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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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52 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Effects of Structural Deformation and Tube Chirality on Electronic Conductance of Carbon Nanotubes

A combination of large scale classical force-field (UFF), density functional theory (DFT), and tight-binding Green's function transport calculations is used to study the electronic properties of carbon nanotubes under the twist, bending, and atomic force microscope (AFM)-tip deformation. We found that in agreement with experiment a significant change in electronic conductance can be induced by AFM-tip deformation of metallic zigzag tubes and by twist deformation of armchair tubes. The effect is explained in terms of bandstructure change under deformation.

Svizhenko, Alexei↗
NASA NTRS2014

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Supercomputing↗
NASA NTRS1999

Computational Study of Field Initiated Surface Reactions for Synthesis of Diamond and Silicon

This project involves using quantum chemistry to simulate surface chemical reactions in the presence of an electric field for nanofabrication of diamond and silicon. A field delivered by a scanning tunneling microscope (STM) to a nanometer scale region of a surface affects chemical reaction potential energy surfaces (PES) to direct atomic scale surface modification to fabricate sub-nanometer structures. Our original hypothesis is that the applied voltage polarizes the charge distribution of the valence electrons and that these distorted molecular orbitals can be manipulated with the STM so as to change the relative stabilities of the electronic configurations over the reaction coordinates and thus the topology of the PES and reaction kinetics. Our objective is to investigate the effect of applied bias on surface reactions and the extent to which STM delivered fields can be used to direct surface chemical reactions on an atomic scale on diamond and silicon. To analyze the fundamentals of field induced chemistry and to investigate the application of this technique for the fabrication of nanostructures, we have employed methods capable of accurately describing molecular electronic structure. The methods we employ are density functional theory (DFT) quantum chemical (QC) methods. To determine the effect of applied bias on surface reactions we have calculated the QC PESs in various applied external fields for various reaction steps for depositing or etching diamond and silicon. We have chosen reactions which are thought to play a role in etching and the chemical vapor deposition growth of Si and diamond. The PESs of the elementary reaction steps involved are then calculated under the applied fields, which we vary in magnitude and configuration. We pay special attention to the change in the reaction barriers, and transition state locations, and search for low energy reaction channels which were inaccessible without the applied bias.

Musgrave, Charles Bruce↗
NASA NTRS1996

The Application B3LYP to Large Systems

The application of density functional theory (DFT), using the B3LYP functional, to a series of chemical problems is described. The first involves the calculation of silica-adsorbate bond energies, including both chemical bonds and weak hydrogen bonding. The calculation of vibrational frequencies for large organic systems is discussed. For the closed shell neutral systems, the B3LYP results are similar to the self- consistent- field results, however, for the positive ions, only the B3LYP level of theory is accurate and sufficiently inexpensive to allow the study of large systems. The final application involves the calculation of successive metal-ligand bond energies. The B3LYP bond energies and entropies are shown to be in good agreement with experiment.

Bauschlicher, Charles W.↗
NASA NTRS1994

On the Interaction of CO and NH3 with BH3 and BF3

BH3CO, BF3CO, BH3NH3, and BF3NH3 have been studied using density functional theory (DFT). The computed geometries are in reasonable agreement with experiment. BF3CO is found to be weakly bound. The binding energies of BH3CO, BH3NH3 , and BF3NH3 have also been computed using the coupled cluster singles and doubles level of theory, including a perturbational estimate of the connected triples [CCSD(T)]. These CCSD(T) calculations are performed using correlation consistent polarized-valence triple-zeta basis sets. These are expected to be the most accurate binding energies to date. The DFT binding energies are in good agreement with those obtained at the CCSD(T) level. The bonding is analyzed using the constrained space orbital variation (CSOV) technique. In addition to analyzing the bonding in BH3CO, BH3NH3, and BF3NH3, the CSOV approach is used to study why the bonding in BF3CO is so weak.

