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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A physical model for predicting bidirectional reflectances over bare soil

While most previous attempts to retrieve soil surface optical property characteristics have proceeded through a fitting of empirical functions to the data, an optimization technique is presently applied to a physically-based surface reflectance model developed for the study of planetary surfaces. This inversion procedure is shown to allow the direct estimation of the single-scattering coefficient, two parameters describing the 'hot spot' phenomenon, and two parameters describing the scattering phase function. A comparison of inversion technique results with both synthetic data and actual observations shows the model to be capable of predicting the observed bidirectional reflectances as well as directional-hemispherical reflectances; it can also build the complete radiance field over the upward hemisphere.

Pinty, Bernard↗
NASA NTRS2018

Blunt-Body Paradox and Improved Application of Transient-Growth Framework

The “Reshotko-Tumin transition criterion" based on optimal transient growth successfully correlates laboratory measurements of roughness induced transition over blunt body configurations. Even though transient growth has not been conclusively linked to the measured onset of transition, the above correlation denotes the only available physics-based model for subcritical transition in blunt body flows, since the latter do not support any modal instabilities at typical experimental conditions. Unlike other established models based on empirical curve fits that are valid for a specific subclass of datasets, the optimal-growth-based transition criterion appears to provide a reasonable correlation with measurements in various wind tunnel and ballistic range facilities and for a broad range of surface temperature ratios. This paper is focused on optimal growth calculations that improve upon significant shortcomings of the computations underlying the Reshotko-Tumin correlation. The improved framework is applied to leeward transition over a spherical section forebody that was tested in the Mach 6 Adjustable Contour Expansion wind tunnel at Texas A&M University. The computed results highlight the significance of nonparallel basic state evolution, curvature terms, and an optimization procedure that varies both inflow and outflow locations of the transient growth interval. More important, the results indicate that the modified correlation is very close to its original form, and hence, that the accuracy of the transient-growth-based transition criterion is not compromised by using a more thorough theoretical framework. Yet the results also show that the optimal energy gain up to the predicted transition onset location can be rather small, highlighting the need to further investigate the optimal growth criterion for additional experimental configurations and to also uncover the in-depth physics underlying blunt body transition.

Freestream conditions↗
DOE OSTI2024

Morphological Modulation of TiO 2 Nanotube via Optimal Anodization Condition for Solar Water Oxidation

With the depletion of fossil fuels and the rising global demand for energy, photoelectrochemical (PEC) water splitting presents a promising solution to avert an energy crisis. Titanium dioxide (TiO 2 ), an n -type semiconductor, has gained popularity as a photoanode due to its remarkable PEC properties. Nevertheless, inherent challenges such as a wide band gap (~3.2 eV), charge recombination, and slow oxygen evolution reaction (OER) rates at the surface limit its practical application by constraining light absorption. To overcome these limitations, we have developed TiO 2 nanotubes (NTs) using a facile anodization method. This study examines the impact of anodization growth parameters on solar water oxidation performance. Specifically, TiO 2 NTs with modified anodization time (referred to as TiO 2 -6) showed a 3.5-fold increase in photocurrent density compared to the as-grown TiO 2 NTs. Furthermore, electrochemical analyses, such as electrochemical impedance spectroscopy (EIS), indicated a significant decrease in charge transfer resistance following the adjustment of on-off anodization time. Additionally, the TiO 2 -6 photoanode demonstrated a higher electrochemically active surface area (ECSA) than other samples. Therefore, optimal nanostructuring parameters are crucial for enhancing the PEC properties of TiO 2 NTs. Overall, our findings offer valuable insights for fabricating high-quality TiO 2 NTs photoanodes, contributing to developing efficient PEC systems for sustainable energy production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Uncovering the Critical Role of Ni on Surface Lattice Stability in Anionic Redox Active Li 1.2 Ni 0.2 Mn 0.6 O 2

