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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

GCKP84--General Chemical Kinetics Code for Gas-Phase Flow and Batch Processes Including Heat Transfer Effects

A general chemical kinetics code is described for complex, homogeneous ideal gas reactions in any chemical system. The main features of the GCKP84 code are flexibility, convenience, and speed of computation for many different reaction conditions. The code, which replaces the GCKP code published previously, solves numerically the differential equations for complex reaction in a batch system or one dimensional inviscid flow. It also solves numerically the nonlinear algebraic equations describing the well stirred reactor. A new state of the art numerical integration method is used for greatly increased speed in handling systems of stiff differential equations. The theory and the computer program, including details of input preparation and a guide to using the code are given.

David A Bittker↗
NASA NTRS1972

General chemical kinetics computer program for static and flow reactions, with application to combustion and shock-tube kinetics

A general chemical kinetics program is described for complex, homogeneous ideal-gas reactions in any chemical system. Its main features are flexibility and convenience in treating many different reaction conditions. The program solves numerically the differential equations describing complex reaction in either a static system or one-dimensional inviscid flow. Applications include ignition and combustion, shock wave reactions, and general reactions in a flowing or static system. An implicit numerical solution method is used which works efficiently for the extreme conditions of a very slow or a very fast reaction. The theory is described, and the computer program and users' manual are included.

Bittker, D. A.↗
DOE OSTI2022

Machine learning models for rat multigeneration reproductive toxicity prediction

Reproductive toxicity is one of the prominent endpoints in the risk assessment of environmental and industrial chemicals. Due to the complexity of the reproductive system, traditional reproductive toxicity testing in animals, especially guideline multigeneration reproductive toxicity studies, take a long time and are expensive. Therefore, machine learning, as a promising alternative approach, should be considered when evaluating the reproductive toxicity of chemicals. We curated rat multigeneration reproductive toxicity testing data of 275 chemicals from ToxRefDB (Toxicity Reference Database) and developed predictive models using seven machine learning algorithms (decision tree, decision forest, random forest, k-nearest neighbors, support vector machine, linear discriminant analysis, and logistic regression). A consensus model was built based on the seven individual models. An external validation set was curated from the COSMOS database and the literature. The performances of individual and consensus models were evaluated using 500 iterations of 5-fold cross-validations and the external validation data set. The balanced accuracy of the models ranged from 58% to 65% in the 5-fold cross-validations and 45%–61% in the external validations. Prediction confidence analysis was conducted to provide additional information for more appropriate applications of the developed models. The impact of our findings is in increasing confidence in machine learning models. We demonstrate the importance of using consensus models for harnessing the benefits of multiple machine learning models (i.e., using redundant systems to check validity of outcomes). While we continue to build upon the models to better characterize weak toxicants, there is current utility in saving resources by being able to screen out strong reproductive toxicants before investing in vivo testing. The modeling approach (machine learning models) is offered for assessing the rat multigeneration reproductive toxicity of chemicals. Our results suggest that machine learning may be a promising alternative approach to evaluate the potential reproductive toxicity of chemicals.

consensus model↗
DOE OSTI2022

Protein Electric Fields Enable Faster and Longer-Lasting Covalent Inhibition of β-Lactamases

The widespread design of covalent drugs has focused on crafting reactive groups of proper electrophilicity and positioning towards targeted amino-acid nucleophiles. In this work, we found that environmental electric fields projected onto a reactive chemical bond, an overlooked design element, play essential roles in the covalent inhibition of TEM-1 beta-lactamase by avibactam. Using the vibrational Stark effect, the magnitudes of the electric fields that are exerted by TEM active sites onto avibactam’s reactive C=O were measured and demonstrate an electrostatic gating effect that promotes bond formation yet relatively suppresses the reverse dissociation. These results suggest new principles of covalent drug design and off-target site prediction. Unlike shape and electrostatic complementary which address binding constants, electrostatic catalysis drives reaction rates, essential for covalent inhibition, and deepens our understanding of chemical reactivity, selectivity, and stability in complex systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Quantum electron transport in degenerate donor–acceptor systems