Bauschlicher, Charles W., Jr.↗
NASA NTRS1996

Chemistry by Way of Density Functional Theory

In this work we demonstrate that density functional theory (DFT) methods make an important contribution to understanding chemical systems and are an important additional method for the computational chemist. We report calibration calculations obtained with different functionals for the 55 G2 molecules to justify our selection of the B3LYP functional. We show that accurate geometries and vibrational frequencies obtained at the B3LYP level can be combined with traditional methods to simplify the calculation of accurate heats of formation. We illustrate the application of the B3LYP approach to a variety of chemical problems from the vibrational frequencies of polycyclic aromatic hydrocarbons to transition metal systems. We show that the B3LYP method typically performs better than the MP2 method at a significantly lower computational cost. Thus the B3LYP method allows us to extend our studies to much larger systems while maintaining a high degree of accuracy. We show that for transition metal systems, the B3LYP bond energies are typically of sufficient accuracy that they can be used to explain experimental trends and even differentiate between different experimental values. We show that for boron clusters the B3LYP energetics are not as good as for many of the other systems presented, but even in this case the B3LYP approach is able to help understand the experimental trends.

Bauschlicher, Charles W., Jr.↗
NASA NTRS2001

Electronic Transport Through Carbon Nanotubes: Effects of Structural Deformation and the Tube Chirality

Atomistic simulations using a combination of classical force field and Density-Functional-Theory (DFT) show that carbon atoms remain essentially sp2 coordinated in either bent tubes or tubes pushed by an atomically sharp AFM tip. Subsequent Green's-function-based transport calculations reveal that for armchair tubes there is no significant drop in conductance, while for zigzag tubes the conductance can drop by several orders of magnitude in AFM-pushed tubes. The effect can be attributed to simple stretching of the tube under tip deformation, which opens up an energy gap at the Fermi surface.

Maiti, Amitesh↗
NASA NTRS2021

Sulfur Molecules in Space by X-rays: A Computational Study

X-ray astronomy lacks high resolution spectra of interstellar dust analogues and molecules, severely hampering interstellar medium studies based on upcoming X-ray missions. Various theoretical approaches may be used to address this problem, but they must first be shown to reproduce reliable spectra compared to the experiment. In this work, we calculate the sulfur Kedge X-ray absorption spectra of H2S, SO2, and OCS, whose spectra are already known from X-ray experiments and predict the X-ray spectrum of CS, which as far as we are aware has not been measured, thereby hampering its detection by X-ray telescopes. We chose these four molecules as the astrochemistry of sulfur is an unsolved problem and as the four molecules are already known to exist in space. We consider three types of methods for modeling the X-ray spectra: more accurate calculations with the algebraic-diagrammatic construction (ADC) and the CC2, CCSD, and CC3coupled cluster (CC) approaches as well as more affordable ones with transition potential density functional theory (TP-DFT). A comparison of our computational results to previously reported experimental spectra shows that the core−valence separation (CVS)approaches CVS-ADC(2)-x and CVS-CC3 generally yield a good qualitative level of agreement with the experiment, suggesting that they can be used for interpreting measured spectra, while the TP-DFT method is not reliable for these molecules. However, quantitative agreement with the experiment is still outside the reach of the computational methods studied in this work.

Goranka Bilalbegovic↗
NASA NTRS1996

The Calculation of Accurate Harmonic Frequencies of Large Molecules: The Polycyclic Aromatic Hydrocarbons, a Case Study

The vibrational frequencies and infrared intensities of naphthalene neutral and cation are studied at the self-consistent-field (SCF), second-order Moller-Plesset (MP2), and density functional theory (DFT) levels using a variety of one-particle basis sets. Very accurate frequencies can be obtained at the DFT level in conjunction with large basis sets if they are scaled with two factors, one for the C-H stretches and a second for all other modes. We also find remarkably good agreement at the B3LYP/4-31G level using only one scale factor. Unlike the neutral PAHs where all methods do reasonably well for the intensities, only the DFT results are accurate for the PAH cations. The failure of the SCF and MP2 methods is caused by symmetry breaking and an inability to describe charge delocalization. We present several interesting cases of symmetry breaking in this study. An assessment is made as to whether an ensemble of PAH neutrals or cations could account for the unidentified infrared bands observed in many astronomical sources.