Anionic redox reaction (ARR) can provide extra capacity beyond transition metal (TM) redox in lithium-rich TM oxide cathodes. Practical ARR application is much hindered by the structure instability, particularly at the surface. Oxygen release has been widely accepted as the ringleader of surficial structure instability. However, the role of TM in surface stability has been much overlooked, not to mention its interplay with oxygen release. Herein, TM dissolution and oxygen release are comparatively investigated in Li 1.2 Ni 0.2 Mn 0.6 O 2 . Ni is verified to detach from the lattice counter-intuitively despite the overwhelming stoichiometry of Mn, facilitating subsequent oxygen release of the ARR process. Intriguingly, surface reorganization occurs following regulated Ni dissolution, enabling the stabilization of the surface and elimination of oxygen release in turn. Accordingly, a novel optimization strategy is proposed by adding a relaxation step at 4.50 V within the first cycle procedure. Battery performance can be effectively improved, with voltage decay suppressed from 3.44 mV/cycle to 1.60 mV/cycle, and cycle stability improved from 66.77% to 90.01% after 100 cycles. This work provides new perspectives for clarifying ARR surface instability and guidance for optimizing ARR performance.

25 ENERGY STORAGE↗
NASA NTRS1978

Development of an improved high efficiency thin silicon solar cell

Efforts were concerned with optimizing techniques for thinning silicon slices in NaOH etches, initial investigations of surface texturing, variation of furnace treatments to improve cell efficiency, initial efforts on optimization of gridline and cell sizes and Pilot Line fabrication of quantities of 2 cm x 2 cm 50 micron thick cells.

Lindmayer, J.↗
NASA NTRS2016

Terrestrial Testing of the CapiBRIC, a Microgravity Optimized Brine Processor

Utilizing geometry based static phase separation exhibited in the radial vaned capillary drying tray, a system was conceived to recover water from brine. This technology has been named the Capillary BRIC; abbreviated CapiBRIC. The CapiBRIC utilizes a capillary drying tray within a drying chamber. Water is recovered from clean water vapor evaporating from the free surface leaving waste brine solids behind. A novel approach of optimizing the containment geometry to support passive capillary flow and static phase separation provides the opportunity for a low power system that is not as susceptible to fouling as membranes or other technologies employing physical barriers across the free brine surface to achieve phase separation in microgravity. Having been optimized for operation in microgravity, full-scale testing of the CapiBRIC as designed cannot be performed on the ground as the force of gravity would dominate over the capillary forces. However, subscale units relevant to full-scale design were used to characterize fill rates, containment stability, and interaction with a variable volume reservoir in the PSU Dryden Drop Tower (DDT) facility. PSU also using tested units scaled such that capillary forces dominated in a 1-g environment to characterize evaporation from a free-surface in 1-g upward, sideways and downward orientations. In order to augment the subscale testing performed by PSU, a full scale 1-g analogue of the CapiBRIC drying unit was initiated to help validate performance predictions regarding expected water recovery ratio, estimated processing time, and interface definitions for inlets, outlets, and internal processes, including vent gas composition. This paper describes the design, development and test of the terrestrial CapiBRIC prototypes.

Sargusingh, Miriam J.↗
NASA NTRS1976

Theoretical optimization and parametric study of n-on-p Al/x/Ga/1-x/As-GaAs graded band-gap solar cell

A comprehensive theoretical model of the graded band-gap Al(x)Ga(1-x)As-GaAs solar cell is used to optimize the n-on-p cell. The model includes power losses due to surface, bulk, and junction minority-carrier recombination, series resistance, and photon reflection from an SiO antireflection coating of optimum thickness. The optimized cell has a junction depth/graded band-gap layer thickness of 1.0 micron, respective donor and acceptor concentrations of 4 x 10 to the 17th power and 2 x 10 to the 17th power per cu cm, and a surface AlAs mode fraction of x = 0.35. The optimized graded band-gap cell has an air-mass-zero efficiency of 17.7% (not corrected for a 13% front surface contact area) and is shown to be less sensitive than a similar n-on-p GaAs cell to material degradation in the form of decreased minority-carrier diffusion lengths and increased surface-recombination velocity

Hutchby, J. A.↗
DOE OSTI2025

Photon counting with intensified charge coupled device (ICCD) – I. In-depth detector characterization

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic computational study of oxide adsorption properties for applications in photocatalytic CO 2 reduction

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Multi-Objective Optimization of Spacecraft Trajectories for Small-Body Coverage Missions

Visual coverage of surface elements of a small-body object requires multiple images to be taken that meet many requirements on their viewing angles, illumination angles, times of day, and combinations thereof. Designing trajectories capable of maximizing total possible coverage may not be useful since the image target sequence and the feasibility of said sequence given the rotation-rate limitations of the spacecraft are not taken into account. This work presents a means of optimizing, in a multi-objective manner, surface target sequences that account for such limitations.

