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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Surface Dynamics of Selective Hydration of Rutile TiO 2 : A Kinetic Monte Carlo Approach

The utility of atomic layer deposition (ALD) continues to expand beyond conformal thin-film fabrication to include area- or site-selective ALD. We previously identified a strategy for site-selective ALD (SS-ALD) via the evaluation of thermodynamically preferred hydration of rutile TiO 2 surfaces, as deduced from electronic structure calculations. Here, we report a novel kinetic Monte Carlo (KMC) model that allows for the investigation of surface dynamics and kinetics that improves our understanding of and intuition for the selective hydration strategy. Here we demonstrate the validity of the strategy with respect to step-edge defects for the lowest energy (110) facet as well as report results for the other common facets which agree with experimental STM observations. The results here indicate that the selective hydration strategy is feasible both thermodynamically (evaluated in our previous publication) and kinetically (from the KMC model). Because diffusion has a slower rate than others, we find that any proximity effects between terrace and defect sites are unlikely to affect the selective hydration strategy for rutile TiO 2 . The KMC model further provides relevant timescales for achieving selectivity experimentally and establishes the kinetic viability of the selective hydration approach to SS-ALD.

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

Neural network kinetics for exploring diffusion multiplicity and chemical ordering in compositionally complex materials

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Towards understanding the magnetic properties of the breathing pyrochlore compound Ba3Yb2Zn5O11through single-crystal studies

Abstract Ba 3 Yb 2 Zn 5 O 11 is exceptional among breathing pyrochlore compounds for being in the nearly-decoupled limit where inter-tetrahedron interactions are weak, hosting isolated clusters or molecular magnet-like tetrahedra of magnetic ytterbium (Yb 3+ ) ions. In this work, we present the study carried out on single-crystal samples of the breathing pyrochlore Ba 3 Yb 2 Zn 5 O 11 , using a variety of magnetometry and neutron scattering techniques along with theoretical modeling. We employ inelastic neutron scattering to investigate the magnetic dynamics as a function of applied field (with respect to both magnitude and direction) down to a temperature of 70 mK, where inelastic scattering reveals dispersionless bands of excitations as found in earlier powder sample studies, in good agreement with a single-tetrahedron model. However, diffuse neutron scattering at zero field and dc-susceptibility at finite field exhibit features suggesting the presence of excitations at low-energy that are not captured by the single tetrahedron model. Analysis of the local structure down to 2 K via pair distribution function analysis finds no evidence of structural disorder. We conclude that effects beyond the single tetrahedron model are important in describing the low-energy, low-temperature physics of Ba 3 Yb 2 Zn 5 O 11 , but their nature remains undetermined.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Domain Decomposition Model Reduction Method for Linear Convection-Diffusion Equations with Random Coefficients

We developed a domain decomposition model reduction method for linear steady- state convection-diffusion equations with random coefficients. Of particular interest to this effort are the diffusion equation with random diffusivity and the convection-dominated transport equation with random velocity. We investigated two types of random fields, i.e., colored noises and discrete white noises, both of which can lead to high-dimensional parametric dependence in practice. The motivation is to exploit domain decomposition to reduce the parametric dimension of local problems in subdomains, such that an entire parametric map can be approximated with a small number of expensive partial differential equation (PDE) simulations. The new method combines domain decomposition with model reduction and sparse polynomial approximation, so as to simultaneously handle the high dimensionality and irregular behavior of the PDEs under consideration. Here, the advantages of our method lie in three aspects: (i) online-offline decomposition, i.e., the online cost is independent of the size of the triangle mesh; (ii) sparse approximation of operators involving nonaffine high-dimensional random fields; (iii) an effective strategy to capture irregular behaviors, e.g., sharp transitions of the PDE solutions. Two numerical examples are provided to demonstrate the advantageous performance of our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Efficient Reformulation of Linear and Nonlinear Solid-Phase Diffusion in Lithium-ion Battery Models using Symmetric Polynomials: Mass Conservation and Computational Efficiency