In this work, we develop a mathematically rigorous theory for the quantum transfer processes in degenerate donor–acceptor dimers in contact with a thermal environment. We explicitly calculate the transfer rates and the acceptor population efficiency. The latter depends critically on the initial donor state. Additionally, we show that quantum coherence in the initial state enhances the transfer process. If the electron is initially shared coherently by the donor levels, then the efficiency can reach values close to 100%, while an incoherent initial donor state will significantly suppress the efficiency. The results are useful for a better understanding of the quantum electron transport in many chemical, solid state, and biological systems with complex degenerate and quasi-degenerate energy landscapes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring the nexus of many-body theories through neural network techniques: the tangent model

Abstract In this paper, we present a physically informed neural network (NN) representation of the effective interactions associated with coupled-cluster downfolding models to describe chemical systems and processes. The NN representation not only allows us to evaluate the effective interactions efficiently for various geometrical configurations of chemical systems corresponding to various levels of complexity of the underlying wave functions, but also reveals that the bare and effective interactions are related by a tangent function of some latent variables. We refer to this characterization of the effective interaction as a tangent model. We discuss the connection between this tangent model for the effective interaction with the previously developed theoretical analysis that examines the difference between the bare and effective Hamiltonians in the corresponding active spaces.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Human Error In Complex Systems

Report presents results of research aimed at understanding causes of human error in such complex systems as aircraft, nuclear powerplants, and chemical processing plants. Research considered both slips (errors of action) and mistakes (errors of intention), and influence of workload on them. Results indicated that: humans respond to conditions in which errors expected by attempting to reduce incidence of errors; and adaptation to conditions potent influence on human behavior in discretionary situations.

Morris, Nancy M.↗
DOE OSTI2025

Human in vitro metabolism of an environmental mixture of polycyclic aromatic hydrocarbons (PAH) found at the Portland Harbor Superfund Site

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental contaminants that pose health risks to humans. Toxicity testing approaches of PAHs have evolved from traditional rodent models to New Approach Methodologies (NAMs), such as high-throughput screening in zebrafish, enabling rapid evaluation of chemical hazards. However, translating toxicity findings from laboratory systems to humans remains difficult due to complexity and species-specific differences. Chemical dosimetry modeling offers a quantitative framework to bridge this gap, but its accuracy depends on robust knowledge of PAH metabolism. The objective of this study was to measure human metabolism rates of Supermix-10, the ten most abundant PAHs found at the Portland Harbor Superfund Site, to support development of human pharmacokinetic models. We incubated individual PAHs from Supermix-10 in pooled human liver microsomes and quantified parent PAH disappearance using high-performance liquid chromatography (HPLC) with UV and florescent detection. To assess the potential of mixture interactions, we also measured metabolism of all 10 compounds in an equimolar mixture and compared rates of parent disappearance to those observed for individual PAHs. All Supermix-10 PAHs demonstrated rapid parent compound disappearance in human hepatic microsomes. PAHs grouped into three metabolism patterns: high metabolism rates and capacity (2-methylnaphthalene, acenaphthylene, fluorene, naphthalene), high affinity metabolism that rapidly achieves low-level saturation (benzo[a]anthracene, chrysene), and moderate metabolism rates and capacity (fluoranthene, pyrene, retene, phenanthrene). Smaller PAHs exhibited faster metabolism, and higher metabolism rates correlated inversely with molecular weight. When incubated in an equimolar mixture, Supermix-10 demonstrated significantly slower metabolism (47–89 %) compared to metabolism of individual PAHs at the same concentration. These findings enhance our understanding of PAH metabolism in humans and demonstrate significant mixture interactions under the conditions tested. Furthermore, our findings offer insights into the metabolic behavior of Supermix-10 and provide critical metabolism rate data to support the development of physiological based pharmacokinetic (PBPK) models. Dosimetry models can translate PAH chemical dosimetry from high-throughput testing platforms, like zebrafish and cellular system assays, to human exposures enhancing the accuracy and reliability of PAH risk assessments.

