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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines

A protocol was developed as a first step in analyzing the complex organic aerosols present on Saturn's moon Titan, as well as the analogues of these aerosols (tholins) made on Earth. Labeling of primary amines using Pacific Blue succinimidyl ester is effected in ethanol with 25 mM triethylamine to maintain basic conditions. This reaction is allowed to equilibrate for at least one hour. Separation of the labeled primary amines is performed in ethanol with 1.05 M acetic acid, and 50 mM ammonium acetate in a commercial two-layer glass device with a standard crossmicrochannel measuring 50 microns wide by 20 microns deep. Injection potentials are optimized at 2 kV from the sample (negative) to the waste well (positive), with slight bias applied to the other two wells ( 0.4 and 0.8 V) to pinch the injection plug for the 30-s injection. Separation is performed at a potential of 5 kV along the channel, which has an effective separation distance of 7 cm. The use of ethanol in this method means that long-chain primary amines can be dissolved. Due to the low pH of the separation buffer, electro-osmotic flow (EOF) is minimized to allow for separation of both short-chain and longchain amines. As the freezing point of ethanol is much lower than water, this protocol can perform separations at temperatures lower than 0 C, which would not be possible in aqueous phase. This is of particular importance when considering in situ sampling of Titan aerosols, where unnecessary heating of the sample (even to room temperature) would lead to decomposition or unpredictable side reactions, which would make it difficult to characterize the sample appropriately.

Willis, Peter A.↗
DOE OSTI2025

Investigating the Impact of Absorbed Surface Impurities (CO, CO 2 , CH 4 , and H 2 O) on Getter Rate Performance

This report provides an overview of engineering and experimental efforts to establish a new capability for measuring H2 uptake rates for Tritium Producing Abosrber Rod (TPBAR) getter materials. This new system was used to gain a better understanding of the impact of contaminant species (CO 2 , CO, CH 4 , and H 2 O) on getter performance under relevant hydrogen uptake conditions (350 °C, 20 torr). Herein, we successfully established a high-resolution gravimetric sorption (HRGS) system in a flow through configuration that can measure sample mass changes with high resolution (1 µg or 10 µg) over long experiment times (days), high temperature, and varying pressures. We coupled this capability with an in-line universal gas analyzer (UGA) system to characterize potential surface chemistry side reactions occurring after contaminant gas exposure. The major findings of this study suggest that methane and CO have the most detrimental effects on getter H 2 uptake performance showing large changes in rate after exposure compared to CO 2 and water. The effect of these contaminant species did not influence getter sample capacity (~ 1.8 wt% H 2 ). After CO and methane exposure, changes in getter rate were accompanied by observable Ni-surface defects and pinholes via SEM imaging suggesting possible Ni- layer corrosion. Additionally, the increase in C and O signal in the zircaloy layer, observed via EDX, point to C and O species transport through the getter sample resulting in the formation of carbides and oxide species. Thus, co-exposure studies where mixed gases or water vapor are introduced together will be important to further understand what mechanisms are contributing to Ni-layer corrosion and changes in getter performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing

We present and characterize the galaxy-galaxy lensing signal measured using the first three years of data from the Dark Energy Survey (DES Y3) covering 4132 deg 2 . These galaxy-galaxy measurements are used in the DES Y3 3 × 2 pt cosmological analysis, which combines weak lensing and galaxy clustering information. We use two lens samples: a magnitude-limited sample and the redmagic sample, which span the redshift range ∼ 0.2 – 1 with 10.7 and 2.6 M galaxies, respectively. For the source catalog, we use the metacalibration shape sample, consisting of ≃ 100 M galaxies separated into four tomographic bins. Our galaxy-galaxy lensing estimator is the mean tangential shear, for which we obtain a total SNR of ∼ 148 for maglim ( ∼ 120 for redmagic), and ∼ 67 ( ∼ 55 ) after applying the scale cuts of 6 Mpc / h . Thus we reach percent-level statistical precision, which requires that our modeling and systematic-error control be of comparable accuracy. The tangential shear model used in the 3 × 2 pt cosmological analysis includes lens magnification, a five-parameter intrinsic alignment model, marginalization over a point mass to remove information from small scales and a linear galaxy bias model validated with higher-order terms. We explore the impact of these choices on the tangential shear observable and study the significance of effects not included in our model, such as reduced shear, source magnification, and source clustering. We also test the robustness of our measurements to various observational and systematics effects, such as the impact of observing conditions, lens-source clustering, random-point subtraction, scale-dependent metacalibration responses, point spread function residuals, and B modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sub-pixel high-resolution imaging of high-energy x-rays inspired by sub-wavelength optical imaging

