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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electromagnetic Radioisotope Separator for Methods Development, Testing, and Training

The major goal of the project is the construction and operation of an electromagnetic isotope separator. Included in that goal is the construction and installation of a high throughput surface ion source, with specific applicability to the Lanthanides. The surface ion source features a single-piece titanium crucible insert that mates with a tantalum hot surface ionizer. The titanium crucible, which does not readily activate, can be loaded with samarium and then irradiated simultaneously, greatly reducing operator dose.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Monitoring, Reporting, and Verification Considerations for Carbon Dioxide Removal

The project investigates Measurement, Reporting, and Verification (MRV) methods for Enhanced Weathering and Marine Carbon Dioxide Removal (mCDR) technologies. Enhanced Weathering accelerates natural mineral processes to capture CO2, while mCDR leverages oceanic processes for carbon sequestration. The study focuses on developing standardized MRV protocols, assessing environmental impacts, and evaluating the scalability and economic feasibility of these carbon sequestration methods. The goal is to ensure reliable and transparent data for validating and improving CO2 removal technologies.

Priyadarshini↗
DOE OSTI2024

Advancing the Understanding of Manufacturing Tools for Hardware Security

This project’s goal was to explore new methods and tools to evaluate the focused ion beam (FIB) effect on active electrical devices, which is becoming increasingly challenged by the continual decrease in transistor geometry. Novel hole transfer methods leveraging FIB patterning were demonstrated utilizing selective area atomic layer deposition (ALD) and metal assisted chemical etching. A FIB damage electrical tester device was fabricated, and the effects of FIB beams were characterized by examining change in performance of damaged transistors. Detailed characterization of end-of-range damage for common FIB ions were correlated to modeling methods. Finally, undamaged and damaged devices were simulated by Charon to begin understanding the FIB effects on active devices. This test platform along with modeling methods give a powerful way to assess FIB damage in materials and devices, and with more development can help establish methods to predict FIB damage effects on electrical devices.

42 ENGINEERING↗
DOE OSTI2024

De novo Materials Design of Catalytic Surface Motifs for Water-Gas-Shift (Final Progress Report DOE Grant DE-SC0019281)

This project was aimed at developing innovative theoretical methods and models to understand essential catalysis-relevant issues such as CO 2 conversion, fuel cells, and lithium batteries. Through collaborations with experimentalists, we strive to develop new quantum and machine learning methods for the understanding of surface and interfacial chemistry that can empower the design of energy and sustainability systems. Overall, our work under this grant brings cross-disciplinary insights into catalytic materials, microenvironments, and other conditions, which can serve to provide design rules for the next generation of catalysts.

25 ENERGY STORAGE↗
DOE OSTI2025

Dynamic Model Development of a Wind Power Plant Using Neural Net Method to Forecast Wind Power Output (CRADA Final Report)

This project is intended to model wind power plant based on monitored data at the wind power plant. This project will promote the university research in Renewable Energy area and trains the future highly qualified engineers. The dynamic model will be based on neural net model with the input from the two met towers (12 inputs), and the number of turbines in operation (one input). The overall input will be 13 inputs to drive the simulations. The output power at the point of interconnection will be used to tune the neural net weight coefficients. Two neural net concepts will be investigated (the back propagation neural net and the dynamic recurrent neural net with feedback).

17 WIND ENERGY↗
DOE OSTI2025

Evaluating Probability of Assessment for Central Alarm Station Operators

This project focused on developing and analyzing a method that could be employed by operational nuclear facilities to evaluate their CAS operators and determine a probability of assessment for each operator. This method is agnostic of alarm communication and display system (AC&D), sensors and cameras in place in the field, and any other technical security measures. This security-measure-agnostic method enables operational facilities to adopt it to determine the effectiveness of their alarm station operators.

42 ENGINEERING↗
DOE OSTI2025

Simultaneous Celestial Navigation

GPS technology is used in a multitude of applications around the world for navigation. However, GPS can be contested or denied and thus alternatives to GPS are needed for positioning in high-consequence systems. This project investigates a non-RF based method to produce an estimated geolocation using stellar/celestial measurements in combination with measurements from inclinometers and a real time clock. The initial iteration of this method, developed in FY20/21, achieved an estimated location accuracy within approximately 3 kilometers of the true location with a 3-sigma bound of about 8 kilometers. The next iteration aims to enhance this technology further, targeting an estimation accuracy within 100 meters of the true location, representing a 30-fold improvement over the initial method.

