]↗
DOE OSTI2022

A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County

The dataset contains hourly Anthropogenic heat (AH) from buildings in Los Angeles County, based on weather data from 2018. The hourly AH is aggregated at three spatial resolutions: 450m x 450m grid, 12km x 12km grid, and census tract. The AH is broken down into three components: building envelope surface convection, heating, ventilation, and air conditioning (HVAC) system heat release, and zone exfiltration and exhaust air heat loss. The dataset is created with the physics-based EnergyPlus building energy models to calculate individual buildings' AH considering WRF-UCM simulated microclimate conditions. Please refer to the paper "A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County" for more information about the data generation workflow and the data validation procedure. The data set contains two folders: the "output_data" folder holds the simulation results (EP_output and EP_output_csv), building metadata (building_metadata.geojson and building_metadata.csv), aggregated heat emission and energy consumption time-series data (hourly_heat_energy), and geographical data (geo_data) associated with the GEOID referenced in heat and energy consumption data. The "input_data" folder contains the raw data used to generate files in the "output_data" folder as well as data sets used in the validation. The code repository (https://github.com/IMMM-SFA/xu_etal_2022_sdata) holds the processing scripts for data curation, validation, and visualization.

Energy↗
DOE OSTI2025

Thermal Hydraulics Validation Activities in the ART-GCR Campaign

The Advanced Reactor Technologies - Gas Cooled Reactor Campaign (ART-GCR) is part of the United States Department of Energy - Office of Nuclear Energy's Advanced Reactor Technologies program aimed at developing a High Temperature Gas-cooled Reactor (HTGR) which will offer enhancements in safety and efficiency. The Design, Methods, and Validation arm of the ART-GCR program provides experience and advanced tools for HTGR design and analysis. The Methods and Validation arm is developing data to validate predictions of decay heat removal through an extensive experimental campaign the Natural Convection Shutdown Heat Removal Test Facility at Argonne National Laboratory. In-core thermal hydraulics validation is being facilitated through the OECD/NEA's Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data. That benchmark contains code-to-code and code-to-data comparisons for 3 sets of HTGR thermal hydraulics phenomena. This ongoing benchmark activity has 16 participants from 9 countries developing leading insights into HTGR thermal hydraulics code validation. The ART-GCR campaign is also working on the development of state-of-the-art MOOSE-based models of the High Temperature Engineering Test Reactor (HTTR). Through the OECD/NEA's HTTR Loss of Forced Cooling (LOFC) program, the ART-GCR campaign is developing a multiphysics transient code validation benchmark based on 3 HTTR experiments that will provide an opportunity for international collaboration on multiphysics code validation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Impacts of PV Module Connector Failures on Cost and Performance of Utility Scale Photovoltaic Systems

The reliability, cost and performance of electrical connectors are a concern in all types of electrical systems, and demands on connectors used on photovoltaic (PV) systems include that connectors maintain electrical conductivity and physical strength, endure ultraviolet sunlight and high ambient temperature, and resist moisture and chemical intrusion over a very long (>25 year) performance period. Connector failures increase operation and maintenance (O&M) costs and reduce plant production, but connector failure can also cause safety and liability problems, which are of greater concern. This work results from a three-year collaboration between Sandia National Laboratories (SNL), the Electric Power Research Institute (EPRI), and the National Renewable Energy Laboratory (NREL) and funded by the U.S. Department of Energy (DOE) Solar Energy Technology Office (SETO) under Agreements #39035 and #38531 "Connector Reliability Across the US Solar Sector." a multi-pronged investigation of PV connector health across the US (see https://energy.sandia.gov/pvconnectors/). This report presents derivation of a Techno-Economic Analysis (TEA) that models failure modes and frequencies (how often failure occurs), estimates O&M costs and lost production associated with connector failures, and then calculates the effect that PV module connectors can have on Levelized Cost of Energy (LCOE). The model is informed with initial data from quantitative assessment of failure rates, root causes and mechanisms, in-situ diagnostics and data collection, lab-based forensics, and interviews with PV connector manufacturers and plant operators. SNL conducted site inspections at multiple utility-scale sites in different climates and subjected field samples of new, used, and degraded connectors to visual and electrical characterization. EPRI conducted metallurgical analysis of the pin and sleeve conductors to study failure-induced morphological and compositional changes. There is in general a shortage of statistically valid data, but data from PVROM database maintained by SNL was sufficient to ascertain failure rates and lost production as well as provide qualitative insight in its curated maintenance records. This report details the structure of the mathematical model but the sources of data to inform the model will continue to evolve. Analysis of a 100 MW PV plant is provided as an example of the use of the model, with results indicating that connectors are responsible for Annualized O&M Costs of $\$$71,933/year; Annualized Unit O&M Costs of $\$$0.72/kW/year; that a Reserve Account of $\$$187,220 should be available to fund repairs related to connectors; that connectors add $\$$1,494,004 to the Net Present Value of the O&M Costs (project life); and that O&M related to connectors adds about $\$$0.00088/kWh to the Levelized Cost of Energy. The impact of this model is to provide a tool to make the US solar sector more robust by quantifying and monetizing the reliability risks to utility-scale PV systems posed by poorly installed, mismatched and/or poorly designed and manufactured connectors. The TEA provides a model incorporating failure statistics, O&M cost data, and lost production into a single figure of merit, informing decisions and enabling practitioners to optimize cost and performance trade-offs. Stakeholders include connector manufacturers, system designers and equipment specifiers, standards bodies, installers and O&M providers, investors and insurance underwriters. This report supports continued growth of PV predicated on assurances that properly installed and maintained PV system connectors are safe and reliable. The project team is proposing future work including accelerated testing of connectors and expanding the approach taken here to other PV system components, such as TEA for rapid shut-down devices.

