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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Ab Initio and Improved Empirical Potentials for the Calculation of the Anharmonic Vibrational States and Intramolecular Mode Coupling of N-Methylacetamide

The second-order Moller-Plesset ab initio electronic structure method is used to compute points for the anharmonic mode-coupled potential energy surface of N-methylacetamide (NMA) in the trans(sub ct) configuration, including all degrees of freedom. The vibrational states and the spectroscopy are directly computed from this potential surface using the Correlation Corrected Vibrational Self-Consistent Field (CC-VSCF) method. The results are compared with CC-VSCF calculations using both the standard and improved empirical Amber-like force fields and available low temperature experimental matrix data. Analysis of our calculated spectroscopic results show that: (1) The excellent agreement between the ab initio CC-VSCF calculated frequencies and the experimental data suggest that the computed anharmonic potentials for N-methylacetamide are of a very high quality; (2) For most transitions, the vibrational frequencies obtained from the ab initio CC-VSCF method are superior to those obtained using the empirical CC-VSCF methods, when compared with experimental data. However, the improved empirical force field yields better agreement with the experimental frequencies as compared with a standard AMBER-type force field; (3) The empirical force field in particular overestimates anharmonic couplings for the amide-2 mode, the methyl asymmetric bending modes, the out-of-plane methyl bending modes, and the methyl distortions; (4) Disagreement between the ab initio and empirical anharmonic couplings is greater than the disagreement between the frequencies, and thus the anharmonic part of the empirical potential seems to be less accurate than the harmonic contribution;and (5) Both the empirical and ab initio CC-VSCF calculations predict a negligible anharmonic coupling between the amide-1 and other internal modes. The implication of this is that the intramolecular energy flow between the amide-1 and the other internal modes may be smaller than anticipated. These results may have important implications for the anharmonic force fields of peptides, for which N-methylacetamide is a model.

Gregurick, Susan K.↗
NASA NTRS2016

Comparison of Quantum Mechanical and Empirical Potential Energy Surfaces and Computed Rate Coefficients for N2 Dissociation

Comparisons are made between potential energy surfaces (PES) for N2 + N and N2 + N2 collisions and between rate coefficients for N2 dissociation that were computed using the quasiclassical trajectory method (QCT) on these PESs. For N2 + N we compare the Laganas empirical LEPS surface with one from NASA Ames Research Center based on ab initio quantum chemistry calculations. For N2 + N2 we compare two ab initio PESs (from NASA Ames and from the University of Minnesota). These use different methods for computing the ground state electronic energy for N4, but give similar results. Thermal N2 dissociation rate coefficients, for the 10,000K-30,000K temperature range, have been computed using each PES and the results are in excellent agreement. Quasi-stationary state (QSS) rate coefficients using both PESs have been computed at these temperatures using the Direct Molecular Simulation of Schwartentruber and coworkers. The QSS rate coefficients are up to a factor of 5 lower than the thermal ones and the thermal and QSS values bracket the results of shock-tube experiments. We conclude that the combination of ab initio quantum chemistry PESs and QCT calculations provides an attractive approach for the determination of accurate high-temperature rate coefficients for use in aerothermodynamics modeling.

quasiclassical trajectory method↗
NASA NTRS2016

Comparison of Quantum Mechanical and Empirical Potential Energy Surfaces and Computed Rate Coefficients for N2 Dissociation

Physics-based modeling of hypersonic flows is predicated on the availability of chemical reaction rate coefficients and cross sections for the collisional processes. This approach has been built around the use of quantum mechanical calculations to describe the interaction between the colliding particles. In this approach a potential energy surface (PES) is computed by solving the electronic Schrödinger equation and collision cross sections are determined for that PES using classical, semiclassical or quantum mechanical scattering methods. The rate coefficients are computed by integrating the thermally weighted cross sections. State-to-state rate coefficients are determined by only integrating over a thermal distribution of collisional energies. Finally, thermal rate coefficients are determined by summation of the state-to-state rate coefficients for reactions of molecules in all relevant ro-vibrational energy levels. If the flow is in thermal non-equilibrium, the translational, vibrational and rotational energy modes can be represented in different ways: three unique temperatures can be used to describe the distributions, the populations of individual ro-vibrational energy levels can be determined by solving the Master Equation, or through the use of direct simulation in particle-based Monte Carlo sampling. The PES-to-rate coefficient approach had been proposed and attempted in the early days of digital computing, but it is only in the last 15 years that computer hardware and software have been up to the task of calculating accurate interatomic and intermolecular potentials.

