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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Mathematical Model of ATM Activation and Chromatin Relaxation by Ionizing Radiation

We propose a comprehensive mathematical model to study the dynamics of ionizing radiation induced Ataxia-telangiectasia mutated (ATM) activation that consists of ATM activation through dual mechanisms: the initiative activation pathway triggered by the DNA damage-induced local chromatin relaxation and the primary activation pathway consisting of a self-activation loop by interplay with chromatin relaxation. The model is expressed as a series of biochemical reactions, governed by a system of differential equations and analyzed by dynamical systems techniques. Radiation induced double strand breaks (DSBs) cause rapid local chromatin relaxation, which is independent of ATM but initiates ATM activation at damage sites. Key to the model description is how chromatin relaxation follows when active ATM phosphorylates KAP-1, which subsequently spreads throughout the chromatin and induces global chromatin relaxation. Additionally, the model describes how oxidative stress activation of ATM triggers a self-activation loop in which PP2A and ATF2 are released so that ATM can undergo autophosphorylation and acetylation for full activation in relaxed chromatin. In contrast, oxidative stress alone can partially activate ATM because phosphorylated ATM remains as a dimer. The model leads to predictions on ATM mediated responses to DSBs, oxidative stress, or both that can be tested by experiments.

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

Impact of the Cathode Pt Loading on PEMFC Contamination by Several Airborne Contaminants

Proton exchange membrane fuel cells (PEMFCs) with 0.1 and 0.4 mg Pt cm -2 cathode catalyst loadings were separately contaminated with seven organic species: Acetonitrile, acetylene, bromomethane, iso-propanol, methyl methacrylate, naphthalene, and propene. The lower catalyst loading led to larger cell voltage losses at the steady state. Three closely related electrical equivalent circuits were used to fit impedance spectra obtained before, during, and after contamination, which revealed that the cell voltage loss was due to higher kinetic and mass transfer resistances. A significant correlation was not found between the steady-state cell voltage loss and the sum of the kinetic and mass transfer resistance changes. Major increases in research program costs and efforts would be required to find a predictive correlation, which suggests a focus on contamination prevention and recovery measures rather than contamination mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Methodology and analytical approach to investigate the impact of building temperature setpoint schedules

This work presents a method for generating a large set of stochastically varying temperature setpoint schedules for building performance simulations. It analyses tradeoffs resulting from specific changes to those schedules in terms of three quantities: total electricity consumption per day; maximum hourly electricity consumption per day and predicted percentage dissatisfied (occupant thermal comfort). The method for generating schedules requires a single base schedule as the starting point and, using a few clearly defined parameters, transforms it into a set of schedules that can be used for modelling an existing building stock or for performing parametric studies. Temperature setpoint schedules are generated and simulated for a small office building in a cool-dry climate in three different case studies pertaining to changing temperature setpoint schedules. Tradeoffs between the three output metrics are significant and vary based on the temperature setpoint schedules and the time of the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flux-driven algebraic damping of m = 2 diocotron mode

Experiments with pure electron plasmas in a Malmberg–Penning trap have observed linear in time, algebraic damping of m = 2 diocotron modes. Transport due to small field asymmetries produces a low-density halo of electrons moving radially outward from the plasma core, and the mode damping begins when the halo reaches the resonant radius of the mode. The damping rate is proportional to the flux of halo particles through the resonant layer. The damping is related to, but distinct from spatial Landau damping in which a linear wave–particle resonance produces exponential damping. This paper reports an analytic theory that captures the main signatures reported for this novel damping, namely, that the damping begins when the halo particles reach the resonant radius and that the damping is algebraic in time with nearly constant damping rate. The model also predicts a nonlinear frequency shift. The model provides two ways to think about the damping. It results from a transfer of canonical angular momentum from the mode to halo particles being swept by the mode field through the nonlinear cat's eye orbits of the resonant region. More mechanistically, the electric field produced by the perturbed charge density of the resonant particles acts back on the plasma core causing E × B drift that gives rise to the damping and nonlinear frequency shift.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quasisteady evolution of fast neutrino-flavor conversions

