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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 1,603 records · Page 89

Data-driven optimized control of the COVID-19 epidemics

Optimizing the impact on the economy of control strategies aiming at containing the spread of COVID-19 is a critical challenge. We use daily new case counts of COVID-19 patients reported by local health administrations from different Metropolitan Statistical Areas (MSAs) within the US to parametrize a model that well describes the propagation of the disease in each area. We then introduce a time-varying control input that represents the level of social distancing imposed on the population of a given area and solve an optimal control problem with the goal of minimizing the impact of social distancing on the economy in the presence of relevant constraints, such as a desired level of suppression for the epidemics at a terminal time. We find that with the exception of the initial time and of the final time, the optimal control input is well approximated by a constant, specific to each area, which contrasts with the implemented system of reopening ‘in phases’. For all the areas considered, this optimal level corresponds to stricter social distancing than the level estimated from data. Proper selection of the time period for application of the control action optimally is important: depending on the particular MSA this period should be either short or long or intermediate. We also consider the case that the transmissibility increases in time (due e.g. to increasingly colder weather), for which we find that the optimal control solution yields progressively stricter measures of social distancing. We finally compute the optimal control solution for a model modified to incorporate the effects of vaccinations on the population and we see that depending on a number of factors, social distancing measures could be optimally reduced during the period over which vaccines are administered to the population.

60 APPLIED LIFE SCIENCES↗

Coulombically-stabilized oxygen hole polarons enable fully reversible oxygen redox

Stabilizing high-valent redox couples and exotic electronic states necessitates an understanding of the stabilization mechanism. In oxides, whether they are being considered for energy storage or computing, highly oxidized oxide-anion species rehybridize to form short covalent bonds and are related to significant local structural distortions. In intercalation oxide electrodes for batteries, while such reorganization partially stabilizes oxygen redox, it also gives rise to substantial hysteresis. In this work, we investigate oxygen redox in layered Na 2-x Mn 3 O 7 , a positive electrode material with ordered Mn vacancies. We prove that coulombic interactions between oxidized oxide-anions and the interlayer Na vacancies can disfavor rehybridization and stabilize hole polarons on oxygen (O-) at 4.2 V vs. Na/Na + . These coulombic interactions provide thermodynamic energy saving as large as O–O covalent bonding and enable ~40 mV voltage hysteresis over multiple electrochemical cycles with negligible voltage fade. As such, our results establish a complete picture of redox energetics by highlighting the role of coulombic interactions across several atomic distances and suggest avenues to stabilize highly oxidized oxygen for applications in energy storage and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-principles molten salt phase diagrams through thermodynamic integration

Precise prediction of phase diagrams in molecular dynamics simulations is challenging due to the simultaneous need for long time and large length scales and accurate interatomic potentials. Here, we show that thermodynamic integration from low-cost force fields to neural network potentials trained using density-functional theory (DFT) enables rapid first-principles prediction of the solid–liquid phase boundary in the model salt NaCl. We use this technique to compare the accuracy of several DFT exchange–correlation functionals for predicting the NaCl phase boundary and find that the inclusion of dispersion interactions is critical to obtain good agreement with experiment. Importantly, our approach introduces a method to predict solid–liquid phase boundaries for any material at an ab initio level of accuracy, with the majority of the computational cost at the level of classical potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational techniques for design optimization of thermal protection systems for the space shuttle vehicle. Volume 1: Final report

Computational techniques were developed and assimilated for the design optimization. The resulting computer program was then used to perform initial optimization and sensitivity studies on a typical thermal protection system (TPS) to demonstrate its application to the space shuttle TPS design. The program was developed in Fortran IV for the CDC 6400 but was subsequently converted to the Fortran V language to be used on the Univac 1108. The program allows for improvement and update of the performance prediction techniques. The program logic involves subroutines which handle the following basic functions: (1) a driver which calls for input, output, and communication between program and user and between the subroutines themselves; (2) thermodynamic analysis; (3) thermal stress analysis; (4) acoustic fatigue analysis; and (5) weights/cost analysis. In addition, a system total cost is predicted based on system weight and historical cost data of similar systems. Two basic types of input are provided, both of which are based on trajectory data. These are vehicle attitude (altitude, velocity, and angles of attack and sideslip), for external heat and pressure loads calculation, and heating rates and pressure loads as a function of time.