Bauschlicher, Charles W., Jr.↗
NASA NTRS1985

Maintenance of Time and Frequency in the DSN Using the Global Positioning System

The Deep Space Network must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. The DSN has three tracking complexes, located approximately equidistantly around the Earth. Various methods are used to coordinate the clocks among the three complexes. These methods include Loran-C, TV Line 10, very long baseline interferometry (VLBI), and the Global Positioning System (GPS). The GPS is becoming increasingly important because of the accuracy, precision, and rapid availability of the data; GPS receivers have been installed at each of the DSN complexes and are used to obtain daily time offsets between the master clock at each site and UTC(USNO/NBS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN frequency and timing system (DFT). A brief history of the GPS timing receivers in the DSN, a description of the data and information flow, data on the performance of the DSN master clocks and GPS measurement system, and a description of hydrogen maser frequency steering using these data are presented.

Clements, P. A.↗
NASA NTRS1984

Maintenance of time and frequency in the Jet Propulsion Laboratory's Deep Space Network using the Global Positioning System

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. Various methods are used to coordinate the clocks among the three tracking complexes. These methods include Loran-C, TV Line 10, Very Long Baseline Interferometry (VLBI), and the Global Positioning System (GPS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN Frequency and Timing System (DFT). Areas of discussion are: (1) a brief history of the GPS timing receivers in the DSN, (2) a description of the data and information flow, (3) data on the performance of the DSN master clocks and GPS measurement system, and (4) a description of hydrogen maser frequency steering using these data.

Clements, P. A.↗
NASA NTRS1993

Cramer-Rao Bound for Gaussian Random Processes and Applications to Radar Processing of Atmospheric Signals

Calculations of the exact Cramer-Rao Bound (CRB) for unbiased estimates of the mean frequency, signal power, and spectral width of Doppler radar/lidar signals (a Gaussian random process) are presented. Approximate CRB's are derived using the Discrete Fourier Transform (DFT). These approximate results are equal to the exact CRB when the DFT coefficients are mutually uncorrelated. Previous high SNR limits for CRB's are shown to be inaccurate because the discrete summations cannot be approximated with integration. The performance of an approximate maximum likelihood estimator for mean frequency approaches the exact CRB for moderate signal to noise ratio and moderate spectral width.

Frehlich, Rod↗
NASA NTRS2023

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↗
NASA NTRSDate not supplied

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗
NASA NTRS2003

Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

Taylor, Jaime↗
NASA NTRS2022

Ab initio Screening of Refractory Nitrides and Carbides for High Temperature Hydrogen Permeation Barriers

Density functional theory was used to screen eleven refractory materials – two pure metals, six nitrides, and three carbides–as high-temperature hydrogen permeation barriers to prevent hydrogen embrittlement. Activation energies were calculated for atomic hydrogen (H) diffusion into the first subsurface layer from the lowest energy surface of the high-temperature phase of each candidate material. The candidate barrier materials with the highest activation energies are h-BN, c-BN, HfN, and ZrN with predicted barriers of 3.25 eV, 3.23 eV, 3.14 eV, and 2.76 eV, respectively. Strain energies, Bader charges, and density of states were calculated for the diffusing H at the relaxed initial state and the transition state to provide insight into contributing factors to high energy barriers. The diffusing H atom in materials with the highest predicted barriers are protic. In addition, interstitial H atoms induce mid-gap states in the density of states of both BN polymorphs. The nitrogen retention of each nitride material at high temperatures was predicted using nitrogen vacancy formation energies with respect to gaseous nitrogen. Experimental evaluation of nitrogen retention in h-BN, ZrN, and TiN confirmed their resistance to nitrogen loss at 1773 K. However, of these nitrides, TiN is predicted to be the least stable. This work identifies multiple promising materials that are predicted to be effective hydrogen barriers at high temperatures and that are stable at temperatures above 2700 K, with BN predicted to perform best.

Density Functional Theory (DFT)↗