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions’ effects in the theoretical modeling of CCSN and BNSM. Some phenomenological schemes have shown good performance in approximating asymptotic states of fast neutrino-flavor conversions (FFCs), known as one of the collective neutrino oscillation modes induced by neutrino self-interactions. However, a recent study showed that they would yield qualitatively different asymptotic states of FFC if the neutrino number is forced to evolve. It is not yet fully understood why the canonical phenomenological models fail to predict asymptotic states. In this paper, we perform detailed investigations through numerical simulations and then provide an intuitive explanation with a quasihomogeneous analysis. Based on the analysis, we propose a new phenomenological model, in which the quasisteady evolution of FFCs is analytically determined. The model also allows us to express the convolution term of spatial wave number as a concise form, which corresponds to useful information on analyses for the nonlinear feedback from small-scale flavor conversions to large-scale ones. Furthermore, our model yields excellent agreement with numerical simulations, which lends support to our interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Reimagining the $e_g$ 1 Electronic State in Oxygen Evolution Catalysis: Oxidation-State-Modulated Superlattices as a New Type of Heterostructure for Maximizing Catalysis

We report that the discovery of solid-phase, inexpensive transition-metal-based water oxidation catalysts is a central goal for renewable energy, and has led to a general consensus that a partially populated metal e g d-electronic state is desirable, leading to favorable catalysis for certain elements in specific oxidation states. In manganese systems, the key species is manganese(III), whose high-spin d 4 electronic configuration places an unpaired electron in the e g orbital, which is postulated to contribute to electronic and structural features that support catalysis. Based on density functional theory calculations, it is predicted that electron transfer would be facilitated by a catalyst with alternating low- and high-Mn III -content sheets, which positions neighboring band edges in closer energetic proximity. The preparation of such catalysts is demonstrated for the first time and it is shown that the catalytic activity is maximized in these systems over more uniform, but more Mn III -rich systems. The best catalyst possesses alternating high-and low-average oxidation state sheets with interlayer Cs + ions, and has an overpotential of 450 mV at 10 mA, which represents an improvement of 250 mV over the best unmodified synthetic potassium birnessites. Using scanning tunneling spectroscopy, bandgap modulations consistent with the theoretically predicted band edge shifts are detected.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Plasma‐catalytic synthesis of acrylonitrile from methane and nitrogen

Here, in this work, we demonstrate plasma-catalytic synthesis of hydrogen and acrylonitrile (AN) from CH 4 and N 2 . The process involves two steps: (1) plasma synthesis of C 2 H 2 and HCN in a nominally 1:1 stoichiometric ratio with high yield up to 90% and (2) downstream thermocatalytic reaction of these intermediates to make AN. The effect of process parameters on product distributions and specific energy requirements are reported. If the catalytic conversion of C 2 H 2 and HCN in the downstream thermocatalytic step to AN were perfect, which will require further improvements in the thermocatalytic reactor, then at the maximum output of our 1 kW radiofrequency 13.56 MHz transformer, a specific energy requirement of 73 kWh kg AN −1 was determined. The expectation is that scaling up the process to higher throughputs would result in decreases in specific energy requirement into the predicted economically viable range less than 10 kWh kg AN −1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Kinetic isotope effects for dissociative recombination of tritiated ketenyl ion ( 3 HCCO + ): A surface-hopping ab initio molecular dynamics study

Dissociative recombination (DR) reactions are important when modeling charged species in the presence of free electrons. While experimental measurements of DR reaction rates are challenging, surface hopping ab initio molecular dynamics (SH-AIMD) simulations provide an attractive alternative. SH-AIMD is especially well-suited for estimating branching ratios, i.e., the relative rates of competing production channels, for DR reactions. Although the radiolysis of diatomic tritium has been studied experimentally, previous attempts to model these systems have failed to account for isotope effects in DR reactions. Previous SH-AIMD studies have also not investigated tritium isotope effects for the branching ratios of DR reactions. In this study, we compute the DR branching ratios of the protiated and tritiated ketenyl ion. Comparison with literature values for the protiated branching ratios provides confidence in the reliability of our SH-AIMD results. Our simulations predict a significant increase of the HC + CO branching ratio for the tritiated system.