Source record↗

RE-1000 free-piston Stirling engine hydraulic output system description

The NASA Lewis Research Center was involved in free-piston Stirling engine research since 1976. Most of the work performed in-house was related to characterization of the RE-1000 engine. The data collected from the RE-1000 tests were intended to provide a data base for the validation of Stirling cycle simulations. The RE-1000 was originally build with a dashpot load system which did not convert the output of the engine into useful power, but was merely used as a load for the engine to work against during testing. As part of the interagency program between NASA Lewis and the Oak Ridge National Laboratory, (ORNL), the RE-1000 was converted into a configuration that produces useable hydraulic power. A goal of the hydraulic output conversion effort was to retain the same thermodynamic cycle that existed with the dashpot loaded engine. It was required that the design must provide a hermetic seal between the hydraulic fluid and the working gas of the engine. The design was completed and the hardware was fabricated. The RE-1000 was modified in 1985 to the hydraulic output configuration. The early part of the RE-1000 hydraulic output program consisted of modifying hardware and software to allow the engine to run at steady-state conditions. A complete description of the engine is presented in sufficient detail so that the device can be simulated on a computer. Tables are presented showing the masses of the oscillating components and key dimensions needed for modeling purposes. Graphs are used to indicate the spring rate of the diaphragms used to separate the helium of the working and bounce space from the hydraulic fluid.

Schreiber, Jeffrey G.↗

Features of Afterbody Radiative Heating for Jupiter Entry

In this extended abstract, a preliminary analysis of a trajectory-based heating and ablation study in the afterbody of a Jovian entry probe is presented. The radiative flux in the afterbody impinging on the backshell of the probe is investigated with and without the presence of ablation product gas. The heritage tangent-slab approximation for radiative heating is shown to underpredict the radiative heating by as much as 50% in the afterbody making the highfidelity, yet computationally expensive, ray-tracing approach necessary to accurately predict the radiative heating predictions. An investigation into the merits of employing the ray-tracing approach for the prediction of the divergence of radiative flux in the afterbody flow field will be presented in the final manuscript. Nonequilibrium effects in the afterbody region will be investigated in the final manuscript including the impact of electron-ion recombination rates. To bound the problem based on the best available knowledge, an uncertainty analysis will be performed. Sources of uncertainty are identified in the ablation modeling, radiation modeling, flowfield kinetics, and thermodynamic properties of select species.

Thermophysics↗

Effects of charged interfaces on electrolyte decomposition at the lithium metal anode

Lithium–Sulfur batteries are promising candidates to substitute conventional Li-ion batteries due to their higher energy density and reduced cost. However, several challenges related to the reactivity of the lithium metal anode have prevented this technology from becoming broadly commercialized. Lithium's high reactive nature leads to the continuous decomposition of the electrolyte and the formation of the solid-electrolyte interphase (SEI) layer. Thus, a comprehensive understanding of how the SEI film is formed is crucial to help elucidate improvements for this battery technology. In this work, we use density functional theory (DFT) based computational methods to investigate the effect of charged interfaces on the electrolyte degradation at the lithium anode. Here, several electrolyte mixtures were considered including 1,2-dimethoxyethane (DME) and 1,3-dioxolane (DOL) as solvents, and lithium bis(fluorosulfonyl)imide (LiFSI) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) as salts. It is found that the extent of salt decomposition is higher when the interface is charged. In addition, two types of solvent reduction mechanisms are identified: C–O bond cleavage and radical attacks. Charge transfer and evolution analysis are characterized in detail. Finally, solvent decomposition reactions are found to become more thermodynamically favorable and their activation barriers to be diminished under the effect of constant potentials and electric fields.