14 SOLAR ENERGY↗
DOE OSTI2022

In Situ Soil Moisture and Thaw Depth Measurements Coincident with Airborne SAR Data Collections, Seward Peninsula, Alaska, 2019

The in-situ soil moisture and thaw depth measurements provided in this dataset were collected coincident with airborne overflights of L- and P-band SAR instruments at the Teller and Kougarok NGEE Arctic study sites on the Seward Peninsula, Alaska. Field measurements and flights were conducted in August 2019 as a collaboration between the NASA ABoVE Project's Airborne SAR Campaign and the NGEE Arctic Project. ABoVE protocols for establishing field measurement plots were followed. NGEE Arctic plots for the ground-based measurements are located at existing study sites where SAR data would also add value to current monitoring and characterization efforts of the NGEE Team. The ground-based data will be used by ABoVE to analyze, calibrate and validate the remote sensing products. This dataset follows the format and collection guidelines of the collaboration effort in 2017. Contained in this dataset are *.csv (including data dictionaries), .zip, .kml, .jpgs, .py, and .pdf files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort (with some overlap with Covid-19 pandemic) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

How accurate is a machine learning-based wind speed extrapolation under a round-robin approach?

As the size of commercial wind turbines keeps increasing, having accurate ways to vertically extrapolate wind speed is essential to obtain a precise characterization of the wind resource for wind energy production. Recently, machine learning has been proposed and applied to extrapolate wind speed to hub heights. However, previous studies trained and tested the machine learning methods at the same site, giving them an unfair advantage over the conventional extrapolation techniques, which are instead more universal. Here, we use data from four sites in Oklahoma to test a round-robin validation approach for machine learning, under which we train a random forest at a site, and test it at a different site, where the model has no prior knowledge of the wind resource. We quantify how the accuracy of this technique varies with distance from the training site, and we find that it outperforms conventional techniques for wind extrapolation at all the considered spatial separations. We then assess how the accuracy of the machine-learning based approach varies when it is used to predict wind speed in a wind farm far wake. Finally, we explore as case study the performance of the random forest in extrapolating winds during a low-level jet event.

17 WIND ENERGY↗
DOE OSTI2022

Survey of Relevant Data from the MSRP to Guide Development of MSR Chemistry Modeling Benchmarks

