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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

A study of microkinetic adjustments required to match shock wave experiments and Monte Carlo Direct Simulation for a wide Mach number range

Shock wave thickness predictions from Monte Carlo Direct Simulations, using differential scattering and the Maitland-Smith-Aziz interatomic potential, underpredict experiments as shock Mach numbers increase above about 4. Examination of several sources of data has indicated that at relatively high energies the repulsive portion of accepted potentials such as the Maitland-Smith-Aziz may be too steep. An Exponential-6 potential due to Ross, based on high energy molecular beam scattering data and shock velocity measurements in liquid argon, has been combined with the lower energy portion of the Maitland-Smith-Aziz potential. When this hybrid potential is used in Monte Carlo Direct Simulations, agreement with experiments is improved over the previous predictions using the pure Maitland-Smith-Aziz form.

Pham-Van-diep, Gerald C.↗
NASA NTRS1991

Nonequilibrium gas flows. I - A detailed validation of Monte Carlo direct simulation for monatomic gases

One-dimensional shock wave properties in helium and argon are predicted using Monte Carlo direct simulation. The collision model is based directly on the interatomic potential taking angular scattering into account. The potential is assumed to be of the Maitland-Smith n(r)-6 form. The detailed validity of the simulation is studied by comparing the predicted macroscopic and miroscopic flow properties in shock waves to a wide range of available data.

Erwin, Daniel A.↗
NASA NTRS1993

A laser-cooled cesium fountain frequency standard and a measurement of the frequency shift due to ultra-cold collisions

A frequency standard based on an atomic fountain of cesium atoms may have an accuracy of 10(exp -16) due to longer interaction times and smaller anticipated systematic errors. All of the known systematic effects that now limit the accuracy of the Cs frequency standard increase either linearly or as some higher power of the atom's velocity. The one systematic frequency shift which is dramatically different is the frequency shift due to the collisions between the laser cooled atoms. At a temperature of a few micro-K, the de Broglie wavelength (lambda(sub deB) = h/p, where h is Planck's constant and p is the momentum of the atom) is much larger than the scale of the interatomic potential. Under these conditions the collision cross sections can be as large as (lambda(sub deB)(sup 2))/Pi and the frequency shift due to these collisions was recently calculated. In our Cs atomic fountain, we laser cooled and trapped 10(exp 10) Cs atoms in 0.4 s. By shifting the frequencies of the laser beams, the atoms were launched upwards at 2.5 m/s and a fraction of the atoms were optically pumped into the F=3 ground state. The unwanted atoms in the F=4 ground state were removed from the fountain with radiation pressure from a laser beam tuned to excite only those atoms. The Cs atoms in the F=3 state traveled ballistically upwards, were excited by the microwave cavity, and then returned back through the same cavity in the atomic fountain configuration. By varying the cold atom density, a density dependent shift of -12.9 +/- 0.7 mHz or -1.4 x 10-12 for an average fountain density of (2.7 +/- 1.5) 10(exp 9) atoms/cm(sup 3) was measured.

Gibble, Kurt↗
NASA NTRS1993

Evaporation kinetics of Mg2SiO4 crystals and melts from molecular dynamics simulations

Computer simulations based on the molecular dynamics (MD) technique were used to study the mechanisms and kinetics of free evaporation from crystalline and molten forsterite (i.e., Mg2SiO4) on an atomic level. The interatomic potential employed for these simulations reproduces the energetics of bonding in forsterite and in gas-phase MgO and SiO2 reasonably accurately. Results of the simulation include predicted evaporation rates, diffusion rates, and reaction mechanisms for Mg2SiO4(s or l) yields 2Mg(g) + 20(g) + SiO2(g).

Kubicki, J. D.↗
NASA NTRS2000

The Rotational Spectra of IO X(sub 1) (sup 2)pi(sub 3/2), v <= 13 and X(sub 2) (sup 2)pi(sub 1/2), v <= 9

The rotational spectra of IO in vibrational states up to v = 13 in the X(sub 1) (sup 2)pi(sub 3/2) state and up to v = 9 in the X2 (sup 2)pi(sub 1/2) state have been observed in an O2 discharge over molecular I2. In addition, I(18)O has been observed for both the X(sub 1) and X(sub 2) states up to v = 5. All data have been analyzed simultaneously with fixed isotopic ratios among the constants. This extends the data set for the X(sub 1) state described last year at this meeting and provides the first high resolution data for the X(sub 2) state and for I(18)O. An extensive set of parameters has been derived. These will be interpreted in terms of the electronic structure and the interatomic potential.