Lithium-ion batteries are typically modeled using porous electrode theory coupled with various transport and reaction mechanisms, along with suitable discretization or approximations for the solid-phase diffusion equation. The solid-phase diffusion equation represents the main computational burden for typical pseudo-2-dimensional (p2D) models since these equations in the pseudo r -dimension must be solved at each point in the computational grid. This substantially increases the complexity of the model as well as the computational time. Traditional approaches towards simplifying solid-phase diffusion possess certain significant limitations, especially in modeling emerging electrode materials which involve phase changes and variable diffusivities. A computationally efficient representation for solid-phase diffusion is discussed in this paper based on symmetric polynomials using Orthogonal Collocation and Galerkin formulation (weak form). A systematic approach is provided to increase the accuracy of the approximation (p form in finite element methods) to enable efficient simulation with a minimal number of semi-discretized equations, ensuring mass conservation even for non-linear diffusion problems involving variable diffusivities. These methods are then demonstrated by incorporation into the full p2D model, illustrating their advantages in simulating high C-rates and short-time dynamic operation of Lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

A Method for Obtaining Liquid–Solid Adsorption Rates from Molecular Dynamics Simulations: Applied to Methanol on Pt(111) in H 2 O

Adsorption is an important step in heterogeneous catalysis as it predetermines how many reactant molecules can participate in a surface reaction per unit time. While the rate of adsorption processes is well studied in gas–solid adsorption in both theory and experiment, such rates are still not well studied for liquid–solid adsorption. This is partly because the ever-changing configurations of liquid-phase solvent molecules impede the ability to study a molecule approaching a surface from a liquid phase by either experiment or theory. In this work, we develop a method using molecular dynamics (MD) simulations to study the rate of adsorption in liquid–solid adsorption processes. Specifically, we use MD to model the diffusion of a methanol molecule in aqueous solvent and its adsorption to a Pt(111) surface. We find that by approximating the solute motion as following the same displacement rates as a random walk model, the adsorbed and non-adsorbed states of the methanol molecule near the Pt(111) surface can be discerned and quantified. In particular, this methodology enables extracting a sticking coefficient and a macroscopically relatable adsorption rate. This method can be applied to arbitrary types of reactants and surfaces, as well as different liquid environments, thus providing a general tool for predicting quantitative adsorption rates of liquid–solid adsorption systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Multi-Dimensional Quantum Tunneling and Transport Using the Density-Gradient Model

We show that quantum effects are likely to significantly degrade the performance of MOSFETs (metal oxide semiconductor field effect transistor) as these devices are scaled below 100 nm channel length and 2 nm oxide thickness over the next decade. A general and computationally efficient electronic device model including quantum effects would allow us to monitor and mitigate these effects. Full quantum models are too expensive in multi-dimensions. Using a general but efficient PDE solver called PROPHET, we implemented the density-gradient (DG) quantum correction to the industry-dominant classical drift-diffusion (DD) model. The DG model efficiently includes quantum carrier profile smoothing and tunneling in multi-dimensions and for any electronic device structure. We show that the DG model reduces DD model error from as much as 50% down to a few percent in comparison to thin oxide MOS capacitance measurements. We also show the first DG simulations of gate oxide tunneling and transverse current flow in ultra-scaled MOSFETs. The advantages of rapid model implementation using the PDE solver approach will be demonstrated, as well as the applicability of the DG model to any electronic device structure.

Biegel, Bryan A.↗
DOE OSTI2025

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗
NASA NTRS1995

Vibrationally excited H2, HCl, and NO(+) in the diffuse clouds toward Zeta Ophiuchi

Absorption lines from vibrationally excited H2 and from HCl were detected in the ultraviolet spectrum of Zeta Oph with the Hubble Space Telescope (HST). Improved upper limits on NO(+) absorption were obtained as well. The data were analyzed with an updated version of a chemical model for diffuse clouds (van Dishoeck & Black 1986) as a guide to understanding this gaseous environment. The comparisons suggest that the flux of ultraviolet radiation impinging on the cloud surface is approximately 1-2 times the average interstellar radiation field, which is lower than once believed.