The Multiphysics Applications technical area of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is tasked with assessing, demonstrating, and applying NEAMS tools in solving multiphysics problems of nuclear reactors, such as liquid-fueled molten salt reactors (MSRs), which are the focus of this report. MSRs are actively being pursued as a potential candidate for power and heat generation by the nuclear industry. However, the inherent multiphysics nature of liquid-fueled MSRs, stemming from the strong interrelationship of neutronics, thermal fluids, and chemistry phenomena, provides unique challenges in modeling and simulation (mod/sim). Therefore, it will be important to develop mod/sim tools with varying types of multiphysics coupling that depend on the problem. The current work is focused on the initiation and development of MSR chemistry modeling benchmarks useful for validating current and potential future NEAMS tools. Development of such benchmarks include the following actions: 1) Summarize available chemistry data from the Oak Ridge National Laboratory (ORNL) MSR Program (MSRP) including operation of the Molten Salt Reactor Experiment (MSRE) and design studies for the Molten Salt Breeder Reactor (MSBR) concept; 2) Recommend simulation problems in MSR chemistry mod/sim based on (1); 3) Assess the current state of NEAMS tools that may support (2); 4) Demonstrate and validate the capabilities of the NEAMS tools in (3) while providing iterative feedback on future code development activities. The objective of this report is to initiate this effort by completing actions (1) and (2), which are discussed in Section 2. An overview of the relevant available MSRE experimental data is provided with examples of how this data may be useful in chemistry mod/sim problems, with the caveat that most of this data is over 50 years old, therefore some problem details as well as uncertainty estimates are often not provided. In Section 3, the current state of NEAMS tools is assessed for potential use in these mod/sim problems, with considerations for future code development activities, supporting action (3). Future work supporting this project under NEAMS may include a deeper dive into the specific phenomena discussed here including tasks such as the compilation of additional available data, updates in code development activities, and ultimately the demonstration and validation of these tools, supporting action (4).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

MeV-scale performance of water-based and pure liquid scintillator detectors

This paper presents studies of the performance of water-based liquid scintillators (WbLS) in both 1-kt and 50-kt detectors. In this work, performance is evaluated in comparison to both pure water Cherenkov detectors and a nominal model for pure scintillator detectors. Performance metrics include energy, vertex, and angular resolution, along with a metric for the ability to separate the Cherenkov from the scintillation signal as being representative of various particle identification capabilities that depend on the Cherenkov/scintillation ratio. We also modify the time profile of scintillation light to study the same performance metrics as a function of rise and decay time. We go on to interpret these results in terms of their impact on certain physics goals, such as solar neutrinos and the search for Majorana neutrinos. This work supports and validates previous results, and the assumptions made therein, and serves as a significant stepping stone to complete detector design studies by using a more detailed detector model and full reconstruction, with a primarily data-driven optical model, and fewer model assumptions. With this model, a high-coverage 50-kt detector achieves better than 10 (1)% precision on the flux of neutrinos from the Carbon-Nitrogen-Oxygen cycle with a water-based liquid scintillator (pure LS) target in five years of data taking. A 1-kt LS detector, with a conservative 50% fiducial volume of 0.5 kt, can achieve better than 5% detection. A liquid scintillator detector has sensitivity into the normal hierarchy region for Majorana neutrinos with half-life sensitivity of $T^{0νββ}_{1/2}$ > 1.4 × 10 28 years at 90% C.L. for 10 years of data taking with a Te-loaded target.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Comparing and contrasting In-Vial and full-scale systems for sparging volatile analytes

Here, in-vial sparging was demonstrated as an effective, practical alternative to a full-scale sparging system for supporting the analysis of volatile constituents. Using elemental mercury (Hg 0 ) and toluene as representative purgeable analytes, the mass removal for various sparge configurations was measured and a reduced order model was developed and validated. In the primary experiments, Hg 0 in the sparge gas was trapped on activated carbon or gold, thermally desorbed, and quantified using atomic absorption or atomic fluorescence spectroscopy. Toluene experiments using the same in-vial sparge apparatus and sparge parameters were performed to demonstrate the applicability of the reduced order model to a broad range of compounds. Toluene removal was tracked by measuring the remaining toluene in sparged aliquots using Ultraviolet-visible (UV–Vis) spectroscopy. For the sparging, flow rates varied from 25 to 75 mL/min for periods from 0 to 30 min. Sparge performance, mass removal as a function of time, and sparge gas volume were measured for both in-vial and full-scale systems. A model based on dimensionless Henry's Law coefficient, normalized sparge gas volume, and fractional extent of equilibrium matched the experimental data for both compounds and provides a practical tool for future applications. For the conditions tested in this study, the calibrated model indicated that the sparge gas in the in-vial system reached approximately 33% of its equilibrium value before exiting the water surface, while a full-scale system reached approximately 100%. The tests validated the quality, reproducibility, and predictability of sparging performance for both full scale and in-vial sparge systems. Related factors such as waste generation, worker risk, and labor were also assessed. Full scale sparge systems provide the advantage of lower detection levels due to larger sample volume, while the in-vial sparge systems provide advantages for most other factors; including automatability, reducing secondary wastes, lessening the need to clean and check the sparge apparatus, and lowering labor and costs. The data and associated reduced order model support continued development and deployment of in-vial sparge platforms as a practical option for analysis of purgeable analytes such as volatile organic compounds and volatile metals/organometallics.