Hinckley, David, Jr.↗
NASA NTRS2017

Multi-Objective Optimization of Spacecraft Trajectories for Small-Body Coverage Missions

Visual coverage of surface elements of a small-body object requires multiple images to be taken that meet many requirements on their viewing angles, illumination angles, times of day, and combinations thereof. Designing trajectories capable of maximizing total possible coverage may not be useful since the image target sequence and the feasibility of said sequence given the rotation-rate limitations of the spacecraft are not taken into account. This work presents a means of optimizing, in a multi-objective manner, surface target sequences that account for such limitations.

Hinckley, David, Jr.↗
NASA NTRS2024

Validation and Application of Satellite-Derived Sea Surface Temperature Gradients in the Bering Strait and Bering Sea

The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.

Arctic↗
DOE OSTI2026

Deep Gaussian process-based cost-aware batch Bayesian optimization for complex materials design campaigns

The accelerating pace and expanding scope of materials discovery demand optimization frameworks that efficiently navigate vast design spaces with complex response surfaces while judiciously allocating limited evaluation resources. We present a cost-aware, batch Bayesian optimization scheme powered by deep Gaussian process (DGP) surrogates and a heterotopic querying strategy. Our DGP surrogate, formed by stacking GP layers, models complex hierarchical relationships among high-dimensional compositional features and captures correlations across multiple target properties, propagating uncertainty through successive layers. We integrate evaluation cost into an upper-confidence-bound acquisition extension, which, together with heterotopic querying, proposes small batches of candidates in parallel, balancing exploration of under-characterized regions with exploitation of high-mean, low-variance predictions across correlated properties. Applied to refractory high-entropy alloys for high-temperature applications, our framework converges to optimal formulations in fewer iterations with cost-aware queries than conventional GP-based BO, highlighting the value of deep, uncertainty-aware, cost-sensitive strategies in materials campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of dilute Rh on oxygen dissociation, spillover, and the oxidation of Cu across many orders of magnitude pressure

Knowledge of how trace amounts of more reactive metals influence the oxidation rate and mechanism of Cu surfaces is essential for developing strategies to optimize the performance of Cu-based catalysts. We find that the addition of 1% Rh to Cu(111) increases the initial O 2 dissociation rate by approximately 9-fold. CO poisoning experiments reveal that single Rh atoms activate O 2 and facilitate the spillover of atomic oxygen to Cu sites. Scanning tunneling microscopy (STM) and in situ X-ray photoelectron spectroscopy (XPS) support this mechanism, showing enhanced surface oxygen near Rh atoms. Here, a density functional theory (DFT)-based model demonstrates that Rh binds the O 2 precursor 0.15 eV more strongly than Cu(111) and lowers the O 2 dissociation barrier by 0.02 eV. Both single-crystal and nanoparticle experiments show that at low oxygen pressures, Rh enhances Cu oxidation, whereas at higher pressures, it inhibits deeper oxidation, as evidenced by in situ ultraviolet-visible (UV-vis) spectra.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Providing Long-term Solar and Meteorological Resource Information from NASA Research through the GIS-Enabled POWER Web Services Portal