Miller, Charles E.↗
NASA NTRS2000

Sputtering Erosion in the Ion Thruster

During the first phase of this research, the sputtering yields of molybdenum by low energy (100 eV and higher) xenon ions were measured by using the methods of secondary neutral mass spectrometry (SNMS) and Rutherford backscattering spectrometry (RBS). However, the measured sputtering yields were found to be far too low to explain the sputtering erosions observed in the long-duration tests of ion thrusters. The only difference between the sputtering yield measurement experiments and the ion thruster tests was that the later are conducted at high ion fluences. Hence, a study was initiated to investigate if any linkage exists between high ion fluence and an enhanced sputtering yield. The objective of this research is to gain an understanding of the causes of the discrepancies between the sputtering rates of molybdenum grids in an ion thruster and those measured from our experiments. We are developing a molecular dynamics simulation technique for studying low-energy xenon ion interactions with molybdenum. It is difficult to determine collision sequences analytically for primary ions below the 200 eV energy range where the ion energy is too low to be able to employ a random cascade model with confidence and it is too high to have to consider only single collision at or near the surface. At these low energies, the range of primary ions is about 1 to 2 nm from the surface and it takes less than 4 collisions on the average to get an ion to degrade to such an energy that it can no longer migrate. The fine details of atomic motion during the sputtering process are revealed through computer simulation schemes. By using an appropriate interatomic potential, the positions and velocities of the incident ion together with a sufficient number of target atoms are determined in small time steps. Hence, it allows one to study the evolution of damages in the target and its effect on the sputtering yield. We are at the preliminary stages of setting up the simulation program.

Ray, Pradosh K.↗
NASA NTRS2011

Lattice Thermal Conductivity of Ultra High Temperature Ceramics ZrB2 and HfB2 from Atomistic Simulations

Atomistic Green-Kubo simulations are performed to evaluate the lattice thermal conductivity for single crystals of the ultra high temperature ceramics ZrB2 and HfB2 for a range of temperatures. Recently developed interatomic potentials are used for these simulations. Heat current correlation functions show rapid oscillations which can be identified with mixed metal-Boron optical phonon modes. Agreement with available experimental data is good.

Lawson, John W.↗
NASA NTRS2011

Lattice Thermal Conductivity of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2 from Atomistic Simulations

Ultra high temperature ceramics (UHTC) including ZrB2 and HfB2 are candidate materials for applications in extreme environments because of their high melting point, good mechanical properties and reasonable oxidation resistance. Unlike many ceramics, these materials have high thermal conductivity which can be advantageous, for example, to reduce thermal shock. Recently, we developed Tersoff style interatomic potentials for both ZrB2 and HfB2 appropriate for atomistic simulations. As an application, Green-Kubo molecular dynamics simulations were performed to evaluate the lattice thermal conductivity for single crystals of ZrB2 and HfB2. The atomic mass difference in these binary compounds leads to oscillations in the time correlation function of the heat current. Results at room temperature and at elevated temperatures will be reported.

Lawson, JOhn W.↗
NASA NTRS2012

Multiscale Modeling of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2: Application to Lattice Thermal Conductivity

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Lawson, John W.↗
NASA NTRS2012

Multiscale Modeling of UHTC: Thermal Conductivity

We are developing a multiscale framework in computational modeling for the ultra high temperature ceramics (UHTC) ZrB2 and HfB2. These materials are characterized by high melting point, good strength, and reasonable oxidation resistance. They are candidate materials for a number of applications in extreme environments including sharp leading edges of hypersonic aircraft. In particular, we used a combination of ab initio methods, atomistic simulations and continuum computations to obtain insights into fundamental properties of these materials. Ab initio methods were used to compute basic structural, mechanical and thermal properties. From these results, a database was constructed to fit a Tersoff style interatomic potential suitable for atomistic simulations. These potentials were used to evaluate the lattice thermal conductivity of single crystals and the thermal resistance of simple grain boundaries. Finite element method (FEM) computations using atomistic results as inputs were performed with meshes constructed on SEM images thereby modeling the realistic microstructure. These continuum computations showed the reduction in thermal conductivity due to the grain boundary network.

Lawson, John W.↗
NASA NTRS2012

Lattice Thermal Conductivity from Atomistic Simulations: ZrB2 and HfB2

Ultra high temperature ceramics (UHTC) including ZrB2 and HfB2 have a number of properties that make them attractive for applications in extreme environments. One such property is their high thermal conductivity. Computational modeling of these materials will facilitate understanding of fundamental mechanisms, elucidate structure-property relationships, and ultimately accelerate the materials design cycle. Progress in computational modeling of UHTCs however has been limited in part due to the absence of suitable interatomic potentials. Recently, we developed Tersoff style parameterizations of such potentials for both ZrB2 and HfB2 appropriate for atomistic simulations. As an application, Green-Kubo molecular dynamics simulations were performed to evaluate the lattice thermal conductivity for single crystals of ZrB2 and HfB2. The atomic mass difference in these binary compounds leads to oscillations in the time correlation function of the heat current, in contrast to the more typical monotonic decay seen in monoatomic materials such as Silicon, for example. Results at room temperature and at elevated temperatures will be reported.

