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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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First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu↗

Special Polymer/Carbon Composite Films for Detecting SO2

A family of polymer/carbon films has been developed for use as sensory films in electronic noses for detecting SO2 gas at concentrations as low as 1 part per million (ppm). Most previously reported SO2 sensors cannot detect SO2 at concentrations below tens of ppm; only a few can detect SO2 at 1 ppm. Most of the sensory materials used in those sensors (especially inorganic ones that include solid oxide electrolytes, metal oxides, and cadmium sulfide) must be used under relatively harsh conditions that include operation and regeneration at temperatures greater than 100 C. In contrast, the present films can be used to detect 1 ppm of SO2 at typical opening temperatures between 28 and 32 C and can be regenerated at temperatures between 36 and 40 C. The basic concept of making sensing films from polymer/carbon composites is not new. The novelty of the present family of polymer/carbon composites lies in formulating the polymer components of these composites specifically to optimize their properties for detecting SO2. First-principles quantum-mechanical calculations of the energies of binding of SO2 molecules to various polymer functionalities are used as a guide for selecting polymers and understanding the role of polymer functionalities in sensing. The polymer used in the polymer-carbon composite is a copolymer of styrene derivative units with vinyl pyridine or substituted vinyl pyridine derivative units. To make a substituted vinyl pyridine for use in synthesizing such a polymer, poly(2-vinyl pyridine) that has been dissolved in methanol is reacted with 3-chloropropylamine that has been dissolved in a solution of methanol. The methanol is then removed to obtain the copolymer. Later, the copolymer can be dissolved in an appropriate solvent with a suspension of carbon black to obtain a mixture that can be cast and then dried to obtain a sensory film.

Homer, Margie↗

An Ensemble Neural Network Model for Predicting Rare-Earth Oxide and Silicate Heat Capacities at High Temperature

In this work, a neural network model was developed to predict the constant pressure heat capacity for materials in the rare-earth oxide—silica material space. Several model architectures were trained and tested on heat capacity data generated from first-principles density functional theory calculations. Hyperparameter optimization was performed, and the optimal model was selected for heat capacity predictions. The optimal model architecture was found to have a root-mean-squared error of 5.12 ± 3.37 J/mol-K. The optimal model architecture was then used in a bagging ensemble model trained using the leave-one-group-out method to provide error estimates for model predictions. The out-of-bag score for the ensemble model was 0.997. The predicted heat capacities agree well with the DFT and experimental results and were computed orders of magnitude faster than DFT simulations. Machine learning shows the potential to provide a suitable surrogate model for thermochemical property predictions for candidate environmental barrier coating materials but refining of input material features and model architectures could further improve accuracy for these models.

environmental barrier coatings↗

Inverse isotope effect and the x dependence of the superconducting transition temperature in PdHx and PdDx

First-principles electron-band-structure calculations and measured phonon properties are employed in a calculation of the concentration dependence of the superconducting transition temperatures for PdHx and PdDx, including the inverse isotope effect. Excellent agreement with the experimental results is obtained. Our model also gives a qualitative understanding of the enhanced transition temperatures in the palladium-noble-metal hydrides.

Klein, B. M.↗

Modified lattice-statics approach to dislocation calculations. II - Application

The atomic structure of a screw dislocation core of the 110 line type in aluminum is calculated by the modified lattice-statics method developed in the preceding paper. The method includes anharmonic as well as harmonic forces and permits relaxation of the atoms in all three dimensions. All forces used in the present calculations were derived from a first-principles interatomic pair potential obtained via pseudopotential theory. Several significant differences from the ordinary lattice statics results are noted, including the displacement field, Peierl's energy barrier, and the equilibrium core-center location.

Esterling, D. M.↗

Analysis of the Defect Structure of B2 Feal Alloys

The Bozzolo, Ferrante and Smith (BFS) method for alloys is applied to the study of the defect structure of B2 FeAI alloys. First-principles Linear Muffin Tin Orbital calculations are used to determine the input parameters to the BFS method used in this work. The calculations successfully determine the phase field of the B2 structure, as well as the dependence with composition of the lattice parameter. Finally, the method is used to perform 'static' simulations where instead of determining the ground state configuration of the alloy with a certain concentration of vacancies, a large number of candidate ordered structures are studied and compared, in order to determine not only the lowest energy configurations but other possible metastable states as well. The results provide a description of the defect structure consistent with available experimental data. The simplicity of the BFS method also allows for a simple explanation of some of the essential features found in the concentration dependence of the heat of formation, lattice parameter and the defect structure.

