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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Lattice-Renormalized Tunneling Models for Superconducting Qubit Materials

We present a lattice-renormalized formalism for configurational tunneling two-level systems (TLS) that overcomes limitations of minimum-energy-path and light-particle models. Derived from the nuclear Hamiltonian, our formulation introduces composite phonon coordinates to capture lattice distortions between degenerate potential wells. This approach resolves deficiencies in prior models and enables accurate computation of tunnel splittings and excitation spectra for hydrogen-based TLS in bcc Nb. Our results bound experimental tunnel splittings and reveal strong anharmonic couplings between tunneling atoms and lattice phonons, establishing a direct link between TLS dynamics and phonon-mediated strain interactions. The formalism further generalizes to multi-level systems (MLS), providing insight into defect-induced decoherence in superconducting qubits and guiding strategies for materials design to suppress TLS-related loss.

Pritchard, P. G. [Northwestern U.]↗
DOE OSTI2017

Bayesian Regression of Thermodynamic Models of Redox Active Materials

Finding a suitable functional redox material is a critical challenge to achieving scalable, economically viable technologies for storing concentrated solar energy in the form of a defected oxide. Demonstrating e ectiveness for thermal storage or solar fuel is largely accomplished by using a thermodynamic model derived from experimental data. The purpose of this project is to test the accuracy of our regression model on representative data sets. Determining the accuracy of the model includes parameter tting the model to the data, comparing the model using di erent numbers of param- eters, and analyzing the entropy and enthalpy calculated from the model. Three data sets were considered in this project: two demonstrating materials for solar fuels by wa- ter splitting and the other of a material for thermal storage. Using Bayesian Inference and Markov Chain Monte Carlo (MCMC), parameter estimation was preformed on the three data sets. Good results were achieved, except some there was some deviations on the edges of the data input ranges. The evidence values were then calculated in a variety of ways and used to compare models with di erent number of parameters. It was believed that at least one of the parameters was unnecessary and comparing evidence values demonstrated that the parameter was need on one data set and not signi cantly helpful on another. The entropy was calculated by taking the derivative in one variable and integrating over another. and its uncertainty was also calculated by evaluating the entropy over multiple MCMC samples. Afterwards, all the parts were written up as a tutorial for the Uncertainty Quanti cation Toolkit (UQTk).

36 MATERIALS SCIENCE↗
DOE OSTI2017

A Bayesian approach to modeling diffraction profiles and application to ferroelectric materials

A new statistical approach for modeling diffraction profiles is introduced, using Bayesian inference and a Markov chain Monte Carlo (MCMC) algorithm. This method is demonstrated by modeling the degenerate reflections during application of an electric field to two different ferroelectric materials: thin-film lead zirconate titanate (PZT) of composition PbZr 0.3 Ti 0.7 O 3 and a bulk commercial PZT polycrystalline ferroelectric. Here, the new method offers a unique uncertainty quantification of the model parameters that can be readily propagated into new calculated parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗
DOE OSTI2016

Investigating Accident Tolerant Fuel Concepts using the BISON Fuel Performance Code

