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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Soluble minerals in chemical evolution. I - Adsorption of 5-prime-AMP on CaSO4 - A model system

The adsorption of 5-prime-AMP onto solid CaSO4-2H2O was studied in a saturated suspension as a function of pH and electrolyte concentration. The adsorption is pH-dependent and is directly correlated with the charge on the 5-prime-AMP molecule which is determined by the state of protonation of the N-1 nitrogen of the purine ring and the phosphate oxygens. It is proposed that the binding that occurs between the nucleotide and the salt is electrostatic in nature. The adsorption decreases with increasing ionic strength of the solution which means that in a fluctuating environment of wetting and drying cycles, a biomolecule similar to 5-prime-AMP could be expected to desorb during the drying phase. The results indicate that CaSO4-2H2O can serve as a concentrating surface for biomolecules. The significance of this is discussed with regard to the possible role of soluble minerals and their surfaces in a geochemical model consistent with the evolution of the earth and the origin of life.

Orenberg, J. B.↗
DOE OSTI2025

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗
DOE OSTI2018

Camelina sativa , an oilseed at the nexus between model system and commercial crop

The rapid assessment of metabolic engineering strategies in plants is aided by crops that provide simple, high throughput transformation systems, a sequenced genome, and the ability to evaluate the resulting plants in field trials. Camelina sativa provides all of these attributes in a robust oilseed platform. The ability to perform field evaluation of Camelina is a useful, and in some studies essential benefit that allows researchers to evaluate how traits perform outside the strictly controlled conditions of a greenhouse. In the field the plants are subjected to higher light intensities, seasonal diurnal variations in temperature and light, competition for nutrients, and watering regimes dictated by natural weather patterns, all which may affect trait performance. There are difficulties associated with the use of Camelina . The current genetic resources available for Camelina pale in comparison to those developed for the model plant Arabidopsis thaliana; however, the sequence similarity of the Arabidopsis and Camelina genomes often allows the use of Arabidopsis as a reference when additional information is needed. Camelina ’s genome, an allohexaploid, is more complex than other model crops, but the diploid inheritance of its three subgenomes is straightforward. The need to navigate three copies of each gene in genome editing or mutagenesis experiments adds some complexity but also provides advantages for gene dosage experiments. In conclusion, the ability to quickly engineer Camelina with novel traits, advance generations, and bulk up homozygous lines for small-scale field tests in less than a year, in our opinion, far outweighs the complexities associated with the crop.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Entry Systems Modeling and Ground Testing: Enabling Flight Performance and Risk Reduction

Entry, Descent, and Landing (EDL) comprise a relatively small portion of a mission’s timeline, however, it is typically among the largest risks. Flying through a body’s atmosphere reliably and accurately – from orbit to ground or via aerocapture – is a critical step toward successful in situ exploration. This exhibit will highlight EDL simulation and ground test capabilities, both existing and under development, that could support mission design, risk reduction, and post-flight analysis for Planetary Science mission concepts displayed in the 2023 SMD Planetary Science Technology Showcase.

Entry Systems↗
DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrated Circular Economy Model System for Direct Lithium Extraction: From Minerals to Batteries Utilizing Aluminum Hydroxide

Aluminum hydroxide, an abundant mineral found in nature, exists in four polymorphs: gibbsite, bayerite, nordstrandite, and doyleite. Among these polymorphs gibbsite, bayerite, and commercially synthesized amorphous aluminum hydroxide have been investigated as sorbent materials for lithium extraction from sulfate solutions. The amorphous form of Al(OH) 3 exhibits a reactivity higher than that of the naturally occurring crystalline polymorphs in terms of extracting Li + ions. This study employed high-temperature oxide melt solution calorimetry to explore the energetics of the sorbent polymorphs. The enthalpic stability order was measured to be gibbsite > bayerite > amorphous Al(OH) 3 . The least stable form, amorphous Al(OH) 3 , undergoes a spontaneous reaction with lithium, resulting in the formation of a stable layered double hydroxide phase. Consequently, amorphous Al(OH) 3 shows promise as a sorbent material for selectively extracting lithium from clay mineral leachate solutions. Further, this research demonstrates the selective direct extraction of Li + ions using amorphous aluminum hydroxide through a liquid–solid lithiation reaction, followed by acid-free delithiation and relithiation processes, achieving an extraction efficiency of 86%, and the maximum capacity was 37.86 mg·g –1 in a single step during lithiation. With high selectivity during lithiation and nearly complete recoverability of the sorbent material during delithiation, this method presents a circular economy model. Furthermore, a life cycle analysis was conducted to illustrate the environmental advantages of replacing the conventional soda ash-based precipitation process with this method, along with a simple operational cost analysis to evaluate reagent and fuel expenses.