Bozzolo, Guillermo↗

Computational techniques in tribology and material science at the atomic level

Computations in tribology and material science at the atomic level present considerable difficulties. Computational techniques ranging from first-principles to semi-empirical and their limitations are discussed. Example calculations of metallic surface energies using semi-empirical techniques are presented. Finally, application of the methods to calculation of adhesion and friction are presented.

Ferrante, J.↗

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗

Ca + HF - The anatomy of a chemical insertion reaction

A comprehensive first-principles theoretical investigation of the gas phase reaction Ca + HF - CaF + H is reported. Ab initio potential energy calculations are first discussed, along with characteristics of the computed potential energy surface. Next, the fitting of the computed potential energy points to a suitable analytical functional form is described, and maps of the fitted potential surface are displayed. The methodology and results of a classical trajectory calculation utilizing the fitted potential surface are presented. Finally, the significance of the trajectory study results is discussed, and generalizations concerning dynamical aspects of Ca + HF scattering are drawn.

Jaffe, R. L.↗

A first-principles derivation of Doppler noise expected from solar wind density fluctuations

The level of Doppler noise (DN) expected from solar wind (SW) density fluctuations (DF) is derived beginning with the expression for refractive index variations. The calculation takes account of up and downlink paths and of the method actually used to produce the DN values. The usual assumptions that the DF are frozen in, that the large-scale radial variation can be separated from the DF, that the DF power spectrum is a power law with outer scale k sub 0 and that the DF are homogeneous on scales less than 2c delta t, delta t = sample time, are made. The result agrees quite well with previous observations of DN. Corrections for the finite number of points used in the actual algorithm are discussed.

Callahan, P. S.↗

Far-Field Lorenz-Mie Scattering in an Absorbing Host Medium: Theoretical Formalism and FORTRAN Program

In this paper we make practical use of the recently developed first-principles approach to electromagnetic scattering by particles immersed in an unbounded absorbing host medium. Specifically, we introduce an actual computational tool for the calculation of pertinent far-field optical observables in the context of the classical Lorenzâ€"Mie theory. The paper summarizes the relevant theoretical formalism, explains various aspects of the corresponding numerical algorithm, specifies the input and output parameters of a FORTRAN program available at https://www.giss.nasa.gov/staff/mmishchenko/Lorenz-Mie.html, and tabulates benchmark results useful for testing purposes. This public-domain FORTRAN program enables one to solve the following two important problems: (i) simulate theoretically the reading of a remote well-collimated radiometer measuring electromagnetic scattering by an individual spherical particle or a small random group of spherical particles; and (ii) compute the single-scattering parameters that enter the vector radiative transfer equation derived directly from the Maxwell equations.

Far-field electromagnetic scattering; Absorbing ho↗

Equivalent crystal theory of alloys

Equivalent Crystal Theory (ECT) is a new, semi-empirical approach to calculating the energetics of a solid with defects. The theory has successfully reproduced surface energies in metals and semiconductors. The theory of binary alloys to date, both with first-principles and semi-empirical models, has not been very successful in predicting the energetics of alloys. This procedure is used to predict the heats of formation, cohesive energy, and lattice parameter of binary alloys of Cu, Ni, Al, Ag, Au, Pd, and Pt as functions of composition. The procedure accurately reproduces the heats of formation versus composition curves for a variety of binary alloys. The results are then compared with other approaches such as the embedded atom and lattice parameters of alloys from pure metal properties more accurately than Vegard's law is presented.

Bozzolo, Guillermo↗

Investigations on the usefulness of the Massively Parallel Processor for study of electronic properties of atomic and condensed matter systems

The usefulness of the Massively Parallel Processor (MPP) for investigation of electronic structures and hyperfine properties of atomic and condensed matter systems was explored. The major effort was directed towards the preparation of algorithms for parallelization of the computational procedure being used on serial computers for electronic structure calculations in condensed matter systems. Detailed descriptions of investigations and results are reported, including MPP adaptation of self-consistent charge extended Hueckel (SCCEH) procedure, MPP adaptation of the first-principles Hartree-Fock cluster procedure for electronic structures of large molecules and solid state systems, and MPP adaptation of the many-body procedure for atomic systems.