25 ENERGY STORAGE↗

Toward more environmentally resistant gas turbines - Progress in NASA-Lewis programs

The paper surveys programs for improving the environmental resistance of gas turbine and power system materials to oxidation and hot corrosion. A computer program Corest has been produced which provides an initial method for predicting long-time metal loss using short-time oxidation data. The role of the coefficient of thermal expansion mismatch on oxide spallation is being studied. A paralinear oxidation attack model in conjunction with regression analysis of weight change data has been applied to the study of oxidation and hot corrosion attack of some Ni-Cr-Al system alloys. Oxide-dispersion strengthened alloys based on the Ni-Cr-Al system are being developed. Sodium sulfate formation during turbine combustion is being investigated from a thermodynamic viewpoint.

Lowell, C. E.↗

The Relationships Between the Trends of Mean and Extreme Precipitation

This study provides a better understanding of the relationships between the trends of mean and extreme precipitation in two observed precipitation data sets: the Climate Prediction Center Unified daily precipitation data set and the Global Precipitation Climatology Program (GPCP) pentad data set. The study employs three kinds of definitions of extreme precipitation: (1) percentile, (2) standard deviation and (3) generalize extreme value (GEV) distribution analysis for extreme events based on local statistics. Relationship between trends in the mean and extreme precipitation is identified with a novel metric, i.e. area aggregated matching ratio (AAMR) computed on regional and global scales. Generally, more (less) extreme events are likely to occur in regions with a positive (negative) mean trend. The match between the mean and extreme trends deteriorates for increasingly heavy precipitation events. The AAMR is higher in regions with negative mean trends than in regions with positive mean trends, suggesting a higher likelihood of severe dry events, compared with heavy rain events in a warming climate. AAMR is found to be higher in tropics and oceans than in the extratropics and land regions, reflecting a higher degree of randomness and more important dynamical rather than thermodynamical contributions of extreme events in the latter regions.

global warming↗

Computationally Guided Discovery of Axis-Dependent Conduction Polarity in NaSnAs Crystals

Most electronic materials exhibit a single dominant charge carrier type, either holes or electrons, along all crystallographic directions. However, there are a small number of compounds, mostly metals, that exhibit simultaneous p-type and n-type conduction behavior along different crystallographic directions. We demonstrate that the experimental discovery of semiconductors with this axis-dependent conduction polarity can be facilitated by identifying a large anisotropy of either the electron or hole effective masses (m*) or both, providing the electron and hole masses dominate along different crystallographic directions. We calculated the layered semiconductor NaSnAs to have a lower electron m* in-plane than the cross-plane and a very large hole m* in-plane and small hole m* cross-plane. We established the growth of >3 mm-sized NaSnAs crystals via Sn flux and confirmed the band gap to be 0.65 eV, in agreement with theory. NaSnAs exhibits p-type thermopowers cross-plane and n-type thermopowers in-plane, confirming that the large anisotropy in the effective mass at the band edges is an excellent indicator for axis-dependent conduction polarity. Altogether, this work shows that the discovery of semiconductors with such a phenomenon can be accelerated by computationally evaluating the anisotropic curvatures of the band edges, paving the way for their future discovery and application.

30 DIRECT ENERGY CONVERSION↗

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R 2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R 2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental and computational kinetics study of the liquid-phase hydrogenation of C=C and C=O bonds

