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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modelling the sulfate capacity of simulated radioactive waste borosilicate glasses

The capacity of simulated high-level radioactive waste borosilicate glasses to incorporate sulfate has been studied as a function of glass composition. Combined Raman, 57 Fe Mössbauer and literature evidence supports the attribution of coordination numbers and oxidation states of constituent cations for the purposes of modelling, and results confirm the validity of correlating sulfate incorporation in multicomponent borosilicate radioactive waste glasses with different models. A strong compositional dependency is observed and this can be described by an inverse linear relationship between incorporated sulfate (mol% SO 4 2- ) and total cation field strength index of the glass, Σ(z/a 2 ), with a high goodness-of-fit (R 2 ≈ 0.950). Similar relationships are also obtained if theoretical optical basicity, Λ th (R 2 ≈ 0.930) or non-bridging oxygen per tetrahedron ratio, NBO/T (R 2 ≈ 0.919), are used. Results support the application of these models, and in particular Σ(z/a 2 ), as predictive tools to aid the development of new glass compositions with enhanced sulfate capacities.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Bergman-type medium range order in amorphous Zr77Rh23 alloy studied by ab initio molecular dynamics simulations

In recent years, some arguments about the existence of medium-range order (MRO) in the Zr-Rh system have been put forward. However, research on the structural features of the Zr-Rh binary alloy at the atomic level is still lacking. This study uses ab initio molecular dynamics simulations to systematically study the local structures of Zr77Rh23 from the liquid to the glassy states. Pair correlation function (PCF), coordination number (CN), Honeycutt–Anderson(HA) index, bond-angle distribution functions, and the Voronoi tessellation method are used to reveal a clear icosahedral-like configuration in the amorphous Zr77Rh23 alloy. It is noteworthy that the splitting in the second peak of the partial PDF implies the existence of a medium range order (MRO) in the Zr77Rh23 system. We obtain the local order in three-dimensional atomic density distributions by using a new atomistic cluster alignment (ACA) method. Interestingly, a Bergman-type MRO is observed in the glassy Zr77Rh23. Furthermore, the spatial distribution and connections of icosahedral-like clusters are shown to further demonstrate the MRO network. Our findings shed light on the nature of atomic local structures of amorphous Zr77Rh23 alloy and have important implications to understanding the formation of various MROs in metallic glasses.

Guo, Y. R.↗
DOE OSTI2022

Structures of Vanadium-Containing Silicate and Borosilicate Glasses: Vanadium Potential Development and MD Simulations

Vanadium-containing multi-component glasses have been found with widely interests in various applications. However, the complex compositions, thus structures, lead to the challenges in experiments to understand the structural origin of the property change of these glasses. In this work, we developed compatible vanadium-related parameters for a widely used pair wise potential set to enable the simulations of the vanadium-containing multi-component glasses. Various crystal structures and glass compositions (with vanadium in different oxidation states) have been tested using the newly developed parameters, and structural information of cell parameters, pair distribution function, estimated bond distance, and coordination number have been obtained. The results are in good agreement with available experimental data, which indicates the new vanadium parameters can be used to simulate the vanadium-containing multi-component glasses and thus help study those applications with wide interests.

Deng, Lu↗
DOE OSTI2022

Numerical simulations of membrane distillation systems with actively heated membranes

Membrane distillation (MD) is a thermal desalination process that is gaining attention for treating hypersaline brines. One recent approach uses composite membranes with a thermally conductive layer that delivers heat to the membrane–feed interface, where it drives evaporation. Though this increases single-pass recovery, it comes with the challenge of promoting lateral heat conduction through the thin membrane. Herein, we develop a 3D, computational fluid dynamics (CFD) model that simulates conjugate heat, mass, and momentum transport in the feed channel and composite membrane. We then use the CFD to verify a simpler numerical model that approximates the feed velocity field analytically. We validate the numerical model experimentally, and use it to investigate the impacts of the conductive layer thickness, feed channel geometry, and operating conditions on temperature and concentration polarization, permeate production, and specific energy consumption. Overall, we find that lateral heating increases permeate production at the expense of increased concentration polarization. In extreme cases, the concentration increases more than four-fold along the membrane surface. Furthermore, we show however, that the feed flow rate and conductive layer thickness can be tailored to mitigate concentration polarization, for only a small reduction in permeate production.