We have developed and demonstrated an image super-resolution method—XR-UNLOC: X-Ray UNsupervised particle LOCalization—for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μ m of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of “nearly-dark” instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community (“droplet analysis”) showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2011

Evaluation of Convective Transport in the GEOS-5 Chemistry and Climate Model

The NASA Goddard Earth Observing System (GEOS-5) Chemistry and Climate Model (CCM) consists of a global atmospheric general circulation model and the combined stratospheric and tropospheric chemistry package from the NASA Global Modeling Initiative (GMI) chemical transport model. The subgrid process of convective tracer transport is represented through the Relaxed Arakawa-Schubert parameterization in the GEOS-5 CCM. However, substantial uncertainty for tracer transport is associated with this parameterization, as is the case with all global and regional models. We have designed a project to comprehensively evaluate this parameterization from the point of view of tracer transport, and determine the most appropriate improvements that can be made to the GEOS-5 convection algorithm, allowing improvement in our understanding of the role of convective processes in determining atmospheric composition. We first simulate tracer transport in individual observed convective events with a cloud-resolving model (WRF). Initial condition tracer profiles (CO, CO2, O3) are constructed from aircraft data collected in undisturbed air, and the simulations are evaluated using aircraft data taken in the convective anvils. A single-column (SCM) version of the GEOS-5 GCM with online tracers is then run for the same convective events. SCM output is evaluated based on averaged tracer fields from the cloud-resolving model. Sensitivity simulations with adjusted parameters will be run in the SCM to determine improvements in the representation of convective transport. The focus of the work to date is on tropical continental convective events from the African Monsoon Multidisciplinary Analyses (AMMA) field mission in August 2006 that were extensively sampled by multiple research aircraft.

Pickering, Kenneth E.↗
DOE OSTI2020

Cesium Removal and Hydraulic Performance Comparisons of CST Ion Exchange Media Batches in Support of the Tank Closure Cesium Removal Project - 20522

Three batches of Crystalline Silicotitanate (CST) ion exchange media have been evaluated for cesium removal efficiency from a Savannah River Site (SRS) High Level Waste (HLW) supernate simulant in support of the Tank Closure Cesium Removal (TCCR) Project, which involves at-tank column waste treatment. Results will be utilized to select the CST media batch to be added to the next TCCR unit columns. Two of the CST media samples were recent production batches and the third was an archived batch studied extensively at SRS nearly two decades ago. The archived CST batch had a significantly smaller average particle diameter than more recent batches. Small-scale (∼23 mL), side-by-side column tests were conducted at 35 deg. C with each of the CST batches using the same simulant at flow rates near 1.2 mL/min (3.0-3.4 CST bed volumes/hr). The cesium ion exchange column performance results were lower than expected for all three CST batches, but the data indicated that 30% more simulant volume and 40% more equivalent CST bed volumes of solution can be processed with the older CST batch prior to reaching the 50% cesium breakthrough point than can be processed with the newer CST batches. Hydraulic evaluations of the CST columns were also conducted in simulant at 24 deg. C to determine the impact of the different particle size distributions and associated bed porosities on frictional pressure drop under dynamic flow conditions. Higher differential pressure drops were observed with the archived CST batch relative to recent production batches, due to the smaller particle size distribution and the packing characteristics of the archived batch. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Dietary uptake of geosmin in rainbow trout ( Oncorhynchus mykiss )