Solvent effects on adsorption equilibrium and reaction kinetics are evaluated for hydrogenation reactions catalyzed by Pd/alumina in a series of different solvents. Three reactants – cyclohexene, benzene and benzaldehyde – and three solvents – n-heptane (HEP), methylcyclohexane (MCHA), decalin (DL) – have been investigated. Kinetic analysis of hydrogenation of cyclohexene reveals that hydrogen adsorbs on different sites from those where cyclohexene and the solvents adsorb; however, the presence of hydrogen on these separate sites affects the heats of adsorption of the hydrocarbons. When the solvent is a weakly interacting linear alkane (HEP), the rate determining step of the reaction is the first hydrogenation of adsorbed cyclohexene. Furthermore, this conclusion is supported by DFT calculations that show a higher enthalpy barrier for the first hydrogenation than for the second, while statistical thermodynamics analysis validates the physical significance of the entropy of adsorption parameters derived from the kinetic fitting of experimental data. By contrast, with solvents such as MCHA and DL, which interact more strongly with the metal surface and compete for active sites with the reactant and the surface intermediate, the rate limiting step seems to shift to the second hydrogenation step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗

Thermodynamically leveraged solventless aerobic deconstruction of polyethylene-terephthalate plastics over a single-site molybdenum-dioxo catalyst

Here, we describe the solventless catalytic deconstruction of polyethylene-terephthalate (PET) under an aerobic atmosphere, mediated by an earth-abundant, low-cost activated carbon (AC)-supported single-site molybdenum-dioxo catalyst (AC/MoO 2 ). Catalytic amounts of AC/MoO 2 selectively convert waste PET into its monomer, terephthalic acid (TPA), within 4 h at 265 °C with yields as high as 94% under 1 atm air. Pure crystalline TPA product sublimes from the reaction hot zone, crystallizing on the reactor cold zone, thus avoiding the need for separation and purification steps. This process does not employ any hazardous/toxic reducing agents or solvents, and the catalyst can be recycled multiple times without loss of activity, rendering this process highly atom-efficient. According to computational and experimental mechanistic studies, the AC/MoO 2 catalyst mediates a thermoneutral metal-catalyzed β-scission step, followed by an exothermic step that converts the vinyl benzoate intermediate to TPA and acetaldehyde using trace amounts of moisture in the air. The formation of gaseous acetaldehyde makes the isolation of TPA from the reaction mixture facile and industrially favorable, especially since solvents are unnecessary. The present methodology is also extended to the deconstruction of other frequently used polyester plastics, polybutylene terephthalate (PBT), polyethylene naphthalate (PEN), and polyethylene furanoate (PEF), and operates equally well with post-consumer waste products. Notably, this process is also compatible with plastic mixtures of polyesters with polyolefins, polyamides, and polycarbonates, leading to the selective conversion of each polyester to the corresponding monomer, leaving the residual polymer unchanged and polyester-free.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational and Experimental Investigation of Thermal-Mechanical- Chemical Mechanisms of High-burnup Spent Nuclear Fuel (SNF) Processes at Elevated Temperatures and Degradation Behavior in Geologic Repositories