42 ENGINEERING↗
DOE OSTI2025

Understanding Mechanisms of Selective Crystal Nucleation and Growth Using In Situ Electron Microscopy

Separation processes are essential for purifying and isolating critical materials, but are challenging due to the natural tendency of systems to mix. This project explores far-from-equilibrium separation methods using external electric and magnetic fields to drive selective nucleation and crystal growth. Using in situ electrochemical transmission electron microscopy (TEM), we observed ion transport and crystallization behavior under applied electric fields. We found that ions migrate toward the working electrode, where nucleation preferentially occurs. These findings advance our understanding of non-equilibrium separation mechanisms and support the development of efficient, sustainable methods for extracting critical materials from unconventional domestic sources.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding Biases in Sample Preparation Techniques for Coupled Scanning Electron Microscopy and MAMA PuO 2 Morphological Analysis

In this project, the scanning electron microscopy (SEM) sampling method used during the statistical design study (SDS) was investigated to determine if any sampling biases were present in the analyzed data. Using standard particle size distribution powders from the National Institute of Standards and Technology (NIST 1984 standard reference material) with the origin wet dispersion method, it was determined that a bias to smaller particles was present. This was supported by theoretical calculations using Stokes’ law to determine the settling rate of spherical particles of roughly the same size and mass as those found in the SDS. Based on the theoretical calculations, it was determined that the settling rate for each of the 76 powder sets in the SDS could be unique based on specific particle shape and mass distributions, making a universal correction factor/formula not applicable. Therefore, priority shifted to developing an improved wet dispersion method that significantly reduced the particle settling rate for all particle size and shapes. This was achieved by replacing the original solvent (isopropyl alcohol) with a heavy liquid (lithium heteropolytungstates), which dramatically slowed the settling rate and allowed for the capture of a suitable homogeneous aliquot. SEM imaging and Morphological Analysis for Material Attribution (MAMA) software analysis were conducted on the NIST standard, and the SEM/MAMA data were compared to data captured by a dynamic image analysis particle size analyzer. The resulting data confirmed that the new wet dispersion method does indeed deliver an improved representative aliquot to the SEM stub. For instance, in the NIST certificate, the average particle size is ~17.1 µm ± 2.2 µm with a normal distribution. The initial wet dispersion method resulted in a drastically reduced average particle size of 6.1 µm in addition to a non-representative heavy bi-modal distribution whereas the improved LST wet dispersion method resulting in an average particle size that was much closer to the NIST certificate (12.7 µm) with a similar normal distribution. Although the improved method was still short of the NIST certificate average, atomic force microscopy analysis determined that the resulting ~20-25% reduction in size was due to particles sinking into the carbon sticky tape used for SEM imaging. It is believed that that this bias can be calibrated in a much more predicable manner than the original settling rate bias. In addition, the matching normal distribution curves between the NIST certificate and the heavy liquid method indicate a much-improved representative aliquot has been sampled and imaged. A surrogate CeO 2 powder was used to reflect PuO 2 more accurately and to aid in implementing radiological controls and shielding. The resulting data sets from the SEM/MAMA method and the particle size analyzer give almost identical average particle sizes and particle distribution statistics. Future work will re-analyze several select runs from the SDS to determine if morphological signatures can be found with the improved sampling method.

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

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Skipper CCD Parameter Optimization with ML

The development of novel detectors faces a bottleneck in the 'parameter selection' phase. A significant amount of a scientist's time must be spent characterizing and testing various parameters in order to optimize them for different science goals. This process can be streamlined with closed-loop Bayesian Optimization (BO), using Gaussian Processes through live measurements on the device. In this project, we demonstrate the effectiveness of this method in parameter optimization on Skipper CCDs and its potential to be fully automated.

Hope, Andrew [Michigan Tech. U.]↗
DOE OSTI2025

The DECADE cosmic shear project IV: cosmological constraints from 107 million galaxies across 5,400 deg$^2$ of the sky

We present cosmological constraints from the Dark Energy Camera All Data Everywhere (DECADE) cosmic shear analysis. This work uses shape measurements for 107 million galaxies measured through Dark Energy Camera (DECam) imaging of $5,\!412$ deg$^2$ of sky that is outside the Dark Energy Survey (DES) footprint. We derive constraints on the cosmological parameters $S_8 = 0.791^{+0.027}_{-0.032}$ and $Ω_{\rm m} =0.269^{+0.034}_{-0.050}$ for the $Λ$CDM model, which are consistent with those from other weak lensing surveys and from the cosmic microwave background. We combine our results with cosmic shear results from DES Y3 at the likelihood level, since the two datasets span independent areas on the sky. The combined measurements, which cover $\approx\! 10,\!000$ deg$^2$, prefer $S_8 = 0.791 \pm 0.023$ and $Ω_{\rm m} = 0.277^{+0.034}_{-0.046}$ under the $Λ$CDM model. These results are the culmination of a series of rigorous studies that characterize and validate the DECADE dataset and the associated analysis methodologies (Anbajagane et. al 2025a,b,c). Overall, the DECADE project demonstrates that the cosmic shear analysis methods employed in Stage-III weak lensing surveys can provide robust cosmological constraints for fairly inhomogeneous datasets. This opens the possibility of using data that have been previously categorized as ``unusable'' for cosmic shear analyses, thereby increasing the statistical power of upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Direct reactions with the AT-TPC