Geosmin is a primary source of muddy/earthy ‘off-flavors’ in farmed fish, which may render their organoleptic quality unacceptable to consumers. Model systems of geosmin uptake typically comprise exposure to waterborne geosmin that is absorbed via the gills. The present research demonstrates dietary exposure as an alternative route of geosmin uptake in Rainbow Trout (Oncorhynchus mykiss) fillets. Trout (average initial weight of 355 g) were stocked in quadruplicate compartmentalized raceways (N = 4 compartments per treatment, n = 50 fish per compartment) supplied with first-use, flow-through water (4.5 complete turnovers per hour). Fish were fed diets containing 0 (control dose), 0.005 (low dose), 0.05 (medium dose), or 0.5 (high dose) mg geosmin/kg feed at 1% body weight/day for four weeks. Fillets (12 fillets/diet/week plus 12 pre-trial fillet samples) and weekly feed and water samples were analyzed via GC–MS to determine geosmin concentrations. Feeding behavior was documented daily according to a four-point scale. ANOVA with post-hoc Tukey tests and polynomial contrast, regression, correlation, and chi-squared statistical analyses were applied to data (α = 0.05 significance level). Palatability of feed did not hinder consumption of the geosmin-spiked feeds: although fish responded positively to all feeds, the most aggressive feeding behavior was observed among those fed medium and high dose feed. Geosmin was effectively imparted into fillets after one week, and no significant temporal effect was found after four weeks. Mean geosmin concentrations significantly increased in fillets from low (mean of 26 ng/kg geosmin) to medium (202 ng/kg) to high (441 ng/kg) dose feed groups during the trial. Polynomial contrasts and regression modeling validated this significant positive effect of dose on geosmin uptake, with an estimated 166 ng/kg rise in fillet-geosmin for every log 10 increase in feed concentration. Waterborne geosmin levels immediately post-feeding were conditionally independent of concentrations in feed and fillets, therefore dietary uptake was affirmed as the predominant mechanism of absorption in the present experimental system. Finally, based on these findings, geosmin-spiked feeds may be used to induce predictable, repeatable levels of this off-flavor compound in fillets and serve as a model system for further investigation of sensory quality and off-flavor mitigation strategies for farm-raised fish.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Modeling Thermal Contact Resistance

One difficulty in using cryocoolers is making good thermal contact between the cooler and the instrument being cooled. The connection is often made through a bolted joint. The temperature drop associated with this joint has been the subject of many experimental and theoretical studies. The low temperature behavior of dry joints have shown some anomalous dependence on the surface condition of the mating parts. There is also some doubts on how well one can extrapolate from the test samples to predicting the performance of a real system. Both finite element and analytic models of a simple contact system have been developed. The model assumes (a) the contact is dry (contact limited to a small portion of the total available area and the spaces in-between the actual contact patches are perfect insulators), (b) contacts are clean (conductivity of the actual contact is the same as the bulk), (c) small temperature gradients (the bulk conductance may be assumed to be temperature independent), (d) the absolute temperature is low (thermal radiation effects are ignored), and (e) the dimensions of the nominal contact area are small compared to the thickness of the bulk material (the contact effects are localized near the contact). The models show that in the limit of actual contact area much less than the nominal area (a much less than A), that the excess temperature drop due to a single point of contact scales as a(exp -1/2). This disturbance only extends a distance approx. A(exp 1/2) into the bulk material. A group of identical contacts will result in an excess temperature drop that scales as n(exp -1/2), where n is the number of contacts and n dot a is constant. This implies that flat rough surfaces will have a lower excess temperature drop than flat polished surfaces.

Kittel, Peter↗
DOE OSTI2022

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An experimental investigation on the characteristics of heat pipes with annular type composite wick structure

Here, an experimental investigation has been conducted on the hydraulic characteristics of annular type wick structures for heat pipes. An experimental facility which can measure porosity, permeability, and effective pore radius of the wick structures in a vacuum condition is established. Nine different types of multi-layered (6 layers in total) composite screen meshes are characterized. Based on the measurement results, a wick structure composed of one layer of 100×100 mesh, three layers of 400×400 mesh, and two layers of 60×60 mesh is determined to have the highest permeability to effective pore radius ratio $(K/r_{eff})$ and was selected as a targeted sample. The wick-to-wall gap effect on the hydraulic characteristics of annular type wick structure is also investigated by measuring the permeability and effective pore radius of the sample wick structure with varying gap widths. The result shows that the permeability increases as the gap increases from 0 mm to 1.2 mm. After a peak at 1.2 mm, the permeability decreases as the gap increases and converges to the value of the case measured without a wall structure. The effective pore radius becomes smaller as the gap increases, making a peak at a gap distance of 1.2 mm. This result implies that there is an optimal point in gap distance which is determined to be 1.2 mm for the selected composite mesh structure. A capillary limitation correlation with a multiplying factor which explains the enhanced performance of the wick due to the gap is suggested. An annular wick type heat pipe is constructed and tested. The capillary limitation of the heat pipe showed good agreement with the suggested correlation.