Federman, S. R.↗
NASA NTRS2003

The Chemical Composition and Gas-to-Dust Mass Ratio of Nearby Interstellar Matter

We use recent results on interstellar gas toward nearby stars and interstellar by-products within the solar system to select among the equilibrium radiative transfer models of the nearest interstellar material presented in Slavin & Frisch. For the assumption that O/H - 400 parts per million, models 2 and 8 are found to yield good fits to available data on interstellar material inside and outside of the heliosphere, with the exception of the Ne abundance in the pickup ion and anomalous cosmic-ray populations. For these models, the interstellar medium (ISM) at the entry point to the heliosphere has n(H(sup 0)) = 0.202-0.208/cu cm, n(He(sup 0) = 0.0137-0.0152/cu cm, and ionizations X(H) = 0.29-0.30, X(He) = 0.47-0.51. These best models suggest that the chemical composition of the nearby ISM is approx.60%-70% subsolar if S is undepleted. Both H(0) and H(+) need to be included when evaluating abundances of ions found in warm diffuse clouds. Models 2 and 8 yield an H filtration factor of approx.0.46. Gas-to-dust mass ratios for the ISM toward epsilon CMa are R(sub gd) = 178-183 for solar abundances of Holweger or R(sub gd) = 611-657 for an interstellar abundance standard 70% solar. Direct observations of dust grains in the solar system by Ulysses and Galileo yield R(sub gd) appr0x. 115 for models 2 and 8, supporting earlier results (Frisch and coworkers). If the local ISM abundances are subsolar, then gas and dust are decoupled over small spatial scales. The inferred variation in R(sub gd) over parsec length scales is consistent with the fact that the ISM near the Sun is part of a dynamically active cluster of cloudlets flowing away from the Sco-Cen association. Observations toward stars within approx.500 pc show that R(sub gd) correlates with the percentage of the dust mass that is carried by iron, suggesting that an Fe-rich grain core (by mass) remains after grain destruction. Evidently large dust grains (>10(exp -13) g) and small dust grains (<10(exp -13) g) are not well mixed over parsec length spatial scales in the ISM. It also appears that very small C-dominated dust grains have been destroyed in the ISM within several parsecs of the Sun, since C appears to be essentially undepleted. However, if gas-dust coupling breaks down over the cloud lifetime, the missing mass arguments applied here to determine R(sub gd) and dust grain mineralogy are not appropriate.

Frisch, Priscilla C.↗
DOE OSTI2019

Studying Nanosecond Discharge in Argon at Atmospheric Pressure with Preionization

The influence of initial conditions on specific features of the formation and development of a cathode-directed ionization wave between two flat electrodes in argon at atmospheric pressure was studied at nanosecond time resolution using a high-speed photoelectron monitor and numerical simulations based on the two-dimensional axisymmetric diffusion–drift model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Reproducing curvature effects due to differential diffusion in tabulated chemistry for premixed flames

Tabulated chemistry reduces the cost of modeling reacting flows by transporting fewer scalars. It also has the benefit of introducing fewer terms that must be closed for Reynolds-averaged Navier-Stokes and large eddy simulation modeling. In this study of premixed lean hydrogen–air flames, an extension to an existing tabulated chemistry model was developed by including differential diffusion and thermal diffusion of multiple species, using a mixture-averaged diffusion model. The transport equations for the tabulation variables (a progress variable and a mixture fraction-like variable) have been formulated, and curvature effects are intrinsic to the transport equations derived from first principles. The mathematical derivation is general, such that other fuel/air mixtures could be examined. The new tabulated chemistry model was then validated using a range of configurations, including flames with curvature, extinction, and hot spots. The model validation indicated excellent agreement with detailed chemistry simulations for lean premixed hydrogen–air mixtures. Conditional means of the progress variable source term were shown to agree well with detailed chemistry simulations of two-dimensional freely propagating flames and three-dimensional turbulent flames. Finally, progress variable source terms three times higher than one-dimensional flat flame results were identified and validated with detailed chemistry, and super-adiabatic hot spots were also predicted in the turbulent flame configuration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Route to Design Novel Functional Peptides by Applying a Denoising Diffusional Model to mRNA Display Libraries

