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NASA NTRS1999

Trace Chemistry

The goals of the trace chemistry group were to identify the processes relevant to aerosol and aerosol precursor formation occurring within aircraft gas turbine engines; that is, within the combustor, turbine, and nozzle. The topics of discussion focused on whether the chemistry of aerosol formation is homogeneous or heterogeneous; what species are important for aerosol and aerosol precursor formation; what modeling/theoretical activities to pursue; what experiments to carry out that both support modeling activities and elucidate fundamental processes; and the role of particulates in aerosol and aerosol precursor formation. The consensus of the group was that attention should be focused on SO2, SO3, and aerosols. Of immediate concern is the measurement of the concentration of the species SO3, SO2, H2SO4 OH, HO2, H2O2, O, NO, NO2, HONO, HNO3, CO, and CO2 and particulates in various engines, both those currently in use and those in development. The recommendation was that concentration measurements should be made at both the combustor exit and the engine exit. At each location the above species were classified into one of four categories of decreasing importance, Priority I through IV, as follows: Combustor exit: Priority I species - SO3:SO2 ratio, SO3, SO2, and particulates; Priority II species: OH and O; Priority III species - NO and NO2; and Priority IV species - CO and CO2. For the Engine exit: Priority I species - SO3:SO2 ratio, SO3, SO2,H2SO4, and particulates; Priority II species: OH,HO2, H2O2, and O; Priority III species - NO, NO2, HONO, and HNO3; and Priority IV species - CO and CO2. Table I summarizes the anticipated concentration range of each of these species. For particulate matter, the quantities of interest are the number density, size distribution, and composition. In order to provide data for validating multidimensional reacting flow models, it would be desirable to make 2-D, time-resolved measurements of the concentrations of the above species and, in addition, of the pressure, temperature, and velocity. A near term goal of the experimental program should be to confirm the nonlinear effects of sulfur speciation, and if present, to provide an explanation for them. It is also desirable to examine if the particulate matter retains any sulfur. The recommendation is to examine the effects on SOx production of variations in fuel-bound sulfur and aromatic content (which may affect the amount of particulates formed). These experiments should help us to understand if there is a coupling between particulate formation and SO, concentration. Similarly, any coupling with NOx can be examined either by introducing NOx into the combustion air or by using fuel-bound nitrogen. Also of immediate urgency is the need to establish and validate a detailed mechanism for sulfur oxidation/aerosol formation, whose chemistry is concluded to be homogeneous, because there is not enough surface area for heterogeneous effects. It is envisaged that this work will involve both experimental and theoretical programs. The experimental work will require, in addition to the measurements described above, fundamental studies in devices such as flow reactors and shock tubes. Complementing this effort should be modeling and theoretical activities. One impediment to the successful modeling of sulfur oxidation is the lack of reliable data for thermodynamic and transport properties for several species, such as aqueous nitric acid, sulfur oxides, and sulfuric acid. Quantum mechanical calculations are recommended as a convenient means of deriving values for these properties. Such calculations would also help establish rate constants for several important reactions for which experimental measurements are inherently fraught with uncertainty. Efforts to implement sufficiently detailed chemistry into computational fluid dynamic codes should be continued. Zero- and one-dimensional flow models are also useful vehicles for elucidating the minimal set of species and reactions that must be included in two- and three-dimensional modeling studies.