2-methylnaphthalene↗
DOE OSTI2022

Foundational Science to Accelerate Nuclear Energy Innovation [Brochure]

The foundational science gaps inhibiting the advancement of nuclear energy technologies are identified and tackled in five priority research opportunities. These opportunities pave the way to accelerate the development and ultimately the adoption of new nuclear energy systems. They include the fundamental aspects of ion-electron interactions; novel properties of next-generation coolants and solvents; interfacial dynamics, not only in solids, but in other aspects of nuclear reactors; novel operando and in-situ monitoring and sensing; and artificial intelligence to accelerate condensed phases discovery. Building on the foundation established by previous BES workshops, these opportunities encompass recent advances in fundamental knowledge and focus on the experimental and computational methods needed to resolve major technical challenges for nuclear energy technologies. Through developing fundamental scientific insight as well as pushing the frontiers of modeling complex systems and probing the operation of materials and chemical systems in extreme environments, research motivated by the priorities identified here will further develop the promise, potential, and utilization of nuclear energy for a clean energy future. The PROs are as follows: (1) Master complex electronic structures to tailor thermochemical reactivity, transport, and microstructural evolution; (2) Interrogate and direct the physics and chemistry underpinning next-generation coolants and solvents; (3) Elucidate and control the underlying physics and chemistry of interfaces in complex nuclear environments; (4) Bridge multi-fidelity multi-resolution experiments, computational modeling, and data science to control dynamic behavior; and (5) Harness artificial intelligence to design inherently resilient condensed phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Reveal of Uranium Bioremediation Mechanisms by Bacillus Species through Proteomics Studies

Radionuclides, such as Uranium (U) and heavy metals continue to pose threats to the ecosystem health and processes at the Department of Energy (DOE) managed, Savannah River Site (SRS), located along the Savannah River near Aiken, SC. Such co-contaminated environments are difficult to remediate using conventional excavation and disposal or pump-and-treat approaches. Globally, more than 109 tons of uranium contaminated areas pose a long term threat to human and ecological health. Even with presented low concentrations in the brain, central nervous effects are still observed. Uranium and depleted uranium (DU) have long term effects on the kidneys. Some small general health effects include severe headaches and breathing problems. Uranus ions are toxic to living cells because they inhibit metabolism of carbohydrates by blocking ATP binding sites. Bioremediation by microorganisms represents an alternative solution, which is advantageous because of the possibility of biosorbent regeneration, cost-effectiveness, increased metal removal and easy recovery of some valuable metals. Bacillus sp. bacterium was previously used in the bioremediation of heavy metals in coal mine run off waters of SRS. However, its ability to bioremediate uranium was unknown so far. Hence, in the present study, uranium bioremediation by Bacillus sp. bacterium was investigated. The mechanism of bioremediation was also revealed through proteomics studies. Heavy metals contamination poses a serious threat to water, soil and human health. Soil and water are contaminated due to excessive exploitation of uranium mines for generation of nuclear energy and weaponry. It is not degradable easily and persist in soil and water for a long period of time due to its long half- life. Savannah river site (SRS) is one of the uranium contaminated sites. The physical or chemical remediation techniques are costly and complex. Microbial system approaches with competent bacteria has received increased attention due to its adaptability in various environmental matrices and cost effectiveness. However, even though there are multiple suggested pathways (F1), the specific mechanisms that drive this behavior are still unclear, especially with popular microorganisms such as Bacillus species. In a previous research (Ibeanusi et al, 2003) Bacillus sp. was shown to detoxify and precipitate a variety of heavy metals in coal pile runoff waters of SRS site. Additionally, genomic analysis demonstrated that this microorganism posses multiple attributes for chemical transport regulation and metabolic pathways. U remediation occurs during the first 20 hours of exposure. During this time period, Bacillus sp. may work primarily under two mechanisms - sorption and accumulation. These two mechanisms simultaneously work to protect the microorganism from high concentrations. Figure 10 demonstrates that certain proteins are up regulated and down regulated under extreme stressful conditions. Membrane fraction proteins were up regulated. Cytosolic fraction proteins were down regulated. This protein information coincides with the adsorption behavior. Bacillus sp. is a good candidate for U remediation at various concentrations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Extended molecular eigenmodes treatment of dipole–dipole NMR relaxation in real fluids