In vitro directed evolution techniques, such as mRNA display, enable peptide ligand discovery and optimization. However, physical libraries that rely on a genetic code can only search a small fraction of sequence space due to inherent biases in the genetic code and experimental limitations. To address this challenge, denoising diffusion implicit models (DDIMs) are applied to generate novel peptide ligands against B‐cell lymphoma extra‐large (Bcl‐x L ), a key cancer target. Starting with high‐throughput sequencing data from previous selections, a DDIM is trained to produce novel sequences with high affinity binding. Experimental validation confirms that most generated sequences are functionally equivalent to the original library members for Bcl‐x L binding and demonstrated comparable binding kinetics and affinity relative to the wildtype and nearest original neighbors. Importantly, this approach generated rare sequences not easily accessible via mutation and directed evolution. These results indicate that DDIMs can complement and expand directed evolution data, efficiently exploring underrepresented regions of sequence space. This approach provides a broadly applicable framework for accelerating ligand discovery and optimizing molecular properties across diverse targets.

Qi, Pearl [Mork Family Department of Chemical Engi↗
DOE OSTI2019

Determining acceptable limits of fast-electron preheat in direct-drive-ignition–scale target designs

In direct-drive–ignition designs, preheat by fast electrons created by the two-plasmon–decay or stimulated Raman instabilities can increase the adiabat in the fuel layer and reduce compression and neutron yield. Since eliminating the preheat entirely is a major challenge, it is necessary to understand the levels of preheat that preclude ignition in a direct-drive target. Two 1-D ignition-scale target designs serve as the basis for examining the effects of synthetically increasing the levels of fast electrons using the 1-D radiation–hydrodynamic code LILAC , which includes two models of fast-electron transport. The first is an ignition design adapted from a 2-D polar-direct-drive (PDD) design for the National Ignition Facility (NIF). The second is derived from the first but uses a laser pulse that generates stronger shocks and a higher fuel adiabat. This more stable “alpha-burner” design approaches ignition and achieves yield multiplication as a result of alpha heating. The designs are then re optimized to recover performance. The igniting design, when fast-electron transport was modeled with diffusion, was found to tolerate 50% more fast-electron preheat of the cold (sub-50 eV) DT ice layer when the laser pulse was optimized using the optimizer Telios . When a straight-line fast-electron transport model was used, the effects of optimization were negligible. For the alpha-burner design, an increase of over a factor of at least 3 in the tolerable level of fast-electron preheat was obtained for both transport models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Methane production and emissions in trees and forests

Forest ecosystem methane (CH 4 ) research has focused on soils, but trees are also important sources and sinks in forest CH 4 budgets. Living and dead trees transport and emit CH 4 produced in soils; living trees and dead wood emit CH 4 produced inside trees by microorganisms; and trees produce CH 4 through an abiotic photochemical process. Here, we review the state of the science on the production, consumption, transport, and emission of CH 4 by living and dead trees, and the spatial and temporal dynamics of these processes across hydrologic gradients inclusive of wetland and upland ecosystems. Emerging research demonstrates that tree CH 4 emissions can significantly increase the source strength of wetland forests, and modestly decrease the sink strength of upland forests. Scaling from stem or leaf measurements to trees or forests is limited by knowledge of the mechanisms by which trees transport soil-produced CH 4 , microbial processes produce and oxidize CH 4 inside trees, a lack of mechanistic models, the diffuse nature of forest CH 4 fluxes, complex overlap between sources and sinks, and extreme variation across individuals. Understanding the complex processes that regulate CH 4 source–sink dynamics in trees and forests requires cross-disciplinary research and new conceptual models that transcend the traditional binary classification of wetland vs upland forest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Effects of Moisture on Diffusion in Unmodified Wood Cell Walls: A Phenomenological Polymer Science Approach