Radhakrishnan, Krishnan↗

NASA NTRS2005

Gears Based on Carbon Nanotubes

Gears based on carbon nanotubes (see figure) have been proposed as components of an emerging generation of molecular- scale machines and sensors. In comparison with previously proposed nanogears based on diamondoid and fullerene molecules, the nanotube-based gears would have simpler structures and are more likely to be realizable by practical fabrication processes. The impetus for the practical development of carbon-nanotube- based gears arises, in part, from rapid recent progress in the fabrication of carbon nanotubes with prescribed diameters, lengths, chiralities, and numbers of concentric shells. The shafts of the proposed gears would be made from multiwalled carbon nanotubes. The gear teeth would be rigid molecules (typically, benzyne molecules), bonded to the nanotube shafts at atomically precise positions. For fabrication, it may be possible to position the molecular teeth by use of scanning tunneling microscopy (STM) or other related techniques. The capability to position individual organic molecules at room temperature by use of an STM tip has already been demonstrated. Routes to the chemical synthesis of carbon-nanotube-based gears are also under investigation. Chemical and physical aspects of the synthesis of molecular scale gears based on carbon nanotubes and related molecules, and dynamical properties of nanotube- based gears, have been investigated by computational simulations using established methods of quantum chemistry and molecular dynamics. Several particularly interesting and useful conclusions have been drawn from the dynamical simulations performed thus far: The forces acting on the gears would be more sensitive to local molecular motions than to gross mechanical motions of the overall gears. Although no breakage of teeth or of chemical bonds is expected at temperatures up to at least 3,000 K, the gears would not work well at temperatures above a critical range from about 600 to about 1,000 K. Gear temperature could probably be controlled by use of coolant gases. For a given application, the gears would work well at temperatures below the critical range, provided that the rotational energy was less than the energy required to tilt the teeth through an angle of 20 . The predominant mechanism of gear failure would be slippage caused by tilting of teeth. Gears would resume functioning if the slipping gears were decelerated sufficiently.

Jaffe, Richard↗

NASA NTRS2016

Spin Glass Patch Planting

In this paper, we propose a patch planting method for creating arbitrarily large spin glass instances with known ground states. The scaling of the computational complexity of these instances with various block numbers and sizes is investigated and compared with random instances using population annealing Monte Carlo and the quantum annealing DW2X machine. The method can be useful for benchmarking tests for future generation quantum annealing machines, classical and quantum mechanical optimization algorithms.

Quantum Annealing↗

NASA NTRS1995

Reliability assessment of multiple quantum well avalanche photodiodes

The reliability of doped-barrier AlGaAs/GsAs multi-quantum well avalanche photodiodes fabricated by molecular beam epitaxy is investigated via accelerated life tests. Dark current and breakdown voltage were the parameters monitored. The activation energy of the degradation mechanism and median device lifetime were determined. Device failure probability as a function of time was computed using the lognormal model. Analysis using the electron beam induced current method revealed the degradation to be caused by ionic impurities or contamination in the passivation layer.

Yun, Ilgu↗

NASA NTRS1996

Computational Materials Research

Computational Materials aims to model and predict thermodynamic, mechanical, and transport properties of polymer matrix composites. This workshop, the second coordinated by NASA Langley, reports progress in measurements and modeling at a number of length scales: atomic, molecular, nano, and continuum. Assembled here are presentations on quantum calculations for force field development, molecular mechanics of interfaces, molecular weight effects on mechanical properties, molecular dynamics applied to poling of polymers for electrets, Monte Carlo simulation of aromatic thermoplastics, thermal pressure coefficients of liquids, ultrasonic elastic constants, group additivity predictions, bulk constitutive models, and viscoplasticity characterization.

Hinkley, Jeffrey A.↗

NASA NTRS1978

Theoretical study of HSiO/+/ and HOSi/+/

Results are reported for quantum-mechanical studies of the ions HSiO(+) and HOSi(+). The equilibrium geometries, rotation constants, and relative stabilities of these ions are determined using the matrix Hartree-Fock model with a basis set of Slater exponential functions. Optimum bond lengths are calculated, and an empirical correction to the computed bond lengths is introduced. The isomer HOSi(+) is found to be more stable than HSiO(+). A frequency of 35.77 GHz is obtained for the J = 1-0 transition of HOSi(+) by assuming that the vibration-rotation interaction constants for this isomer are the same as those for HCP.