Jaffe, Richard L.↗
NASA NTRS1979

Close-coupling calculations with an INDOX/1s static potential, semiclassical exchange, and a semi-empirical polarisation potential for electron-CO2 elastic scattering and rotational excitation

A semiempirical molecular-orbital method for modelling the effective potential for electron-molecule scattering is applied to elastic scattering and rotational excitation of CO2 at 20 eV impact energy. Agreement with experiment is reasonably good. The calculated rotationally summed integral cross section is 67.8 a sub 0 squared.

Onda, K.↗
NASA NTRSDate not supplied

Semi-Empirical Interatomic Potential for Large-Scale Molecular Dynamics Simulation of Metal-Oxide Systems

Classical molecular dynamics (MD) simulation can be applied to systems containing billions of atoms during times up to microseconds. However, utilization of a large-scale MD simulation requires reliable but computationally cheap interatomic potentials. In the case of metallic systems, embedded atom method (EAM) and Finnis-Sinclair (FS) potentials are the reasonable choices, but their development for multicomponent alloys is a challenge. Addition of oxygen atoms makes the problem of developing semi-empirical potentials even more difficult because the long-range Coulomb interaction cannot be neglected, and different atoms have different charges which vary during MD relaxation such that a charge equilibration procedure should be applied every MD step. As results researchers tend to avoid simulating metal-oxide systems. In this talk, a new Finnis-Sinclair (FS) Ni-Co-Cr potential will be presented. Special attention will be paid to reproducing of the element melting temperatures and clustering. Next, a charge transfer ionic potential (CTIP) developed to simulate the NiO properties will be presented. This potential utilizes the Ni FS potential and accounts for the Coulomb interaction in the vicinity of oxygen atoms. Fitting of the CTIP parameters and FS potential functions describing the interaction with oxygen atoms to the available experimental and ab initio data will be discussed. Results of MD simulation of interaction of NiO particles with dislocations in Ni will be shown.

molecular dynamics simulation↗
NASA NTRSDate not supplied

Molecular dynamics simulation of effects of solutes on dislocation propagation in Ni-based superalloys

Ni-based superalloys are used in the hot sections of jet turbine engines because of their high strength, stability and resistance to oxidation. The properties of these alloys can be further optimized by adding alloying elements. Therefore, a fundamental knowledge on the effect of different elements on properties of Ni-based superalloys is required. Molecular dynamics simulation could shed light here but its application is hindered by the absence of reliable and computationally cheap semi-empirical potential of the interatomic interaction for 4 and more element alloys. We will present a new Ni-Al-Cr-Nb Finnis-Sinclair (FS) potential specially designed to simulate the dislocation propagation from to  phase. In order to construct this potential, we designed a special algorithm to incorporate the data on element partitioning in the potential development procedure. For example, it is known from experiment, that Cr is mostly present in the gamma phase. Figure 1 shows a snapshot obtained after equilibration of the model of the Ni68Al17Cr15 alloy at T=1000 K using the hybrid Monte-Carlo (MC)/molecular dynamics (MD) simulation with the developed semi-empirical potential. One can clearly see that the Cr partitioning is in agreement with the experimental data. We will discuss the developed algorithm to incorporate the solute partition data in details. Using the developed semi-empirical potential, we first investigated the effect of anti-site defects in the  phase on the single dislocation propagation. It was found that the dislocation velocity increases with the increasing of the anti-site defect concentration. This effect was attributed to smaller number of Al-Al pairs forming during the dislocation migration in the presence of the anti-site defects. Next, we investigated the effect of Nb on the dislocation pair propagation in the Kolbe mechanism. It was found that the addition of Nb leads to considerable decrease in the dislocation propagation rate. This is in agreement with the experimental data on the effect of Nb on the creep resistance of the Ni-based superalloys. We will discuss the origin of this effect.

Mikhail I. Mendelev↗
NASA NTRS1972

Model potential calculations of lithium transitions.

Semi-empirical potentials are constructed that have eigenvalues close in magnitude to the binding energies of the valence electron in lithium. The potentials include the long range polarization force between the electron and the core. The corresponding eigenfunctions are used to calculate dynamic polarizabilities, discrete oscillator strengths, photoionization cross sections and radiative recombination coefficients. A consistent application of the theory imposes a modification on the transition operator, but its effects are small for lithium. The method presented can be regarded as a numerical generalization of the widely used Coulomb approximation.