25 ENERGY STORAGE↗
DOE OSTI2019

Model systems for screening and investigation of lithium metal electrode chemistry and dendrite formation

The use of lithium metal as an electrode for electrochemical energy storage will provide a significant impact on practical energy storage technology. Unfortunately, the use of lithium metal is plagued with challenging chemical problems. Specifically, the formation of a solid electrolyte interphase layer and the nucleation and growth of lithium dendrites: both must be addressed and controlled in order to achieve a practically useable pure lithium metal electrode. Currently sophisticated experimental techniques and computationally expensive simulations are being used to probe these problems but these methods are arduous and time consuming which delays timely evaluation and insight into the rapidly changing field of advanced energy storage. Here, we report the use of DFT simulations of lithium nanoclusters to investigate and explore lithium metal chemistry with inexpensive computational methods to gain greater insight into electrochemical reductions and the nucleation and growth of dendrites. DME, LiTFSI, and LiFSI reduction energetics and structures with electrode effects from lithium metal are reported providing better physical description of the absolute reduction potential characterization. The electronic structure of the lithium nanoclusters were used to investigate the nucleation and growth of lithium dendrites from an ab initio perspective. The results demonstrate that kinetic processes have more control over non uniform growth than thermodynamic processes. Based on this information, a non ab initio model was created in Matlab that shows the initial stages of dendrite nucleation considering approximately 2000 atoms.

25 ENERGY STORAGE↗
NASA NTRS1999

Model system for plant cell biology: GFP imaging in living onion epidermal cells

The ability to visualize organelle localization and dynamics is very useful in studying cellular physiological events. Until recently, this has been accomplished using a variety of staining methods. However, staining can give inaccurate information due to nonspecific staining, diffusion of the stain or through toxic effects. The ability to target green fluorescent protein (GFP) to various organelles allows for specific labeling of organelles in vivo. The disadvantages of GFP thus far have been the time and money involved in developing stable transformants or maintaining cell cultures for transient expression. In this paper, we present a rapid transient expression system using onion epidermal peels. We have localized GFP to various cellular compartments (including the cell wall) to illustrate the utility of this method and to visualize dynamics of these compartments. The onion epidermis has large, living, transparent cells in a monolayer, making them ideal for visualizing GFP. This method is easy and inexpensive, and it allows for testing of new GFP fusion proteins in a living tissue to determine deleterious effects and the ability to express before stable transformants are attempted.

NASA Discipline Plant Biology↗
DOE OSTI2022

Using the Criticality Accident Alarm System modeling capabilities in SCALE [Slides]

The following is a summary of advice for CAAS modeling in SCALE. Refer to the SCALE Criticality Safety and Radiation Shielding training slides or to the SCALE manual for exact syntax. Use a mesh for the fission source that is the most adequate for the problem to solve (coarse/fine). Don’t spend unnecessary resources; simplify the model if it does not impact the final results of interest. Be careful to deactivate secondary fissions in MAVRIC or the calculation may never end. Check that k eff and $\overline{\upsilon}$ calculated results are logical. Between KENO and MAVRIC, cross section libraries, materials, geometry, and mesh grid can be the same or different. Iterative calculations are usually complex problems that need variance reduction. It will be hard to find the best solving parameters in the first attempt; expert judgement is needed. Check each step separately. Use Fulcrum to visualize fission source, mesh source, and spatial/energy distributions to find potential errors or impactful imprecisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

NASA Spacecraft Trade Modeling System (NSTRDMS)

A rapid mission analysis tool is developed to support the ongoing design of the Lunar Transit trajectory of the Power and Propulsion Element (PPE). A 50-kW class electric propulsion system is envisioned to transit a massive vehicle be-tween a Medium Earth Orbit (MEO) parking orbit and a lunar L2 southern Near Rectilinear Halo Orbit (NRHO). A parameterization is developed by which the Lunar Transit can be analyzed in the context of varying vehicle mass, solar elec-tric propulsion (SEP) configurations, and solar array power output. A rapid and novel mission analysis tool enables a wide array of these trade analyses to be completed without the need for extensive computing resources or time. This tool is shown to be useful in the analysis of a reference trajectory, where changes to the baseline vehicle architecture or off-nominal operational scenarios (such as electric thruster failures) can be rapidly assessed by the mission designer.