There has been an increased interest in research of accident tolerant fuels (ATF) and claddings for use in commercial reactors ever since the events that occurred at the Fukushima Daiichi nuclear power plant in 2011. The economic impact of these events on the nuclear energy sector is significant. As a result, the United States Department of Energy's Office of Nuclear Energy accelerated research in nuclear fuel concepts with enhanced accident tolerance as part of its Fuel Cycle Research and Development (FCRD) Advanced Fuels Campaign (AFC). A report produced by the AFC entitled Light Water Reactor Accident Tolerant Fuel Performance Metrics outlines a set of metrics that can be used to guide selection of promising ATF concepts. Moreover, the report specifies that a down-selection is to occur in the 2016-2017 time frame, at which time the program will move from a proof-of-concept to a proof-of-principle stage with continued research and development into a small set of concepts. Given the time necessary for comprehensive irradiation experiments and post-irradiation examination, it is impossible to perform a complete set of experiments for material characterization. Therefore, the AFC is utilizing computational analysis tools in an effort to understand the proposed materials under a variety of normal operating and accident conditions. For some time, the DOE's Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has been developing computational analysis tools for nuclear fuel simulation. These codes include BISON and Marmot which investigate fuel behavior at the continuum and microstructural scales, respectively. In 2014, NEAMS introduced what it calls High Impact Problems (HIPs) into its program plan. These HIPs are intended to make significant advancements in a particular area of nuclear power research in a short period of time (3 years or less). NEAMS has chosen an ATF project, which emphasizes utilizing BISON and Marmot to model proposed materials, as its first HIP. This summary focuses on the methodology being utilized for investigation of ATF concepts using the BISON fuel performance code. First, we give an overview of the model development for two candidate ATF materials, FeCrAl for cladding and uranium silicide (U{sub 3}Si{sub 2}) for fuel. Then, we present the approach for deciding which simulations are necessary given the importance of such simulations in providing a detailed report into the fuel performance behavior of these materials by the conclusion of the HIP. In absence of experimental data and given the aggressive schedule outlined by the AFC for ATF research and development, computational analysis tools are required. These tools are being used to help guide experiment design and to perform bounding and sensitivity studies to gain valuable information for which experimental data is limited. In support of this effort, models have been incorporated into BISON for simulation of U{sub 3}Si{sub 2} and FeCrAl. Continued material model development and engineering analysis will help address questions related to the performance of these ATF materials under normal operating and accident conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Elucidating the effects of adsorbent flexibility on fluid adsorption using simple models and flat-histogram sampling methods

Using flat-histogram Monte Carlo methods, we investigate the adsorptive behavior of the square-well fluid in two simple slit-pore-like models intended to capture fundamental characteristics of flexible adsorbent materials. Both models require as input thermodynamic information about the flexible adsorbent material itself. An important component of this work involves formulating the flexible pore models in the appropriate thermodynamic (statistical mechanical) ensembles, namely, the osmotic ensemble and a variant of the grand-canonical ensemble. Two-dimensional probability distributions, which are calculated using flat-histogram methods, provide the information necessary to determine adsorption thermodynamics. For example, we are able to determine precisely adsorption isotherms, (equilibrium) phase transition conditions, limits of stability, and free energies for a number of different flexible adsorbent materials, distinguishable as different inputs into the models. While the models used in this work are relatively simple from a geometric perspective, they yield non-trivial adsorptive behavior, including adsorption-desorption hysteresis solely due to material flexibility and so-called “breathing” of the adsorbent. The observed effects can in turn be tied to the inherent properties of the bare adsorbent. Some of the effects are expected on physical grounds while others arise from a subtle balance of thermodynamic and mechanical driving forces. In addition, the computational strategy presented here can be easily applied to more complex models for flexible adsorbents.

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

srlife: A Fast Tool for High Temperature Receiver Design and Analysis

This report describes a tool for estimating the structural service life of tubular, panel solar receivers operating at high temperatures. A complete version of the tool is available as open source software at https://github.com/Argonne-National-Laboratory/srlife and can be installed through the PyPi (https://pypi.org) package manager. Given the basic receiver geometry and the thermal loads on the receiver, the tool provides 1D, 2D, or 3D thermal and structural (single tube and simplified system) analysis and creep-fatigue service life prediction for six metallic alloys – 316H, 800H, Alloy 617, Alloy 740H, and Alloy 230. With the exception of Alloy 230 where the material data is preliminary, the software included a detailed set of models for the materials, well-supported by high temperature experimental test data. The tool is designed for easy integration with a software stack, including solar field and thermohydraulic simulations, for optimizing receiver designs to meet service life and economic targets. The report describes several heuristics that can be applied in srlife to reduce the analysis time by several orders of magnitude but with fairly accurate life estimation when compared with full analysis. The report provides several examples demonstrating the utility of srlife in receiver design. Finally, the report discusses high temperature tests on Alloy 282, collected as part of this project, used to develop and support the material model for that alloy.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

A Study of Green's Function Methods Applied to Space Radiation Protection

The purpose of this research was to study the propagation of galactic ions through various materials. Galactic light ions result from the break up of heavy ion particles and their propagation through materials is modeled using the one-dimensional Boltzmann equation. When ions enter materials there can occur (i) the interaction of ions with orbital electrons which causes ionization within the material and (ii) ions collide with atoms causing production of secondary particles which penetrate deeper within the material. These processes are modeled by a continuum model. The basic idea is to place a control volume within the material and examine the change in ion flux across this control volume. In this way on can derive the basic equations for the transport of light and heavy ions in matter. Green's function perturbation methods can then be employed to solve the resulting equations using energy dependent nuclear cross sections.