Wilson, S.↗

NASA NTRS2008

NASA Tech Briefs, March 2008

Topics covered include: WRATS Integrated Data Acquisition System; Breadboard Signal Processor for Arraying DSN Antennas; Digital Receiver Phase Meter; Split-Block Waveguide Polarization Twist for 220 to 325 GHz; Nano-Multiplication-Region Avalanche Photodiodes and Arrays; Tailored Asymmetry for Enhanced Coupling to WGM Resonators; Disabling CNT Electronic Devices by Use of Electron Beams; Conical Bearingless Motor/Generators; Integrated Force Method for Indeterminate Structures; Carbon-Nanotube-Based Electrodes for Biomedical Applications; Compact Directional Microwave Antenna for Localized Heating; Using Hyperspectral Imagery to Identify Turfgrass Stresses; Shaping Diffraction-Grating Grooves to Optimize Efficiency; Low-Light-Shift Cesium Fountain without Mechanical Shutters; Magnetic Compensation for Second-Order Doppler Shift in LITS; Nanostructures Exploit Hybrid-Polariton Resonances; Microfluidics, Chromatography, and Atomic-Force Microscopy; Model of Image Artifacts from Dust Particles; Pattern-Recognition System for Approaching a Known Target; Orchestrator Telemetry Processing Pipeline; Scheme for Quantum Computing Immune to Decoherence; Spin-Stabilized Microsatellites with Solar Concentrators; Phase Calibration of Antenna Arrays Aimed at Spacecraft; Ring Bus Architecture for a Solid-State Recorder; and Image Compression Algorithm Altered to Improve Stereo Ranging.

Source record↗

NASA NTRS2019

AladynPi – Adaptive Neural Network Molecular Dynamics Simulation Code with Physically Informed Potential: Computational Materials Mini-Application

This report provides an overview and description of commands used in the Computational Materials mini-application, AladynPi. AladynPi is an extension of a previously released mini-application, Aladyn (https://github.com/nasa/aladyn; Yamakov, V.I., and Glaessgen, E.H., NASA/TM-2018-220104). Aladyn and AladynPi are basic molecular dynamics codes written in FORTRAN 2003, which are 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 method. An input for the ANN is a set of structure coefficients, characterizing the local atomic environment of each atom, for which the atomic energy is obtained in the ANN inference process. In Aladyn, the ANN gives directly the energy of interatomic interactions. In AladynPi, the ANN gives optimized parameters for a predefined empirical function, known as bond-order-potential (BOP). The parameterized BOP function is then used to calculate the energy. AladynPi code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing manycore architectures based on graphic processing units (GPUs). The effort is supported by the High Performance Computing incubator (HPCi) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗

NASA NTRS1987

High temperature transport properties of air

A general computer code was developed to allow calculation of atom-atom and ion-atom transport collision integrals from accurate potential energy curves described by a set of discrete data points for a broad range of scattering conditions. This code is based upon semiclassical approximations that properly account for quantum mechanical behavior such as tunneling effects near a barrier maximum, resonance charge exchange, and nuclear symmetry effects. Transport collision integrals were determined for N-N, O-O, N(+)-N, and O(+)-O interactions from complete sets of accurate potential functions derived from combined experimental and ab initio structure calculations. For the O-O case, this includes results for excited states. The calculated values of the N(+)-N and O(+)-O resonance charge exchange cross section Q(ex) agree well with measurements from beam experiment that are available at high energies where the diffusion cross section Q(d) satisfies Q(d) approximately equal to 2Q(ex).

Levin, E.↗

NASA NTRS2018

Mechanism of Quantum Speedup in Novel Population Transfer Protocol for Binary Optimization Problems

We consider a novel quantum population transfer protocol to solve binary optimization problems that exploits quantum many-body dynamics in the delocalized regime. Hard optimization problems are characterized by energy landscape with a large number of local minima separated by large Hamming distances which scale with the problem size. This landscape gives rise to an interesting computational primitive: given an initial bit-string, we are to produce other bit-strings within certain narrow range of energies around the initial state. We consider a specific model we call "impurity band": a system of n qubits in a transverse field, where a number of bitstrings $M<<2^n$ selected at random are assigned random energies distributed in a narrow window of width $W<<1$ around the mean energy $-n$. We demonstrate the existence of the many-body delocalized regime in this model when the spectrum of the model splits into many-body minibands, and a typical eigenstate wave function is a superposition of peaks centered at a large number of local minima. The typical width of the minibands in energy determines the efficiency of the population transfer protocol. We demonstrate theoretically that the population transfer protocol achieves Grover type speedup in the unstructured impurity band model.