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

A buoyancy–shear–drag–scalar-based turbulence model for power-law acceleration-driven Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing

A previously developed phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing based on a general buoyancy–shear–drag model [O. Schilling, “A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing,” Physica D 402, 132238 (2020)] is extended to include active or passive scalar mixing and power-law acceleration-driven Rayleigh–Taylor mixing. The buoyancy–shear–drag equations are coupled to a scalar variance equation that is used to define the molecular mixing parameter θ m , and when the scalar is active, modifies the Rayleigh–Taylor and Kelvin–Helmholtz mixing layer growth parameters to depend on the asymptotic value of this parameter, θ mol . Here, the scalar variance equation is closed by algebraically or differentially modeling the scalar variance dissipation rate. Nonlinear analytical solutions of the model are obtained in the total and separate bubble and spike mixing layer width formulations with the algebraic scalar variance dissipation rate for each instability, which are then used to calibrate the mechanical and scalar equation coefficients to predict specific values of physical observables and molecular mixing parameters. Surrogate mechanical and scalar turbulent fields can be constructed by multiplying a presumed self-similar spatial profile by appropriate functions of the width and its time derivative, and of the scalar obtained by solving the ordinary differential model equations. The explicit modeling and solution of turbulent transport equations are not required. The bubble and spike mixing layer width and scalar variance equations are then solved numerically for constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing, confirming that the prescribed level of molecular mixing is correctly predicted and illustrating the spatiotemporal evolution of the scalar fields.

Buoyancy–drag↗
DOE OSTI2022

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

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

A Comparative Study of Electrical Double Layer Effects for CO Reduction Reaction Kinetics

Solvation models describe how the interactions between the solutes and solvents affect the reactivity and selectivity in electrochemical processes. In this study, we developed a framework for evaluating the effects of applied potential and electrical double layer on CO reduction (COR), comparing fully explicit, implicit, and hybrid solvation models at the standard hydrogen electrode (SHE) scale. We analyzed all crucial intermediates leading to the production of C 1 and C 2 products and found good agreement across these models. Some notable differences were observed in the implicit description of *C and *CO adsorption at higher overpotentials and overall trends in the adsorption energies within the hybrid model. Using this unified SHE framework, we built comparable microkinetic models for COR kinetics and rates. Despite small differences in thermodynamics, solvation-model-based microkinetic simulations showed good agreement for onset potentials against the benchmark experiment. Only qualitative difference was observed for C 1+ versus hydrogen evolution at high overpotentials for the implicit model. Finally, we constructed a generalized C 2 selectivity map in descriptor space (U SHE , ΔG electrolyte CO ), which highlights the limitations of a copper-based COR catalyst and guides the search for optimal descriptor parameters to maximize C 2 selectivity. In conclusion, these findings demonstrate the importance of considering electrical double layer effects in reduction reactions and offer a useful framework for comparing solvation models and predicting optimal electrochemical conditions for specific applications.

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

Toward Engineering of Solution Microenvironments for the CO 2 Reduction Reaction: Unraveling pH and Voltage Effects from a Combined Density-Functional–Continuum Theory

Engineering the electrolyte microenvironment represents an attractive route to tuning the selectivity of electrocatalytic reactions beyond catalyst composition and morphology. However, harnessing the full potential of this approach requires understanding the interplay between voltage, electrolyte composition, and adsorbate binding within the electrical double layer, which is absent from the usual theoretical approaches. In this study, we apply a recently developed density functional theory (DFT)–continuum approach based on the effective screening medium method and reference interaction site model (ESM–RISM) to explore electrolyte effects with an enhanced description of the electrochemical interface. Furthermore, applying this method to the binding of CO adsorbates in potassium-containing electrolytes on copper, a problem of direct relevance to CO 2 electroreduction to value-added products, we show that the interdependence of voltage and pH leads to an unexpected change in adsorption site preference on Cu(001) terraces. Our findings highlight the often-overlooked importance of the electrical double-layer structure for predicting catalyst operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Colloidal Stability of PFSA-Ionomer Dispersions. Part I. Single-Ion Electrostatic Interaction Potential Energies