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

Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model

The residential buildings sector is one of the largest electricity consumers worldwide and contributes disproportionally to peak electricity demand in many regions. Strongly driven by occupant activities, household energy consumption is stochastic and heterogeneous in nature. However, most residential energy models applied by industry use homogeneous, deterministic activity schedules, which work well for predictions of annual energy consumption, but can result in unrealistic hourly or sub-hourly electric load profiles, with exaggerated or muted peaks. The increasing proportion of variable renewable energy generators means that representing the heterogeneity and stochasticity of occupant behavior is now crucial for reliable planning at both bulk-power and distribution-system scales. This work presents a novel and open-source occupancy simulation approach that can simulate a diverse set of individual occupant and household event schedules for all major electricity, fuel, and hot water end uses. To accomplish this, we evaluated three alternative occupant activity simulation approaches before selecting a hybrid combining time-inhomogeneous Markov chains and probability-sampling of event durations and magnitudes. Further, we integrated the stochastic occupancy simulation with an open-source bottom-up physics-simulation building stock model and published a set of 550,000 diverse household end-use activity schedules representing a national housing stock. The simulator was verified against time-use survey data, and simulation results were validated against measured end-use electricity data for accuracy and reliability. While we use data for the United States, our application demonstrates how similar approaches could be applied using the time-use survey data collected in many countries around the world.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Field validation of isotropic analytical models for simulating fabric shades

Fabric roller shades are common shading materials used in commercial and residential buildings. Accurately characterizing and modeling shades helps practitioners select the appropriate product and its control strategy based on climate and occupants' priorities, such as visual comfort and view to outdoors. Previous studies established a generalized method for modeling complex fenestration systems using data-driven tabulated bidirectional scattering distribution functions. However, deploying such a method at scale to all fabric shading products on the market is too costly and time-consuming. Analytical models that are based on a limited set of measurements (e.g., normal-normal and normal-hemispherical visible transmittance and reflectance, and directional cut-off angles) can be used to model the wide variety of shading products on the market. This study evaluates the performance of two isotropic analytical models, Roos-Wienold and Modified-Kotey, for modeling fabric roller shades, with a focus on the model's ability to predict occupant visual comfort. The performance evaluation was conducted through laboratory and field measurements and simulations. The results showed that both models are sufficient for predicting vertical illuminance at seated eye-level. Roos-Wienold model was able to predict binary visual comfort classification (glare/no-glare) under a wide range of luminance conditions, while Modified-Kotey model did not perform as well under high-contrast low-adaptation conditions. Both models are insufficient in predicting visual comfort at a four-point scale (e.g., imperceptible, perceptible, disturbing, intolerable). The two isotropic models become less accurate when the fabric exhibits high anisotropy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Multi-machine validation of plasma initiation modelling and prospects for future devices: Predicting plasma initiation using only hardware design and control room input data

This paper reports on the generic prediction capability of full electromagnetic plasma initiation modelling with DYON, which was carried out for the first time in fusion research by the joint modelling of the International Tokamak Physics Activity—Integrating Operation Scenario group. The following devices were included in the experiment database: VEST (spherical torus, copper coils, Stainless steel wall, R/a = 0.3 m/0.2 m, V v = 3.7 m 3 ), MAST-U (spherical torus, copper coils, C wall, R/a = 0.7 m/0.5 m, V v = 55 m 3 ), EAST (conventional tokamak, superconducting coils, metallic wall, R/a = 1.85 m/0.5 m, V v = 38 m 3 ), DIII-D (conventional tokamak, copper coils, C wall, R/a = 1.67 m/0.65 m, V v = 35 m 3 ), and KSTAR (conventional tokamak, superconducting coils, C wall, R/a = 1.8 m/0.5 m, V v = 55 m 3 ). Despite the different hardware features of the devices, the required operating spaces of the loop voltage induction and prefill gas pressure for inductive plasma initiation in each device were successfully reproduced by the predictive simulations with DYON using only the individual hardware design and the control room input data for each discharge. This successful validation across multiple machines demonstrates that the full electromagnetic DYON modelling can capture the essential physics of inductive plasma initiation. The simulation settings commonly employed for all modelling and the modifications necessary to account for the discrepancies between individual devices are reported. Predictions for ITER based on the multi-machine validation indicate that a wide range of prefill gas pressures exists for the Townsend breakdown and the plasma burn-through (0.01–1.5 mPa).