Heinbockel, John H.↗
DOE OSTI2015

Critical thickness of atomically ordered III-V alloys

The critical thickness model is modified with a general boundary energy that describes the change in bulk energy as a dislocation regularly alters the atomic structure of an ordered material. The model is evaluated for dislocations gliding through CuPt-ordered GaInP and GaInAs, where the boundary energy is negative and the boundary is stable. With ordering present, the critical thickness is significantly lowered and remains finite as the mismatch strain approaches zero. The reduction in critical thickness is most significant when the order parameter is greatest and the amount of misfit energy is low. The modified model is experimentally validated for low-misfit GaInP epilayers with varying order parameters using in situ wafer curvature and ex situ cathodoluminescence. With strong ordering, relaxation begins at a lower thickness and occurs at a greater rate, which is consistent with a lower critical thickness and increased glide force. Thus, atomic ordering is an important consideration for the stability of lattice-mismatched devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A fully coupled thermal–microstructural–mechanical finite element process model for directed energy deposition additive manufacturing of Ti–6Al–4V

A fully coupled thermal–microstructural–mechanical finite element modelling framework is developed to investigate the distortion and residual stresses during directed energy deposition (DED) of multi-phase Ti–6Al–4V alloy. The Johnson–Cook constitutive model is used to predict the yield strength of each phase as a function of strain, strain rate and temperature where the flow stress is calculated by a linear mixing rule based on the volumetric phase fractions. A thin-walled rectangular sample is chosen as the reference geometry and the results are compared with experimentally measured in situ thermal history and distortion data, where a reasonable agreement is achieved. The proposed modelling framework with physics-based material constitutive model provides useful information for a better understanding of process–microstructure–property relations in additive manufacturing by DED.

Tunay, Merve↗
DOE OSTI2024

Modeling the Impacts of Material Properties on Oscillatory Neuron Behavior

In this study, neuromorphic computing, which mimics the functions of biological brains, offers improvements in both latency and energy efficiency over typical von Neumann computing architectures. Spiking neural networks can be especially power-efficient because they encode information temporally and can use more sparse electrical inputs. Here, we study the design of volatile memristors (variable resistors with memory) for neuronal devices, with particular consideration toward the feasibility of all-on-chip oscillation using built-in capacitance. We use circuit simulations to model the behavior of oscillator neurons with a range of realistic material properties. We find that energy inputs increase with insulating-phase resistivity, thermal conductivity, and device aspect ratio. However, we also find that the minimum capacitance needed for oscillation decreases with increasing insulating-phase resistivity, which opposes the constraints for power efficiency. Based on published data on NbO 2 , VO 2 , and EuNiO 3 , we find that existing materials can be engineered for all-on-chip spiking using their parasitic capacitance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multilevel atomic structural model for interstratified opal materials

The structure of opal has long fascinated scientists. It occurs in a number of structural states, ranging from amorphous to exhibiting features of stacking disorder. Opal-CT, where C and T signify cristobalite- and tridymite-like interstratification, represents an important link in the length scales between amorphous and crystalline states. However, details about local atomic (dis)order and arrangements extending to long-range stacking faults in opal polymorphs remain incompletely understood. Here, a multilevel modeling approach is reported that considers stacking states in correlation with the abundance of C and T segments as a high-level structural parameter (i.e. not each atom). Optimization accounting for inter-tetrahedral bond lengths and angles and the regularity of the silicate tetrahedra is included as lower levels of structural parameters. Together, a set of parameters with both coarse-grained and atomistic features for different levels of structural details is refined. Structural disorder at the ~10–100 Å distance scale is evaluated using experimental pair distribution function and diffraction datasets, comparing peak intensities, widths and asymmetry. Here this work presents a complete multilevel structural description of natural opal-CT and explains many of the unusual features observed in X-ray powder diffraction patterns. This modeling approach can be adopted generally for analyzing layered materials and their assembly into 3D structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗
DOE OSTI2021