Charged colloidal particles neutralized by a single counterion are increasingly important for many emerging technologies. Attention here is paid specifically to hydrogen fuel cells and water electrolyzers whose catalyst layers are manufactured from a perfluorinated sulfonic acid polymer (PFSA) suspended in aqueous/alcohol solutions. Partially dissolved PFSA aggregates, known collectively as ionomers, are stabilized by the electrostatic repulsion of overlapping diffuse double layers consisting of only protons dissociated from the suspended polymer. We denote such double layers containing no added electrolyte as "single ion". Size-distribution predictions build upon interparticle interaction potential energies from the Derjaguin-Landau-Verwey-Overbeek (DLVO) formalism. However, when only a single counterion is present in solution, classical DLVO electrostatic potential energies no longer apply. Accordingly, here a new formulation is proposed to describe how single-counterion diffuse double layers interact in colloidal suspensions. Part II (Srivastav, H.; Weber, A. Z.; Radke, C. J. Langmuir 2024 DOI: 10.1021/acs.langmuir.3c03904) of this contribution uses the new single-ion interaction energies to predict aggregated size distributions and the resulting solution pH of PFSA in mixtures of n-propanol and water. A single-counterion diffuse layer cannot reach an electrically neutral concentration far from a charged particle. Consequently, nowhere in the dispersion is the solvent neutral, and the diffuse layer emanating from one particle always experiences the presence of other particles (or walls). Thus, in addition to an intervening interparticle repulsive force, a backside osmotic force is always present. With this new construction, we establish that single-ion repulsive pair interaction energies are much larger than those of classical DLVO electrostatic potentials. The proposed single-ion electrostatic pair potential governs dramatic new dispersion behavior, including dispersions that are stable at a low volume fraction but unstable at a high volume fraction and finite volume-fraction dispersions that are unstable with fine particles but stable with coarse particles. Finally, the proposed single-counterion electrostatic pair potential provides a general expression for predicting colloidal behavior for any charged particle dispersion in ionizing solvents with no added electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The Interplay of Solvation and Polarization Effects on Ion Pairing in Nanoconfined Electrolytes

The nature of ion–ion interactions in electrolytes confined to nanoscale pores has important implications for energy storage and separation technologies. However, the physical effects dictating the structure of nanoconfined electrolytes remain debated. Here we employ machine-learning-based molecular dynamics simulations to investigate ion–ion interactions with density functional theory level accuracy in a prototypical confined electrolyte, aqueous NaCl within graphene slit pores. We find that the free energy of ion pairing in highly confined electrolytes deviates substantially from that in bulk solutions, observing a decrease in contact ion pairing but an increase in solvent-separated ion pairing. These changes arise from an interplay of ion solvation effects and graphene’s electronic structure. Notably, the behavior observed from our first-principles-level simulations is not reproduced even qualitatively with the classical force fields conventionally used to model these systems. The insight provided in this work opens new avenues for predicting and controlling the structure of nanoconfined electrolytes.

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

In Situ Oxidation Studies of High-Entropy Alloy Nanoparticles

Although high-entropy alloys (HEAs) have shown tremendous potential for elevated temperature, anticorrosion, and catalysis applications, little is known on how HEA materials behave under complex service environments. Herein, we studied the high-temperature oxidation behavior of Fe 0.28 Co 0.21 Ni 0.20 Cu 0.08 Pt 0.23 HEA nanoparticles (NPs) in an atmospheric pressure dry air environment by in situ gas-cell transmission electron microscopy. It is found that the oxidation of HEA NPs is governed by Kirkendall effects with logarithmic oxidation rates rather than parabolic as predicted by Wagner's theory. Further, the HEA NPs are found to oxidize at a significantly slower rate compared to monometallic NPs. The outward diffusion of transition metals and formation of disordered oxide layer are observed in real time and confirmed through analytical energy dispersive spectroscopy, and electron energy loss spectroscopy characterizations. Localized ordered lattices are identified in the oxide, suggesting the formation of Fe 2 O 3 , CoO, NiO, and CuO crystallites in an overall disordered matrix. Hybrid Monte Carlo and molecular dynamics simulations based on first-principles energies and forces support these findings and show that the oxidation drives surface segregation of Fe, Co, Ni, and Cu, while Pt stays in the core region. The present work offers key insights into how HEA NPs behave under high-temperature oxidizing environment and sheds light on future design of highly stable alloys under complex service conditions.

36 MATERIALS SCIENCE↗