Direct reactions are crucial tools for accessing properties of the atomic nucleus. Fundamental and exotic phenomena such as collective modes, pairing, weakbinding effects and evolution of single-particles energies can be investigated in peripheral collisions between a heavy nucleus and a light target. The necessity of using inverse kinematics to reveal how these structural properties change with isospin imbalance renders direct reactions a challenging technique when using the missing mass method. In this scenario, Active Target Time Projection Chambers (AT-TPC) have demonstrated an outstanding performance in enabling these types of reactions even under conditions of very low beam intensities. The AT-TPC of the Facility for Rare Isotope Beams (FRIB) is a next generation multipurpose Active Target. When operated inside a solenoidal magnet, direct reactions benefit from the measurement of the magnetic rigidity that enables particle identification and the determination of the excitation energy with high resolution without the need of auxiliary detectors. Additionally, the AT-TPC can be coupled to a magnetic spectrometer improving even further its spectroscopic investigation capability. In this contribution, we discuss inelastic scattering and transfer reaction data obtained via the AT-TPC and compare them to theory. In particular, we present the results for the 14 C(p,p′) and 12 Be (p,d) 11 Be reactions. For 14 C, we compare the experimental excitation energy of the first 1 – excited state with coupled-cluster calculationsbased on nuclear interactions from chiral effective field theory and with available shell-model predictions. For 12 Be, we determine the theoretical spectroscopic factors of the 12 Be (p,d) 11 Be transfer reaction in the shell modeland compare them to the experimental excitation spectrum from a qualitative standpoint.

active target↗
DOE OSTI2023

Searches for Extremely Metal-poor Galaxies Using Arecibo Legacy Fast ALFA–Selected Dwarf Galaxies

We present a study of nearby dwarf galaxies selected from the Arecibo Legacy Fast ALFA (ALFALFA) blind H I survey. A primary goal of the project was to utilize a nonstandard selection method with the hope of detecting previously unrecognized extremely metal-poor (XMP) galaxies. The study was motivated by the recent discovery of two XMP galaxies, Leo P and Leoncino, which were both originally found via the ALFALFA survey. We have obtained narrowband H α images for 42 dwarf systems, many of which are located in the Local Void in front of the Pisces–Perseus Supercluster. Spectra for 11 of the best candidates resulted in the determination of metal abundances for 10 of the systems. None were found to be extremely metal-poor, although one system (AGC 123350) was found to have an oxygen abundance of log(O/H)+12 = 7.46, or ~6% solar. One of the galaxies in our sample exhibits a high oxygen abundance for its luminosity, suggesting the possibility that it may have a tidal origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2

The development, implementation, and evaluation of a new weakly coupled ocean data assimilation (WCODA) system for the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2) utilizing the four-dimensional ensemble variational (4DEnVar) method are presented in this study. The 4DEnVar method, based on the dimension-reduced projection four-dimensional variational (DRP-4DVar) approach, replaces the adjoint model with the ensemble technique, thereby reducing computational demands. Monthly mean ocean temperature and salinity data from the EN4.2.1 reanalysis are integrated into the ocean component of E3SMv2 from 1950 to 2021 with the goal of providing realistic initial conditions for decadal predictions and predictability studies. The performance of the WCODA system is assessed using various metrics, including the reduction rate of the cost function, root mean square error (RMSE) differences, correlation differences, and model biases. Results indicate that the WCODA system effectively assimilates the reanalysis data into the climate model, consistently achieving negative reduction rates of the cost function and notable improvements in RMSE and correlation across various ocean layers and regions. Significant enhancements are observed in the upper ocean layers across the majority of global ocean regions, particularly in the north Atlantic, north Pacific, and Indian Ocean. Model biases in sea surface temperature and salinity are also substantially reduced. For sea surface temperature, cold biases in the north Pacific and north Atlantic are diminished by about 1–2 °C, and warm biases in the Southern Ocean are corrected by approximately 1.5–2.5 °C. In terms of salinity, improvements are observed with bias reductions of about 0.5–1 psu in the north Atlantic and north Pacific and up to 1.5 psu in parts of the Southern Ocean. The ultimate goal of the WCODA system is to advance the predictive capabilities of E3SM for subseasonal to decadal climate predictions, thereby supporting research on strategic energy-sector policies and planning.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1969

Ground-based microwave probing

Theoretical and experimental activities in remote sensing were conducted. The projects are: (1) the linear statistical inversion method, (2) vertical temperature profile determination from microwave emission measurements near 60 GHz, (3) radio path length correction determination from emission measurements at 20.6 GHz, and (4) liquid water content determination of thunderstorm cells by emission measurements at 10.7 GHz.

Westwater, E. R.↗