Traditional models of NMR relaxation fail to account for the complex, multi-exponential behavior of the autocorrelation function in realistic systems characterized by soft-interactions and molecules that are chemically and physically complex. Here, in this study, we describe the relative diffusion of the spin dipoles by means of a Fokker–Planck equation that includes an interaction potential of mean force to account for the response of the physical/chemical environment around the dipoles. By numerically solving the Fokker–Planck equation for the diffusion propagator, we estimate dipole–dipole NMR relaxation for like- and unlike-spin systems via its eigenmode solution. We test the model against molecular simulations of diffusing dipoles with harmonic potentials and also validate using experimental longitudinal relaxation data from real systems, including Gd(III)–aqua and Gd(III)–DO3A–butrol complexes, the latter being an important MRI contrast agent. Using this novel approach, we predict both the inner- and outer-shell contributions to the relaxivity rates with excellent accuracy at frequencies relevant to MRI. We also show that, under the appropriate assumptions, our framework naturally recovers the Bloembergen–Purcell–Pound, the Solomon–Bloembergen–Morgan, and the Hwang–Freed models. Our implementation is general and publicly available for application to a broad range of systems.

Pinheiro dos Santos, Thiago J. [Rice Univ., Housto↗
DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗
DOE OSTI2020

Electron Transfer Reactions at the Nexus of Water, Minerals, and Contaminant Metals

The chemistry of natural aquatic systems is fundamentally based on electron transfer reactions. This includes inorganic, organic, and biologic processes, which in the natural environment couple together in complex ways to set the prevailing chemical characteristics of the system. At the molecular scale, electron transfer entails a redistribution of charge between reactants during mutual encounter, a redistri - bution that often breaks or makes new chemical bonds and imparts new properties to the products. These new properties can come in the form of dramatic changes, such as transforming a chemical species from toxic to benign, or from mostly watersoluble to insoluble, leading to nearly instantaneous precipitation of solids.

Rosso, Kevin M.↗
NASA NTRS1962

Empire. a study of early manned interplanetary missions final report, may 26 - nov. 25, 1962

This report summarizes the investigations and results of the EMPIRE Study Program undertaken by Aeronutronic Division of Ford Motor Company for the Future Projects Office, Marshall Space Flight Center, under Contract NAS8-5025. The dual planet flyby missions of the Crocco and Symmetric trajectory classes are discussed. The Crocco mission with an August 1971 launch window requires an interplanetary injection velocity increment of i0.i km/sec, has a return velocity of 13.5 km/sec, and takes approximately 400 days. The Symmetric mission with a July 1970 launch window has an injection velocity increment of 5.3 km/sec, a return velocity of 15.8 km/sec, and takes approximately 630 days. Additional results of the trajectory studies and abort trajectories are reported. The guidance and navigation subsystem, midcourse corrections, and planetary approach corrections are discussed. A detailed analysis of the reentry phase of EMPIRE includes consideration of an Apollo-type, a Drag Brake, and a lifting-type reentry vehicle to return the six-man crew at mission completion or in an aborted condition. The High L/D reentry vehicle is used in the missions considered. The various technological areas required for design criteria are developed and several spacecraft designs are considered. The all chemical propulsion Crocco system is discarded due to weight, complexity, and cost. The nuclear injected Crocco is treated in a similar manner. The lower energy injection for the Symmetric Mission leads to the feasibility of a nuclear injected vehicle with an Earth orbit weight of about 180,000 kilograms (400,000 pounds) before interplanetary transit. In addition, two chemical symmetric vehicles are treated. Conservative radiation exposures are derived, for the 630 day mission, of less than 200 REM and a polyethelene radiation shelter is designed. Scientific aspects of the missions are discussed. Mission Success Probabilities are presented for the various missions considered and for Saturn C-5, Nova, and Super-Nova Earth launch vehicles in light of possible development. The need for acceleration of nuclear rocket engine developments and auxiliary power developments is indicated. Definition of a larger nuclear engine of the order of 200,000 pounds thrust and about 800 seconds burning time or 50,000 pound thrust and 3600 seconds burning time is indicated for the Symmetric Mission in 1970 (energy requirements are higher in 1972 and for later launch due to the less favorable position of Mars)_ Immediate development of this advanced nuclear propulsion capability is recommended. A Development Plan and Funding Schedule is given for the 1970 launch window pinpointing the critical development areas and indicating a total program cost of $12.6 billion independent of other programmed R&D costs. In conclusion, technological feasibility for an early manned dual planet Mars-Venus flyby is believed to be demonstrated in this study. Several areas of accelerated development and experimental confirmation of theory are pinpointed. The necessary funding and development of Nova or orbital operations capability with Saturn C-5's is required. The 1970 launch window appears to offer the least expensive Symmetric Mission for several years into the 1980's.