42 ENGINEERING↗
DOE OSTI2022

The miniJPAS survey: A search for extreme emission-line galaxies

Context. Galaxies with extreme emission lines (EELGs) may play a key role in the evolution of the Universe, as well as in our understanding of the star formation process itself. For this reason an accurate determination of their spatial density and fundamental properties in different epochs of the Universe will constitute a unique perspective towards a comprehensive picture of the interplay between star formation and mass assembly in galaxies. In addition to this, EELGs are also interesting in order to explain the reionization of the Universe, since their interstellar medium (ISM) could be leaking ionizing photons, and thus they could be low z, analogous of extreme galaxies at high z . Aims. This paper presents a method to obtain a census of EELGs over a large area of the sky by detecting galaxies with rest-frame equivalent widths ≥300 Å in the emission lines [O II]λλ3727,3729Å, [O III]λ5007Å, and Hα. For this, we aim to use the J-PAS survey, which will image an area of ≈8000 deg 2 with 56 narrow band filters in the optical. As a pilot study, we present a methodology designed to select EELGs on the miniJPAS images, which use the same filter dataset as J-PAS, and thus will be exportable to this larger survey. Methods. We make use of the miniJPAS survey data, conceived as a proof of concept of J-PAS, and covering an area of ≈1 deg 2 . Objects were detected in the r SDSS images and selected by imposing a condition on the flux in a given narrow-band J-PAS filter with respect to the contiguous ones, which is analogous to requiring an observed equivalent width larger than 300 Å in a certain emission line within the filter bandwidth. The selected sources were then classified as galaxies or quasi-stellar objects (QSOs) after a comparison of their miniJPAS fluxes with those of a spectral database of objects known to present strong emission lines. This comparison also provided a redshift for each source, which turned out to be consistent with the spectroscopic redshifts when available (|Δz/(1 + z spec )| ≤ 0.01). Results. The selected candidates were found to show a compact appearance in the optical images, some of them even being classified as point-like sources according to their stellarity index. After discarding sources classified as QSOs, a total of 17 sources turned out to exhibit EW 0 ≥ 300 Å in at least one emission line, thus constituting our final list of EELGs. Our counts are fairly consistent with those of other samples of EELGs in the literature, although there are some differences, which were expected due to biases resulting from different selection criteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Deep-field analytical calibration

The next generation of imaging surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Euclid, and the Nancy Grace Roman Space Telescope, will provide unprecedented constraints on cosmology using weak gravitational lensing. To fully exploit this statistical power, shear measurement methods must achieve sub- per cent accuracy while mitigating systematic biases from noise, the point-spread function (PSF), blending, and shear-dependent detection. The analytical calibration framework (AnaCal) has demonstrated such accuracy but requires adding noise to images, reducing effective depth. We introduce Deep-Field Analytical Calibration (DEEP-FIELD AnaCal), an extension of AnaCal that uses deep-field images to compute shear responses while preserving the statistical power of wide-field data. We validate DEEP-FIELD AnaCal on isolated and blended galaxy image simulations with LSST-like conditions, finding it meets the stringent requirement of multiplicative bias $|m| < 3\times 10^{-3}$ at 99.7 per cent confidence. Compared to standard AnaCal applied to wide-field images, DEEP-FIELD AnaCal increases the effective galaxy number density from 17 to 30 arcmin$^{-2}$ for simulated 10-yr LSST data. With deep fields $10\times$ longer than the wide field, we find pixel noise variance in shear estimation is reduced by 30 per cent and overall uncertainty by $\sim 25~{{\ \rm per\ cent}}$. Finally, using the LSST Deep Drilling Fields strategy, we assess sample variance and find an equivalent calibration uncertainty of $\lesssim 0.3~{{\ \rm per\ cent}}$. These results demonstrate that DEEP-FIELD AnaCal offers a promising path to achieve the required shear calibration for upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services

Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions that lead to significant inefficiency in the long term, vehicles should be allocated to requests by optimizing a non-myopic utility function or by batching requests together and optimizing a myopic utility function. While the former approach is typically offline, the latter can be performed online. We point out two major issues with such approaches when applied to paratransit services in practice. First, it is difficult to batch paratransit requests together as they are temporally sparse. Second, the environment in which transit agencies operate changes dynamically (e.g., traffic conditions can change over time), causing the estimates that are learned offline to become stale. To address these challenges, we propose a fully online approach to solve the dynamic vehicle routing problem (DVRP) with time windows and stochastic trip requests that is robust to changing environmental dynamics by construction. We focus on scenarios where requests are relatively sparse—our problem is motivated by applications to paratransit services. We formulate DVRP as a Markov decision process and use Monte Carlo tree search to evaluate actions for any given state. Accounting for stochastic requests while optimizing a non-myopic utility function is computationally challenging; indeed, the action space for such a problem is intractably large in practice. To tackle the large action space, we leverage the structure of the problem to design heuristics that can sample promising actions for the tree search. Our experiments using real-world data from our partner agency show that the proposed approach outperforms existing state-of-the-art approaches both in terms of performance and robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗
DOE OSTI2021

Millisecond timescale reactions observed via X-ray spectroscopy in a 3D microfabricated fused silica mixer

Determination of electronic structures during chemical reactions remains challenging in studies which involve reactions in the millisecond timescale, toxic chemicals, and/or anaerobic conditions. Here, a three-dimensionally (3D) microfabricated microfluidic mixer platform that is compatible with time-resolved X-ray absorption and emission spectroscopy (XAS and XES, respectively) is presented. This platform, to initiate reactions and study their progression, mixes a high flow rate (0.50–1.5 ml min –1 ) sheath stream with a low-flow-rate (5–90 µl min –1 ) sample stream within a monolithic fused silica chip. The chip geometry enables hydro­dynamic focusing of the sample stream in 3D and sample widths as small as 5 µm. The chip is also connected to a polyimide capillary downstream to enable sample stream deceleration, expansion, and X-ray detection. In this capillary, sample widths of 50 µm are demonstrated. Further, convection–diffusion-reaction models of the mixer are presented. The models are experimentally validated using confocal epifluorescence microscopy and XAS/XES measurements of a ferricyanide and ascorbic acid reaction. The models additionally enable prediction of the residence time and residence time uncertainty of reactive species as well as mixing times. Residence times (from initiation of mixing to the point of X-ray detection) during sample stream expansion as small as 2.1 ± 0.3 ms are also demonstrated. Importantly, an exploration of the mixer operational space reveals a theoretical minimum mixing time of 0.91 ms. The proposed platform is applicable to the determination of the electronic structure of conventionally inaccessible reaction intermediates.

3D microfabrication↗
NASA NTRS1994

Aerothermodynamics of Pyrolizing Surfaces in Hypersonic Rarefied Flows

Direct simulation Monte Carlo (DSMC) calculations of rarefied flows about entry bodies typically employ a fixed surface temperature or a radiative-equilibrium energy balance to compute that temperature. Such boundary conditions neglect any effects of heat capacitance and heat conduction in the spacecraft heat shield and, therefore, provide an upper bound for the surface temperature. Such calculations also neglect pyrolysis from the heat shield which can be significant for a high-energy incident flow at very low densities. Accurate prediction of both heating and aerodynamic forces requires including pyrolysis and surface heat transfer in the models for gas-surface interaction employed in DSMC methods. Although these physical models have long appeared in various continuum flow calculation codes, they have only recently appeared in DSMC codes which are required to simulate rarefied flows during entry at high altitudes. In the current implementation, routines from the widely distributed Charring Material Thermal Response and Ablation (CMA) program are coupled into a DSMC code to calculate the one-dimensional heat transfer into the carbon phenolic heat shield at each point on a vehicle surface. Temperature-dependent material properties, surface re-radiation, and in-depth pyrolysis were included in the calculation, but surface ablation was neglected. Sample calculations for entry of the Galileo probe into the atmosphere of Jupiter demonstrate that including pyrolysis in the model leads to significant differences in predicted aerodynamics. Granted, the drag coefficient does not depend strongly on the surface temperature which can itself be significantly below the radiative equilibrium value during entry. However, the surface mass flux due to pyrolysis of the material is significant once the probe drops to altitudes characterized by transition flow. This leads to a noticeable increase in drag and a decrease in heating compared to a body without pyrolysis.

Haas, Brian L.↗
DOE OSTI2024

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