42 ENGINEERING↗
DOE OSTI2019

Simulations of a high-density, highly-radiating lithium divertor

Results are presented for one- and two-dimensional (2D) edge plasma transport simulations for strong injection of lithium (Li) in the divertor region of a tokamak. The model includes the scrape-off layer and divertor regions, and, for 2D, a small region inside the magnetic separtrix. Equations are solved for the density and momentum of a deuterium/tritium (DT) species and all three charge states of Li, in addition to separate ion and electron energy equations via the UEDGE code. Equations are also included for the DT and Li gas species. Lithium gas is injected from the side walls or divertor plate, implying that these surfaces are evaporating liquid Li. For a range of Li gas input, steady-state, detached-plasma solutions are shown where greater than 90% of the exhaust power is radiated by Li, resulting in peak surface heat fluxes ~2 MW/m 2 on the divertor plate, outer wall, and private-flux wall. While Li ions dominate in the divertor leg, their density is in the range of 10% of the DT density at the midplane. The collisional parallel thermal force plays a key role in determining the midplane ion Li density, and sensitivity of results to different model assumptions are discussed. Here the key issue is possible dilution of the core DT fuel. A brief comparison of the Li neutral solution is made with that from the Direct Simulation Monte-Carlo (DSMC) SPARTA code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Coarse-grained discrete particle simulations of particle segregation in rotating fluidized beds in vortex chambers [Discrete particle simulations of particle segregation in rotating fluidized beds in vortex chambers]

Vortex chambers allow the generation of rotating fluidized beds, offering high-G intensified gas-solid contact, gas-solids separation and solids-solids segregation. Focusing on binary particle mixtures and fixing the density and diameter of the heavy/large particles, transient batch CFD-coarse-grained DPM simulations were carried out with varying densities or sizes of the light/small particles to evaluate to what extent combining these three functionalities is possible within a vortex chamber of given design. Both the rate and quality of segregation were analyzed. Within a relatively wide density and size range, fast and efficient segregation takes place, with an inner and slower rotating bed of the lighter/small particles forming within the outer and faster rotating bed of the heavier/large particles. Simulations show that the contamination of the outer bed with lighter particles occurs more easily than contamination of the inner bed with heavier particles and increases with decreasing difference in size or density of the particles. Bubbling in the inner bed is observed with an inner bed of very low density or small particles. Porosity plots show that vortex chambers with a sufficient number of gas inlet slots have to be used to guarantee a uniform gas distribution and particle bed. Lastly, the flexibility of particle segregation in vortex chambers with respect to the gas flow rate is demonstrated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Equilibria and Rate Phenomena from Atomistic to Mesoscale: Simulation Studies of Magnetite

Batteries are complex devices composed of multiple components that operate far from equilibrium and may operate under extreme stress and varying loads. Research of isolated battery components are valuable to the fundamental understanding of the physical processes occurring within each constituent element. When the components are integrated into a full device and operated under realistic conditions, it can be difficult to decouple the physical processes that occur across multiple interfaces and multiple length scales. Thus, the physical processes studied in isolated components may change in a full battery setup or may be irrelevant to performance. Simulation studies on many length scales play a key role in the analysis of experiments and in the elucidation of the relevant physical processes impacting performance. In this Account, we aim to highlight the use of modeling on multiple length scales to identify rate limiting phenomena in lithium-ion batteries. To illustrate the utility of modeling, we examine lithium-ion batteries with nanostructured magnetite, Fe 3 O 4 , as the positive electrode active material against a solid Li 0 negative electrode. Due to continuous operation away from equilibrium, batteries exhibit highly nonideal behavior, and a model that aims to reproduce behavior under realistic operating conditions must be able to capture the physics occurring on the length scales relevant to the performance of the system. It is our experience that limiting behavior in lithium-ion batteries can be observed on the atomic scale and up through the electrode scale and thus, predictive models must be capable of integrating and communicating physics across multiple length scales. Magnetite is studied as an electrode material for lithium-ion batteries, but it is found to suffer from slow solid-state transport of lithium, slow reaction kinetics, and poor cycling. Magnetite (Fe 3 O 4 ) is a material capable of undergoing multiple electron transfers (MET), and can accept up to eight lithium per formula unit (Li 8 Fe 3 O 4 ). Magnetite, (Fe 8a 3+ )[Fe 3+ Fe 2+ ] 16d O 4,32e 2– , has a close-packed inverse spinel structure and undergoes intercalation, structural rearrangement, and conversion reactions upon full lithiation. To overcome solid-state transport resistances, magnetite can be nanostructured to decrease Li + diffusion lengths, and this has been shown to increase capacity. Additionally, unique architectures incorporating both carbon and Fe 3 O 4 have shown to alleviate transport and cycling issues in the material. Here, we solely address traditional composite electrodes, in which Fe 3 O 4 is synthesized as nanoparticles and combined with additives to fabricate the electrode. In the case of nanoparticulate magnetite, it has been found that the electrode fabrication process results in the formation of micrometer-sized agglomerates of the Fe 3 O 4 nanoparticles, introducing a secondary structural motif. The agglomerates may form in one or more fabrication processes, and their elimination may not be straightforward or warranted. Here, we highlight the impact of these secondary formations on the performance of the Fe 3 O 4 lithium-ion battery. We illustrate how simulations can be used to design experiments, prioritize research efforts, and predict performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Molecular Simulation of Lithium Carbonate Reactive Vapor–Liquid Equilibria Using a Deep Potential Model