Das, T. P.↗

Dynamics of a Finite Liquid Oxygen (LOX) Column in a Pulsed Magnetic Field

It is well known that liquid oxygen has a sufficient paramagnetic susceptibility that a strong magnetic field gradient can lift it in the earth's gravitational field. The movement of liquid oxygen is vital to the space program since it one of the primary oxidizers used for propulsion. Transport of liquid oxygen (LOX) via direct interaction of the magnetic fields (B field) with the fluid is a current topic of research and development at Kennedy Space Center, FL. This method of transporting (i.e. pumping) LOX may have particular advantages on Mars and other reduced gravitational environments, namely safety and reliability. This paper will address transport of a magnetic fluid, LOX, via phased-pulsed electromagnets acting on the edge of the column of fluid. The authors have developed a physical model from first-principles for the motion of a magnetic fluid in a particular U-tube geometry subjected to a pulsed magnetic field from an arbitrary solenoidal electromagnet. Experimental data that have been collected from the analogous geometry correlate well to that of the ab-initio calculations.

Youngquist, Robert↗

First-Principles Modeling Of Electromagnetic Scattering By Discrete and Discretely Heterogeneous Random Media

A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell- Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of the first principles formalism enabling accurate calculations of monochromatic and quasi-monochromatic scattering by static and randomly varying multiparticle groups. We illustrate how this general framework can be coupled with state-of-the-art computer solvers of the Maxwell equations and applied to direct modeling of electromagnetic scattering by representative random multi-particle groups with arbitrary packing densities. This first-principles modeling yields general physical insights unavailable with phenomenological approaches. We discuss how the first-order-scattering approximation, the radiative transfer theory, and the theory of weak localization of electromagnetic waves can be derived as immediate corollaries of the Maxwell equations for very specific and well-defined kinds of particulate medium. These recent developments confirm the mesoscopic origin of the radiative transfer, weak localization, and effective-medium regimes and help evaluate the numerical accuracy of widely used approximate modeling methodologies.

Michael I Mishchenko↗

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗

GOATS - Orbitology Component

The GOATS Orbitology Component software was developed to specifically address the concerns presented by orbit analysis tools that are often written as stand-alone applications. These applications do not easily interface with standard JPL first-principles analysis tools, and have a steep learning curve due to their complicated nature. This toolset is written as a series of MATLAB functions, allowing seamless integration into existing JPL optical systems engineering modeling and analysis modules. The functions are completely open, and allow for advanced users to delve into and modify the underlying physics being modeled. Additionally, this software module fills an analysis gap, allowing for quick, high-level mission analysis trades without the need for detailed and complicated orbit analysis using commercial stand-alone tools. This software consists of a series of MATLAB functions to provide for geometric orbit-related analysis. This includes propagation of orbits to varying levels of generalization. In the simplest case, geosynchronous orbits can be modeled by specifying a subset of three orbit elements. The next case is a circular orbit, which can be specified by a subset of four orbit elements. The most general case is an arbitrary elliptical orbit specified by all six orbit elements. These orbits are all solved geometrically, under the basic problem of an object in circular (or elliptical) orbit around a rotating spheroid. The orbit functions output time series ground tracks, which serve as the basis for more detailed orbit analysis. This software module also includes functions to track the positions of the Sun, Moon, and arbitrary celestial bodies specified by right ascension and declination. Also included are functions to calculate line-of-sight geometries to ground-based targets, angular rotations and decompositions, and other line-of-site calculations. The toolset allows for the rapid execution of orbit trade studies at the level of detail required for the early stage of mission concept development.

Haber, Benjamin M.↗

The Effects of Magnetic Nozzle Configurations on Plasma Thrusters

Over the course of eight years, the Ohio State University has performed research in support of electric propulsion development efforts at the NASA Lewis Research Center, Cleveland, OH. This research has been largely devoted to plasma propulsion systems including MagnetoPlasmaDynamic (MPD) thrusters with externally-applied, solenoidal magnetic fields, hollow cathodes, and Pulsed Plasma Microthrusters (PPT's). Both experimental and theoretical work has been performed, as documented in four master's theses, two doctoral dissertations, and numerous technical papers. The present document is the final report for the grant period 5 December 1987 to 31 December 1995, and summarizes all activities. Detailed discussions of each area of activity are provided in appendices: Appendix 1 - Experimental studies of magnetic nozzle effects on plasma thrusters; Appendix 2 - Numerical modeling of applied-field MPD thrusters; Appendix 3 - Theoretical and experimental studies of hollow cathodes; and Appendix 4 -Theoretical, numerical and experimental studies of pulsed plasma thrusters. Especially notable results include the efficacy of using a solenoidal magnetic field downstream of a plasma thruster to collimate the exhaust flow, the development of a new understanding of applied-field MPD thrusters (based on experimentally-validated results from state-of-the art, numerical simulation) leading to predictions of improved performance, an experimentally-validated, first-principles model for orificed, hollow-cathode behavior, and the first time-dependent, two-dimensional calculations of ablation-fed, pulsed plasma thrusters.

Turchi, P. J.↗