From material properties to multiscale modeling to improve lithium-ion energy storage safety

Energy storage using lithium-ion cells dominates consumer electronics and is rapidly becoming predominant in electric vehicles and grid-scale energy storage, but the high energy densities attained lead to the potential for release of this stored chemical energy. This article introduces some of the paths by which this energy might be unintentionally released, relating cell material properties to the physical processes associated with this potential release. The selected paths focus on the anode–electrolyte and cathode–electrolyte interactions that are of typical concern for current and near-future systems. Relevant material processes include bulk phase transformations, bulk diffusion, surface reactions, transport limitations across insulating passivation layers, and the potential for more complex material structures to enhance safety. We also discuss the development, parameterization, and application of predictive models for this energy release and give examples of the application of these models to gain further insight into the development of safer energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2016

Equilibrium, metastability, and hysteresis in a model spin-crossover material with nearest-neighbor antiferromagnetic-like and long-range ferromagnetic-like interactions

Phase diagrams and hysteresis loops were obtained by Monte Carlo simulations and a mean- field method for a simplified model of a spin-crossovermaterialwith a two-step transition between the high-spin and low-spin states. This model is a mapping onto a square-lattice S = 1/2 Ising model with antiferromagnetic nearest-neighbor and ferromagnetic Husimi-Temperley ( equivalent-neighbor) long-range interactions. Phase diagrams obtained by the two methods for weak and strong long-range interactions are found to be similar. However, for intermediate-strength long-range interactions, the Monte Carlo simulations show that tricritical points decompose into pairs of critical end points and mean-field critical points surrounded by horn-shaped regions of metastability. Hysteresis loops along paths traversing the horn regions are strongly reminiscent of thermal two-step transition loops with hysteresis, recently observed experimentally in several spin-crossover materials. As a result, we believe analogous phenomena should be observable in experiments and simulations for many systems that exhibit competition between local antiferromagnetic-like interactions and long-range ferromagnetic-like interactions caused by elastic distortions.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho↗
DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients: Impact of Particle Deposition in ICRP 66 Human Respiratory Tract Model

Inhaled radioactive materials can pose a long-term health concern, as the material can be incorporated into the body’s metabolic pathways and remain in organs and tissues for extended durations. During the retention period, the radioactive material may localize in a source organ and irradiate adjacent target organs and tissues. Distribution of these materials changes over time, requiring biokinetic modeling to evaluate their movement through various tissues and organs. The evolving distribution depends on multiple inputs characterizing the inhaled material, such as particle size and size distribution, particle density, aspect ratio, specific radionuclide, the chemical form, and solubility. In addition, biological parameters such as breathing rate, breathing type (nasal or nasal/oral), respiratory system morphometry, tidal volume, functional residual capacity, and anatomical dead space all influence material transport. These aerosol properties and physiological characteristics of the respiratory tract jointly define a range of initial conditions that influence the time-dependent distribution of radioactive material. To evaluate both uncertainty in the initial conditions of inhalation exposure and the final output (committed effective dose) from biokinetic models, a Python-based software tool, Radiological Exposure Dose Calculator (REDCAL), was developed to propagate uncertainty within the human respiratory tract model. Focusing on deposition fraction uncertainty, the primary objective was to characterize the initial activity distribution across respiratory regions as a function of anticipated particle sizes and distributions. The impact of the deposition fraction uncertainty was propagated to committed effective dose coefficients for selected radionuclides in a companion publication. For each particle size, a lognormal distribution, characterized by its geometric mean as defined within ICRP Publication 66, serves as the basis for introducing uncertainty into the physical processes governing deposition in various lung regions. Finally, this study addresses the deposition process and examines how uncertainty in deposition mechanisms affects activity distribution in the airways, ultimately presenting the expected range and standard deviation of deposited activity as a function of particle size.

International Commission on Radiological Protectio↗