Despite the importance of cell wall diffusion to nearly all aspects of wood utilization, diffusion mechanisms and the detailed effects of moisture remain poorly understood. In this perspective, we introduce and employ approaches established in polymer science to develop a phenomenological framework for understanding the effects of moisture on diffusion in unmodified wood cell walls. The premise for applying this polymer-science-based approach to wood is that wood polymers (cellulose, hemicelluloses, and lignin) behave like typical solid polymers. Therefore, the movement of chemicals through wood cell walls is a diffusion process through a solid polymer, which is in contrast to previous assertions that transport of some chemicals occurs via aqueous pathways in the cell wall layers. Diffusion in polymers depends on the interrelations between free volume in the polymer matrix, molecular motions of the polymer, diffusant dimensions, and solubility of the diffusant in the polymer matrix. Because diffusion strongly depends on whether a polymer is in a rigid glassy state or soft rubbery state, it is important to understand glass transitions in the amorphous wood polymers. Through a review and analysis of available literature, we conclude that in wood both lignin and the amorphous polysaccharides very likely have glass transitions. After developing and presenting this polymer-science-based perspective of diffusion through unmodified wood cell walls, suggested directions for future research are discussed. A key consideration is that a large difference between diffusion through wood polymers and typical polymers is the high swelling pressures that can develop in unmodified wood cell walls. This pressure likely arises from the hierarchical structure of wood and should be taken into consideration in the development of predictive models for diffusion in unmodified wood cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Diffuse X-ray scattering from polished silicon: application of the distorted wave Born approximation

Measured diffuse X-ray scattering data for a `smooth' as well as for a `rough' silicon sample were fit to theoretical expressions within the distorted wave Born approximation (DWBA). Data for the power spectral density (PSD) for both samples were also obtained by means of atomic force microscopy and optical interferometry. The Fourier transforms of trial correlation functions were fit to the PSD data and then applied to the DWBA formalism. The net correlation functions needed to fit the PSD data for each sample comprised the sum of two terms with different cutoff lengths and different self-affine fractal exponents. At zero distance these correlation functions added up to yield net values of σ 2 = (2) 2 and (71) 2 Å 2 for the smooth and rough samples, respectively. X-ray scattering data were obtained at beamline 1-BM of the Advanced Photon Source. Data and fits at values of q z = 0.05 and 0.10 Å −1 for the smooth sample are reported. Good fits for the smooth sample were obtained at both q z values simultaneously, that is, identical fitting parameters were applied at both values of q z . The smooth sample also exhibited weak Yoneda wings and a clear distinction between the strong specular scattering and the weak diffuse scattering. Data for the rough sample were qualitatively different and exhibited very weak scattering at the specular condition in contrast to extremely large Yoneda wings. Fits for the rough sample are reported for q z = 0.04, 0.05, and 0.06 Å −1 . Although the large Yoneda wings could be fit quite well in both position and amplitude, scattering near the specular condition could not be equally well fit by applying the same fitting parameters at all values of q z . Albeit imperfect, best-fitting results at the specular condition were obtained by invoking only diffuse scattering, that is, without including a separate theoretical expression for specular scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1986

Fluctuation and rotation in diffusion-influenced monomolecular reactions

Models of partially absorbing boundaries for calculating diffusion-influenced chemical reactions are examined analytically. The limitations of diffusion-equation and random-walk models are indicated; the presence of an ambiguous length parameter in a standard radiation-boundary-condition (RBC) model is demonstrated; the RBC model for a boundary with oscillation (at a rate much faster than the rate of thermal collisions) between absorbing and nonabsorbing states is considered; an alternative stochastically switching absorber (SSA) model is introduced and shown to be physically consistent; the equivalence of one-dimensional RBC and SSA models under some conditions is shown; one time passage is calculated for an axially symmetric three-dimensional SSA model with anisotropic absorption; and the analogy between rotation and stochastic switching is explored.

Bashford, Donald↗