We developed a first-principles machine learning model for the reactive vapor–liquid phase behavior of molten Li 2 CO 3 . The model was trained on ab initio electronic density functional theory data using the Deep Potential (DP) methodology, and its accuracy was evaluated by comparing model predictions of density and viscosity to experimental measurements. Direct coexistence simulations with the DP model over time scales of tens of nanoseconds were used to observe equilibrium dissociation of Li 2 CO 3 into CO 2 residing primarily in the vapor phase and Li 2 O which remains dissolved in the liquid. The simulations covered a range of temperatures, overall system sizes, and vapor-to-liquid volume ratios. Results were analyzed in terms of the observed chemical composition of the liquid and vapor phases, product structure, and CO 2 partial pressures. In addition, we calculated equilibrium constants for the dissociation reaction by assuming ideal-solution behavior for the liquid. As expected on the basis of thermodynamic arguments and prior experiments for this system, the observed partial pressure of CO 2 in the gas phase depends on both the temperature and the ratio of vapor to liquid volumes, while the calculated equilibrium constants only depend on temperature. DP model predictions for the equilibrium constant of the reaction are generally consistent with the available experimental measurements. Furthermore, the present study establishes the validity of the DP methodology for the description of reactive, multiphase equilibria from first principles, with possible applications to many other systems of scientific and technological interest even in the absence of relevant experimental measurements.

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

Combined Force-Frequency Sampling for Simulation of Systems Having Rugged Free Energy Landscapes.

An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinct states and the generalized force estimates that arise in a system as it evolves in phase space. This is accomplished by introducing a self-integrating artificial neural network, which generates an estimate of the free energy directly from its derivatives. The usefulness of the proposed combined approach is examined in the context of two concrete examples, namely, an alanine dipeptide molecule in water and a polymer diffusing through a narrow pore. This new method is found to be robust, faster, and more accurate than approaches that rely only on frequency-based or generalized force-based estimations. After combining the proposed approach with overfill protection and support for sparse data storage and training, the method is shown to be more effective than comparable, previously available techniques and capable of scaling efficiently to larger numbers of collective variables.

Sevgen, Emre↗
DOE OSTI2025

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Crystal Growth Simulations To Establish Physically Relevant Kinetic Parameters from the Empirical Kolmogorov-Johnson-Mehl-Avrami Model

A series of simulations was performed to enable interpretation of the material and physical significance of the parameters defined in the Kolmogorov, Johnson and Mehl, and Avrami (KJMA) rate expression commonly used to describe phase boundary controlled reactions of condensed matter. The parameters k, n, and t 0 are shown to be highly correlated, which if unaccounted for seriously challenge mechanistic interpretation. It is demonstrated that rate measurements exhibit an intrinsic uncertainty without precise knowledge of the location and orientation of nucleation with respect to the free volume into which it grows. More significantly, it is demonstrated that the KJMA rate constant k is highly dependent on sample size. However, under the simulated conditions of slow nucleation relative to crystal growth, sample volume and sample anisotropy correction affords a means to eliminate the experimental condition dependence of the KJMA rate constant, k, producing the material-specific parameter, the velocity of the phase boundary, v pb .

Dill, Eric D.↗
DOE OSTI2024

Real-Time Time-Dependent Density Functional Theory for Simulating Nonequilibrium Electron Dynamics

The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. Here, in this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.

Hamiltonians↗
DOE OSTI2020

Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

Abstract The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation.

Vilà‐Guerau de Arellano, J.↗