DYON↗
DOE OSTI2020

Development of an Encoding Method on an Co-simulation Platform for Mitigating the Impact of Unreliable Communication

This report presents a hardware-in-the-loop (HIL) based modeling approach for simulating impacts of unreliable communication on the performance of centralized volt-var control and for developing an encoding method to mitigate the impacts. First, an asynchronous real-time HIL simulation platform is introduced to enable multi-rate co-simulation of a distribution system with many inverter-based distributed energy resources (DERs). The distribution system is modeled by milliseconds phasor-based models and the DERs are modeled by micro-seconds power electronic models. Communication connections between a centralized volt-var controller (modeled externally to the HIL testbed) and smart inverters are built by implementing Modbus links and the Long Term Evolution network. On this co-simulation platform, an enhanced, augmented Lagrangian multiplier based encoded data recovery (EALM-EDR) algorithm for mitigating the impact of unreliable communication is developed and validated. Simulation results demonstrate the efficacy of using the HIL-based co-simulation platform as a power grid digital twin for developing algorithms that coordinate a large number of heterogeneous control systems through wired and wireless communication links.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Highly selective Si 3 N 4 /SiO 2 etching using an NF 3 /N 2 /O 2 /H 2 remote plasma. I. Plasma source and critical fluxes

Highly selective plasma etching of silicon nitride (Si 3 N 4 ), while not etching silicon dioxide (SiO 2 ), is a critical step in the fabrication of microelectronics devices. In many applications, this etching must be damage-free and isotropic, which then motivates the use of remote plasmas where the reactants interacting with the substrate are dominantly neutral species. In this paper and Paper II, mechanisms for highly selective Si 3 N 4 etching in remote plasmas are discussed based on results from experiments and simulations. It has been shown experimentally that high Si 3 N 4 /SiO 2 etch selectivity (≈380) can be achieved in the downstream effluent of an NF 3 /N 2 /O 2 /H 2 plasma. The authors found that H2 plays a principal role in the reaction mechanism as Si 3 N 4 /SiO 2 selectivity shows a sharp maximum as a function of the H2 flow rate. Based on this observation, and measured densities of F-atoms and H2 in the process chamber, a mechanism of selective Si 3 N 4 /SiO 2 etching is proposed in which HF molecules in vibrationally excited states accelerate etching reactions. A reaction mechanism for NF 3 /N 2 /O 2 /H 2 plasmas and its afterglow was developed to computationally determine the species densities and fluxes on the wafer level, validated by comparing with experimentally measured F-atom and H 2 densities. The calculated species densities and fluxes were used as input to an analytical model of Si 3 N 4 and SiO 2 etching based on the results of quantum chemistry simulations. This paper presents experimental results (etching data and species densities), the reaction mechanism for NF 3 /N 2 /O 2 /H 2 plasmas, and the results of simulations of gas phase chemistry. Quantum chemistry simulations of elementary etching reactions, description of the analytical model of Si 3 N 4 and SiO 2 etching, calculations of the etch rates, and Si 3 N 4 and SiO 2 selectivity with this model are presented in Paper II.

42 ENGINEERING↗
DOE OSTI2021

Light transport with weak angular dependence in fog

Random scattering and absorption of light by tiny particles in aerosols, like fog, reduce situational awareness and cause unacceptable down-time for critical systems or operations. Computationally efficient light transport models are desired for computational imaging to improve remote sensing capabilities in degraded optical environments. To this end, we have developed a model based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes, thereby covering the applicability domain of both the small angle and diffusion approximations. An analytic solution was derived and validated using experimental data acquired at the Sandia National Laboratory Fog Chamber facility. The evolution of the fog particle density and size distribution were measured and used to determine macroscopic absorption and scattering properties using Mie theory. A three-band (0.532, 1.55, and 9.68 µ m) transmissometer with lock-in amplifiers enabled changes in fog density of over an order of magnitude to be measured due to the increased transmission at higher wavelengths, covering both the moderate and highly scattering regimes. The meteorological optical range parameter is shown to be about 0.6 times the transport mean free path length, suggesting an improved physical interpretation of this parameter.

74 ATOMIC AND MOLECULAR PHYSICS↗