Caves, T. C.↗
NASA NTRS1980

Dislocation dissociation in some f.c.c. metals

The dissociation of a perfect screw dislocation into a stacking fault in an f.c.c. lattice is modeled by the modified lattice statics. The interatomic potentials are obtained from the work of Esterling and Swaroop and differ substantially from those empirical potentials usually employed in defect simulations. The calculated stacking fault widths for aluminum, copper, and silver are in good agreement with weak beam microscopy results.

Esterling, D. M.↗
NASA NTRS1986

Theoretical study of the 7Sigma(u)+ state of N2

Theoretical potentials for the 7Sigma(u)+ state are reported using both extended Slater and Gaussian basis sets. Electron correlation is included using the interacting correlated fragments (ICF), the singles plus doubles configuration-interaction (SDCI), and the coupled-pair functional (CPF) approaches. The best potential, corrected for basis set superposition errors, has a well depth of about 21/cm and an r(e) of 7.52 bohr. The inclusion of the nitrogen 2s correlation significantly increases the well depth. These results are in reasonably good agreement with the empirical potential of Ferrante and Stwalley (1983), and support the contention that spin-polarized atomic nitrogen should behave like a classical solid such as Ne. It is shown that the modified Buckingham potential used by Ferrante and Stwalley is consistent with the present ab initio potentials if smaller values are used for the dispersion coefficients of the nitrogen atom.

Partridge, H.↗
NASA NTRSDate not supplied

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗
NASA NTRSDate not supplied

Hierarchical Screening for Li-Based Solid Electrolytes Using Fast, Interpretable Machine-Learned Potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates.

Materials discovery↗
NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗
NASA NTRS1978

Calculated rate constants for the reaction ClO + O yields Cl + O2 between 220 and 1000 deg K

Classical trajectory calculations are presented for the reaction ClO + O yields Cl + O2, a reaction which is an important step in the chlorine-catalyzed destruction of ozone which is thought to occur in the 220 and 1000 K. The calculated rate constant is 4.36 x 10 to the minus 11th power exp (-191/T)cu cm molecule (-1)s(-1) and its value at 300 K is 2.3 plus or minus 10 to the 11th power cu cm molecule (-1)s(-1), about a factor of 2 lower than recent experimental data. The empirical potential energy surface used in the calculations was constructed to fit experimental data for ClO, O2 and ClOO molecules. Other important features of this potential surface, such as the barrier to reaction, were varied systematically and calculations were performed for a range of conditions to determine the best theoretical rate constants. Results demonstrate the utility of classical trajectory methods for determining activation energies and other kinetic data for important atmospheric reactions.

Jaffee, R. L.↗
NASA NTRS1988

Simulation studies for surfaces and materials strength

During this six month period of the Simulation Studies for Surfaces and Materials Strength program investigations were carried out in two general areas: (1) Energy barriers and structural transitions between isomers of small Al clusters were investigated. In this study an empirical potential function which was parametrized based on accurate first principle results was employed; (2) A comparative study was conducted to investigate the applicability of most commonly employed model potential functions in calculating various bulk, surface and small cluster properties.

Halicioglu, Timur↗
NASA NTRS1997

Carbon Nanotubules: Building Blocks for Nanometer-Scale Engineering

Proximal probe technology has provided researchers with new ways to investigate and manipulate matter on the nanometer scale. We have studied, through molecular dynamics simulations, using a many-body empirical potential, the indentation of a hydrogen-terminated, diamond (111 ) surface, with a proximal probe tip that consists of an open, hydrogen-terminated, (10,10) carbon nanotubule. The simulations showed that upon indenting 1.8 A, the tubule deforms but returns to its original shape upon retraction. The Young's modulus of the tubule was determined using the predicted Euler buckling force and was found to be comparable to measured and calculated values. In a second series of simulations, an open (10, 10) nanotubule was heated to 4500 K and allowed to close. We find that at this temperature the resulting cap contains numerous imperfections, including some not mentioned previously in the literature.

Sinnott, Susan B.↗
NASA NTRS1998

Modeling of Branched (L, T and Y) Carbon Nanotubes

Models for connecting two or three carbon nanotubes (CNT) using topological defects (i.e., pentagons and heptagons) are presented for the characterization of experimentally observed L, T and Y CNT junctions. The effects of the separation and orientation of the topological defects on the structures and energetics of these junctions are investigated using the nonlocal density function theory (DFT) and semi-empirical molecular orbital (AM1) calculations, and the Brenner empirical potential molecular mechanics simulations. The potential applications of L, Y and T CNT junctions in nanoelectronic devices are also discussed.

Han, Jie↗