The overarching goal of the combined computational and experimental R&D activities proposed in this project is to enhance understanding of the mechanisms and thermal-mechanical-chemical (TMC) parameters controlling the instant release fraction (IRF) and matrix dissolution of high-burnup (HB; burnup) spent nuclear fuels (SNFs) and the subsequent formation, stability, and phase transformations of SNF alteration products under long-term storage and geological disposal conditions. Uranium dioxide may undergo oxidative corrosion/alteration, and the IRF may be increased for HB SNF, both of which may affect environmental systems associated with SNF long-term storage and disposal. The oxidative matrix dissolution may form various complex uranyl-based phases, including a rich variety of oxides, silicates, carbonates and other secondary minerals in varied geological environments (e.g., studtite, metastudtite, amorphous uranyl peroxide, uranium trioxide, triuranium octoxide, schoepite, dehydrated schoepite, metaschoepite, becquerelite, soddyite, rutherfordine,...). These uranyl phases generally have higher mobility UO 2 +2 species than less soluble U 4+ phases. However, limited information on the thermodynamic properties and formation kinetics of these uranyl-bearing phases is available to predict explicitly paragenesis under the conditions relevant to long-term storage or disposal. The proposed project draws on complementary expertise and research backgrounds from the team members: (i) to apply a combined ab initio modeling (UNLV/UTEP and SNL) and experimental (UNLV) strategy investigating the high-temperature TMC mechanisms of alteration of SNF under α-radiolysis conditions; (ii) to investigate the mechanistic of phase transformations in UNF degradation products under various conditions expected in long-term storage systems (e.g. (UO 2 )O 2 (H 2 O) 4 → (UO 2 )O 2 (H 2 O) 2 → U 2 O 7 → UO 3 → U 3 O 8 ); (iii) to determine high-accuracy TMC parameters for complex uranyl-based phases formed in storage or geological disposal environments (e.g. UO 3 (H 2 O) 2 , Ca[(UO 2 ) 6 O 4 (OH) 8 ] 8 H 2 O, (UO 2 ) 2 (SiO 4 ) 3 2H 2 O,…). The unforeseen COVID-19 pandemic led to the laboratory/campus closure since March 2020, that resulted in a significant delay in reaching milestones in a satisfactory manner, due to (i) the statewide recommendation from stop-working to later limited work in the lab and work-from-home (WFH), (ii) no in-person interactions, and (iii) a hiring freeze at UNLV. Therefore, a no cost extension (10/01/2021- 9/30/2022) was requested to help make up the time we lost during the global pandemic in 2020-2021, leading to paradigm shifts in the focus of the project in the following three main tasks: Task 1 (Computational), Task 2 (Experimental), and Task 3 (Final report, due on 12/29/2022).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling in High Temperature Corrosion: A Review and Outlook

Realizing higher operating temperatures to increase efficiency of future applications for energy conversion and storage while minimizing cost is a challenge for development of high-temperature materials. Simultaneous optimization of mechanical properties and corrosion resistance continues to be a difficult task but is essential due to the need to significantly accelerate the transition between technology readiness levels in the future. Furthermore, oxidation-induced degradation will be a critical life-limiting mechanism at increased operating temperatures. Suitable high-temperature materials cannot be solely identified by time-consuming experiments and reliable computational methods incorporating the relevant physics of processes must be considered to complement the experimental efforts. In the present work, a review of the methods employed to model oxidation-induced material degradation described in literature will be discussed. Furthermore, their capability to predict lifetime and aid in material selection will be evaluated.

36 MATERIALS SCIENCE↗

Elucidating plasma dynamics in Hasegawa–Wakatani turbulence by information geometry

In this work, the impact of adiabatic electrons on drift-wave turbulence, modeled by the Hasegawa–Wakatani equations, is studied using information length. Information length is a novel theoretical method for measuring distances between statistical states represented by different probability distribution functions (PDFs) along the path of a system and represents the total number of statistically different states that a system evolves through in time. Specifically, the time-dependent PDFs of turbulent fluctuations for a given adiabatic index $A$ are computed. The changes in fluctuation statistics are then quantified in time by using information length. The numerical results provide time traces exhibiting intermittent plasma dynamics, and such behavior is identified by a rapid change in the information length. The effects of $A$ are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of Charged Solute-Solvent Interaction on Reservoir Temperature during Subsurface CO2 Injection

A short-term side-effect of CO2 injection is a developing low-pH front that forms ahead of the bulk water injectant, due to differences in solute diffusivity. Observations of downhole well temperature show a reduction in aqueous-phase temperature with the arrival of a low-pH front, followed by a gradual rise in temperature upon the arrival of a high concentration of bicarbonate ion. In this work, we model aqueous-phase transient heat advection and diffusion, with the volumetric energy generation rate computed from solute-solvent interaction using the Helgeson–Kirkham–Flowers (HKF) model, which is based on the Born Solvation model, for computing specific molar heat capacity and the enthalpy of charged electrolytes. A computed injectant water temperature profile is shown to agree with the actual bottom hole sampled temperature acquired from sensors. The modeling of aqueous-phase temperature during subsurface injection simulation is important for the accurate modeling of mineral dissolution and precipitation because forward dissolution rates are governed by a temperature-dependent Arrhenius model.

58 GEOSCIENCES↗