Lawson, John W.↗
NASA NTRS2012

Lattice Thermal Conductivity of Ultra High Temperature Ceramics (UHTC) ZrB2 and HfB2 from Atomistic Simulations

Ultra high temperature ceramics (UHTC) including ZrB2 and HfB2 have a number of properties that make them attractive for applications in extreme environments. One such property is their high thermal conductivity. Computational modeling of these materials will facilitate understanding of fundamental mechanisms, elucidate structure-property relationships, and ultimately accelerate the materials design cycle. Progress in computational modeling of UHTCs however has been limited in part due to the absence of suitable interatomic potentials. Recently, we developed Tersoff style parameterizations of such potentials for both ZrB2 and HfB2 appropriate for atomistic simulations. As an application, Green-Kubo molecular dynamics simulations were performed to evaluate the lattice thermal conductivity for single crystals of ZrB2 and HfB2. The atomic mass difference in these binary compounds leads to oscillations in the time correlation function of the heat current, in contrast to the more typical monotonic decay seen in monoatomic materials such as Silicon, for example. Results at room temperature and at elevated temperatures will be reported.

Lawson, John W.↗
NASA NTRS2017

The Statistical Mechanics of Solar Wind Hydroxylation at the Moon, Within Lunar Magnetic Anomalies, and at Phobos

We present a new formalism to describe the outgassing of hydrogen initially implanted by the solar wind protons into exposed soils on airless bodies. The formalism applies a statistical mechanics approach similar to that applied recently to molecular adsorption onto activated surfaces. The key element enabling this formalism is the recognition that the interatomic potential between the implanted H and regolith-residing oxides is not of singular value but possess a distribution of trapped energy values at a given temperature, F(U,T). All subsequent derivations of the outward diffusion and H retention rely on the specific properties of this distribution. We find that solar wind hydrogen can be retained if there are sites in the implantation layer with activation energy values exceeding 0.5eV. We especially examine the dependence of H retention applying characteristic energy values found previously for irradiated silica and mature lunar samples. We also apply the formalism to two cases that differ from the typical solar wind implantation at the Moon. First, we test for a case of implantation in magnetic anomaly regions where significantly lower-energy ions of solar wind origin are expected to be incident with the surface. In magnetic anomalies, H retention is found to be reduced due to the reduced ion flux and shallower depth of implantation. Second, we also apply the model to Phobos where the surface temperature range is not as extreme as the Moon. We find the H atom retention in this second case is higher than the lunar case due to the reduced thermal extremes (that reduces outgassing).

Solar Wind↗
NASA NTRS2016

Influence of Molecular Simulation Model Accuracy on the Interfacial Properties of an Ionic Liquid: Overview of Recommended Practices

Increasing the energy storage capability of ionic liquid supercapacitors will require better understanding of ion-electrode interactions. We have probed the influence of these interactions on the structure and differential capacitance of of an ionic liquid ([EMIM][BF4]) at an ideal graphite interface as a function of model accuracy. Of note, differential capacitance is determined through newly derived and validated fluctuation formulas. In terms of model accuracy, we test electrostatic techniques, electrode charging techniques, and electrolyte interatomic potentials. For electrostatic summations, we employ high cost, high fidelity techniques as well as less expensive, approximate techniques for summation in slab geometry. For electrode charging, uniform, constant-charge and environmentally responsive, constant-potential conditions are employed. For the ionic liquid, constant charge and atomically polarizable models are employed. We comment on the role of model accuracy on the structure and energetics of the electric double layer as well as on the magnitude and shape of differential capacitance.

simulations↗
NASA NTRS2019

Physically-Informed Artificial Neural Networks for Atomistic Modeling of Materials

A new approach is presented for the development of classical interatomic potentials using physically-informed neural networks (PINN) combined with an analytical bond-order atomic interaction model. Due to the strong physical underpinnings, the PINN potentials demonstrate much better transferability than the existing machine-learning potentials while drastically improving the accuracy in comparison with traditional potentials. PINN potentials can be constructed for both metallic and covalent materials in a unified manner. A number of applications of PINN potentials to large-scale molecular dynamics and Monte Carlo simulations and calculation of thermal and mechanical properties of diverse materials are demonstrated. Some of the specific materials systems include silicon and aluminum, as well as alloys and compounds. Computational aspects of PINN potentials are discussed and future developments in this field are outlined.

J Hickman↗
NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗
DOE OSTI2025

Self-Learning Kinetic Monte Carlo Simulations of Radiation Damage in Nuclear Fuels

Understanding how irradiation affects the thermo-physical and mechanical properties of nuclear materials, such as thermal conductivity degradation in fuels and embrittlement of structural components, is critical to the safety and efficiency of nuclear reactors. These effects are largely governed by the formation and evolution of atomic-scale point defects and defect clusters. Due to their small sizes, however, these defects are invisible under high-resolution scanning transmission electron microscopy. This project aims to fill this experimental knowledge gap by integrating density functional theory (DFT), machine learning interatomic potential (MLIP), and kinetic Monte Carlo (KMC) techniques to predict longtime evolution of irradiation-induced defects in nuclear fuels.

36 - MATERIALS SCIENCE↗