Solar and other renewable energy systems are optimized using geophysical parameters describing information about the solar resource and meteorological environments and how those environments may be changing in time. The Prediction of Worldwide Renewable Energy Resource (POWER) team at the NASA LaRC Research Center deployed its first version of the revitalized POWER geophysical parameter website that employs Esri Geographic Information System (GIS) tools. This web application provides access to both time series and climatological data sets spanning from a few days behind real-time back to the early 1980’s with a spatial resolution of 0.5 x 0.5 degree, thus extending over 30 years. The GIS tools enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility to government agencies, industry and individuals. There is an API that provides data through a URL coding and can also invoked inside user software packages. Output data formats now include ASCII, CSV, geoTiff, JSON and .netCDF. Since May 2018, over 10.4 TB of data have been delivered to fulfill over 110 million data requests from 240,000 unique user IPs (https://power.larc.nasa.gov). This presentation provides an overview of this project and the current version of the new POWER web capabilities through to the end usage. Surface solar parameters are adapted from both the NASA/GEWEX (Global and Energy Water Cycle Exchange) SRB (Surface Radiation Budget) project and the CERES (Clouds and Earth’s Radiant Energy System) data products. The meteorological parameters are adapted from NASA’s MERRA-2 (Modern Era Retrospective-analysis for Research and Applications). We review uncertainty of various basic parameters using surface measurements. After the introduction, we specifically discuss various clusters of parameters for equator pointing tilted surfaces that provide for the estimation of optimal tilt angle by month and year. The discussion will emphasize a few examples of how solar and building engineers are using the data products. We will then preview the capabilities of Version 2 featuring examples of hourly solar and meteorological data products, customized user reports and expanded web mapping services from CERES data products. The web services provide a unique, expandable resource for renewable energy systems engineers to design, evaluate and optimize to environments worldwide.

Solar Resource↗
NASA NTRS2005

Experience With Bayesian Image Based Surface Modeling

Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.

Stutz, John C.↗
DOE OSTI2024

Analytical ab initio hessian from a deep learning potential for transition state optimization

Identifying transition states—saddle points on the potential energy surface connecting reactant and product minima—is central to predicting kinetic barriers and understanding chemical reaction mechanisms. In this work, we train a fully differentiable equivariant neural network potential, NewtonNet, on thousands of organic reactions and derive the analytical Hessians. By reducing the computational cost by several orders of magnitude relative to the density functional theory (DFT) ab initio source, we can afford to use the learned Hessians at every step for the saddle point optimizations. We show that the full machine learned (ML) Hessian robustly finds the transition states of 240 unseen organic reactions, even when the quality of the initial guess structures are degraded, while reducing the number of optimization steps to convergence by 2–3× compared to the quasi-Newton DFT and ML methods. All data generation, NewtonNet model, and ML transition state finding methods are available in an automated workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Evaluation of Precipitation Detection over Various Surfaces from Passive Microwave Imagers and Sounders

During the middle part of this decade a wide variety of passive microwave imagers and sounders will be unified in the Global Precipitation Measurement (GPM) mission to provide a common basis for frequent (3 hr), global precipitation monitoring. The ability of these sensors to detect precipitation by discerning it from non-precipitating background depends upon the channels available and characteristics of the surface and atmosphere. This study quantifies the minimum detectable precipitation rate and fraction of precipitation detected for four representative instruments (TMI, GMI, AMSU-A, and AMSU-B) that will be part of the GPM constellation. Observations for these instruments were constructed from equivalent channels on the SSMIS instrument on DMSP satellites F16 and F17 and matched to precipitation data from NOAA's National Mosaic and QPE (NMQ) during 2009 over the continuous United States. A variational optimal estimation retrieval of non-precipitation surface and atmosphere parameters was used to determine the consistency between the observed brightness temperatures and these parameters, with high cost function values shown to be related to precipitation. The minimum detectable precipitation rate, defined as the lowest rate for which probability of detection exceeds 50%, and the detected fraction of precipitation, are reported for each sensor, surface type (ocean, coast, bare land, snow cover) and precipitation type (rain, mix, snow). The best sensors over ocean and bare land were GMI (0.22 mm/hr minimum threshold and 90% of precipitation detected) and AMSU (0.26 mm/hr minimum threshold and 81% of precipitation detected), respectively. Over coasts (0.74 mm/hr threshold and 12% detected) and snow-covered surfaces (0.44 mm/hr threshold and 23% detected), AMSU again performed best but with much lower detection skill, whereas TMI had no skill over these surfaces. The sounders (particularly over water) benefited from the use of re-analysis data (vs. climatology) to set the a-priori atmospheric state and all instruments benefit from the use of a conditional snow cover emissivity database over land. It is recommended that real-time sources of these data be used in the operational GPM precipitation algorithms.

GPM↗