F. P. Dixon↗
DOE OSTI2023

Perspectives on novel refractory amorphous high-entropy alloys in extreme environments

Two new refractory amorphous high-entropy alloys (RAHEAs) within the W–Ta–Cr–V and W–Ta–Cr–V–Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using in situ Transmission Electron Microscopy. While the 14W-41Ta-26Cr-19V in at.% RAHEA (defined as WTaCrV RAHEA) was found to be unstable under such tests, additions of Hf in this system composing a new quinary 24W-40Ta-18Cr-5V-13Hf in at.% RAHEA (defined as WTaCrVHf RAHEA) was found to be a route to achieve stability both under annealing and irradiation. A new effect of nanoprecipitate reassembling observed to take place within the WTaCrVHf RAHEA under irradiation indicates that a duplex microstructure composed of an amorphous matrix with crystalline nanometer-sized precipitates enhances the radiation response of the system. Further, it is demonstrated that tunable chemical complexity arises as a new alloy design strategy to foster the use of novel RAHEAs within extreme environments. New perspectives for the alloy design and application of chemically-complex amorphous metallic alloys in extreme environments are presented with focus on their thermodynamic phase stability when subjected to high-temperature annealing and displacing irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A DFT-based kinetic Monte Carlo simulation of multiphase oxide-metal thin film growth

Functional thin films of nanoscale metal pillars in oxide or nitride matrices known as vertically aligned nanocomposite (VAN) have gained much interest owing to their unique strain-coupled and highly anisotropic properties. So far, the deposition of these films has been explored mostly experimentally. In this work, a density functional theory (DFT)-based kinetic Monte Carlo simulation model using Bortz–Kalos–Lebowitz algorithm was developed to understand the growth of VAN films deposited by pulsed laser technique on mismatching substrates. The model has been parameterized and applied to understand the kinetics of growth thin films consisting of Au pillars in CeO2 matrix deposited on SrTiO3 substrates. The effects of pulsed laser deposition (PLD) conditions including the pulse frequency, deposition flux, and substrate temperature were explored. The simulations indicate that the Au pillar size and shape exhibit significant dependence on the PLD conditions. Namely, increasing the temperature increases the average pillar size and lowers the pillar density, and vice versa. In addition, the simulations revealed that increasing the deposition rate results in lowering the average pillar size and increasing the density. Particularly, the DFT results suggest that Au pillar size can be tuned during the initial growth of the first monolayer due to the significantly low activation barrier. Our analysis showed that the relationship between the average pillar size and pillar density is influenced by the kinetics. Furthermore, autocorrelation analysis showed that pillars self-organize in quasi-ordered patterns at certain windows of the deposition conditions, which is attributed to the complex nature of the chemical interactions in the system, the kinetics, and the deposition parameters.

Physics↗
NASA NTRS1992

A carbonate-silicate aqueous geochemical cycle model for Mars

A model for the carbonate-silicate geochemical cycle of an early, wet Mars is under development. The results of this study will be used to constrain models of the geochemical history of Mars and the likely mineralogy of its present surface. Although Mars today is a cold, dry planet, it may once have been much warmer and wetter. Values of total outgassed CO2 from several to about 10 bars are consistent with present knowledge (Pollack et al. 1987), and this amount of CO2 implies an amount of water outgassed at least equal to an equivalent depth of 500-1000 meters (Carr 1986). Pollack et al. (1987), in addition, estimate that a thick CO2 atmosphere may have existed for an extended period of time, perhaps as long as a billion years. The greenhouse effect of such an atmosphere would permit the presence of liquid water on the surface, most likely in the form of a shallow sea in the lowest regions of the planet, such as the northern plains (Schaefer 1990). The treatment of geochemical cycles as complex kinetic chemical reactions has been undertaken for terrestrial systems in recent years with much success (Lasaga 1980, 1981; Berner et al. 1983; Lasaga et al. 1985). Although the Martian system is vastly less well understood, and hence less well-constrained, it is also a much simpler system, due to the lack of biogenic reactions that make the terrestrial system so complex. It should be possible, therefore, to use the same techniques to model the Martian system as have been used for terrestrial systems, and to produce useful results. A diagram of the carbonate-silicate cycle for Mars (simplified from the terrestrial system) is given.

Schaefer, M. W.↗