Low thrust↗
NASA NTRS2023

Overview of the NASA Spacecraft Trade Modeling System (NSTRDMS), A Rapid Mission Analysis Tool

A rapid mission analysis tool is developed to support the ongoing design of the Lunar Transit trajectory of the Power and Propulsion Element (PPE). A 50-kW class electric propulsion system is envisioned to transit a massive vehicle be-tween a Medium Earth Orbit (MEO) parking orbit and a lunar L2 southern Near Rectilinear Halo Orbit (NRHO). A parameterization is developed by which the Lunar Transit can be analyzed in the context of varying vehicle mass, solar elec-tric propulsion (SEP) configurations, and solar array power output. A rapid and novel mission analysis tool enables a wide array of these trade analyses to be completed without the need for extensive computing resources or time. This tool is shown to be useful in the analysis of a reference trajectory, where changes to the baseline vehicle architecture or off-nominal operational scenarios (such as electric thruster failures) can be rapidly assessed by the mission designer.

Low thrust↗
DOE OSTI2022

Electric Vehicle and Infrastructure Systems Modeling in Washington D.C. and Baltimore

This report documents the Argonne-Exelon effort to develop and utilize an agent-based model (ATEAM) of charging demand and infrastructure expansion applicable to the Washington, DC–Baltimore, MD consolidated metropolitan area. This study extends the ATEAM model time horizon to 10 years (from 2020 to 2030), expands agent behavior modeling capabilities, incorporates more granular and extensive empirical data on charging behavior, and analyzes charging needs for a much larger population of PEVs, in keeping with regional goals for significant adoption of ZEVs. With given targets for annual BEV adoption, five scenarios were developed to examine public infrastructure needs and resulting charging load, considering different home charging availabilities, as well as different PEV consumer profiles and public charging infrastructure deployment strategies. Scenario results show that if new chargers (both L2 and DCFC) are spread more widely (as with ubiquitous deployment strategies), there will be less variation in the number of chargers added to each census tract in the study area. More importantly, widespread public charging infrastructure with ubiquitous deployment strategies reduces unmet charging demand and improves charging success, even with heavy reliance on public charging. About 80 percent of BEV drivers can charge on their first attempt in scenarios with ubiquitous deployment strategies. Moreover, widespread public charging infrastructure better meets the demand for more charging, and in return, increases BEV adoption. Low home charging availability produces higher charging loads in public locations, especially during the early morning (around 8:00 a.m.) and late afternoon (around 6:00 p.m.). The evening peak load indicates that drivers are taking advantage of public charging before heading home. Study results also indicate that even with 20 percent home charging availability in 2030, just 20 percent of drivers attempt to charge on a given day. With their relatively high electric range (200+ miles), the BEVs expected to be on the road in 2030 can handle daily commutes without re-charging for a couple of days.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Impacts of cloud superparameterization on projected daily rainfall intensity climate changes in multiple versions of the Community Earth System Model

Abstract Changes in the character of rainfall are assessed using a holistic set of statistics based on rainfall frequency and amount distributions in climate change experiments with three conventional and superparameterized versions of the Community Atmosphere Model (CAM and SPCAM). Previous work has shown that high‐order statistics of present‐day rainfall intensity are significantly improved with superparameterization, especially in regions of tropical convection. Globally, the two modeling approaches project a similar future increase in mean rainfall, especially across the Inter‐Tropical Convergence Zone (ITCZ) and at high latitudes, but over land, SPCAM predicts a smaller mean change than CAM. Changes in high‐order statistics are similar at high latitudes in the two models but diverge at lower latitudes. In the tropics, SPCAM projects a large intensification of moderate and extreme rain rates in regions of organized convection associated with the Madden Julian Oscillation, ITCZ, monsoons, and tropical waves. In contrast, this signal is missing in all versions of CAM, which are found to be prone to predicting increases in the amount but not intensity of moderate rates. Predictions from SPCAM exhibit a scale‐insensitive behavior with little dependence on horizontal resolution for extreme rates, while lower resolution (∼2°) versions of CAM are not able to capture the response simulated with higher resolution (∼1°). Moderate rain rates analyzed by the “amount mode” and “amount median” are found to be especially telling as a diagnostic for evaluating climate model performance and tracing future changes in rainfall statistics to tropical wave modes in SPCAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Enabling immersive engagement in energy system models with deep learning

Complex ensembles of energy simulation models have become crucial components of renewable energy research in recent years. Often the increasing computational cost, high-dimensional structure, and other complexities hinder researchers from fully utilizing these data sources for knowledge building. Researchers at National Renewable Energy Laboratory have determined an immersive visualization workflow to dramatically improve user engagement and analysis capability through a combination of low-dimensional structure analysis, deep learning, and custom visualization methods. We present case studies for two energy simulation platforms.

97 MATHEMATICS AND COMPUTING↗