Kechedzhi, Kostyantyn↗

NASA NTRS1974

Vibration-translation energy transfer in anharmonic diatomic molecules. 1: A critical evaluation of the semiclassical approximation

The semiclassical approximation is applied to anharmonic diatomic oscillators in excited initial states. Multistate numerical solutions giving the vibrational transition probabilities for collinear collisions with an inert atom are compared with equivalent, exact quantum-mechanical calculations. Several symmetrization methods are shown to correlate accurately the predictions of both theories for all initial states, transitions, and molecular types tested, but only if coupling of the oscillator motion and the classical trajectory of the incident particle is considered. In anharmonic heteronuclear molecules, the customary semiclassical method of computing the classical trajectory independently leads to transition probabilities with anomalous low-energy resonances. Proper accounting of the effects of oscillator compression and recoil on the incident particle trajectory removes the anomalies and restores the applicability of the semiclassical approximation.

Mckenzie, R. L.↗

NASA NTRS1975

Vibration-translation energy transfer in anharmonic diatomic molecules. I - A comparative evaluation of the semiclassical approximation

The semiclassical approximation (quantum oscillator, classical path) is applied to anharmonic diatomic oscillators in excited initial states. Multistate numerical solutions giving the vibrational transition probabilities for collinear collisions with an inert atom are compared with equivalent, exact quantum-mechanical calculations. Several symmetrization methods are shown to correlate accurately the predictions of both theories for all initial states, transitions, and molecular types tested, but only if coupling of the oscillator motion and the classical trajectory of the incident particle is considered. In anharmonic heteronuclear molecules, the customary semiclassical method of computing the classical trajectory independently leads to transition probabilities with anomalous low-energy resonances. Proper accounting of the effects of oscillator compression and recoil on the incident particle trajectory removes the anomalies and restores the applicability of the semiclassical approximation.

Mckenzie, R. L.↗

NASA NTRS1992

Vibrational relaxation of anharmonic oscillators in expanding flows

Although the Landau-Teller vibrational model accurately predicts vibrational excitation process in post-shock and compressing flows, it under-predicts the rate of de-excitation in cooling and expanding flows. In the present paper, detailed calculations of the vibrational relaxation process of N2 and CO in cooling flows are conducted. A coupled set of vibrational transition rate equations and quasi-one-dimensional fluid dynamic equations is solved. Multiple quantum level transition rates are computed using SSH theory. The SSH transition rate results are compared with available experimental data and other theoretical models. Vibration-vibration exchange collisions are responsible for some vibrational relaxation acceleration in situations of high vibrational temperature and low translational temperature. The present results support the relaxation mechanisms proposed by Bray and by Treanor Rich and Rehm.

Ruffin, Stephen M.↗

NASA NTRSDate not supplied

Impact of NASA’s Entry Systems Modeling Project on Planetary Mission Design

Planetary missions continue to grow larger and more complex. Furthermore, the current focus on human exploration of the Moon and Mars, as well as Mars Sample Return(MSR), place increas-ingly stringent requirements on the reliability of the entry, descent, and landing (EDL) system that ensures the safe delivery of payload or crew to their destination. Planetary EDL is an area in which mission designers are critically reliant on modeling and simulation to demonstrate the reliability of the system, as there are no ground facilities that are able to fully test these systems in a flight-relevant environment. NASA’s state-of-the-art modeling and simulation capability must continually evolve to meet the needs of the next generation of planetary EDL. To accomplish this aim, NASA’s Entry Systems Modeling (ESM) Project was formed in 2013and is funded bythe Space Technology Mission Directorate(STMD) and Science Mission Directorate (SMD). ESM is the Agency’s only cross-cutting effort for advancing entry systems modeling and simulation capabilities across a range of technical disciplines and Solar System destinations. ESM is a portfolio project covering a variety of mid-TRL research efforts within four core EDL-related areas of investment: (1) Thermal protection material modeling, (2) Shock layer kinetics and radiation, (3) Aerosciences, and (4) Guidance, navigation, and con-trol. The material modeling group creates detailed material response modelsof thermal protection systems (TPS)from the micro to macro scale, and at the fun-damental and engineering levels. Shock layer kinetics and radiation focuses on radiative heating of space-craft, quantum chemistry and benchmark experiments for validation.Aerosciences is a broad research area that impacts many aspects of entry systems, including parachutes, aerodynamics, and turbulent heating augmentation due to TPS roughness.The guidance, navigation,and control effort under ESM is expanding the capabilities of NASA’s main flight mechanics tool, POST2, for use on high-performance computing architectures and to generalize interoperability with external applications for more detailed end-to-end simula-tion.In addition, several focusedresearch topics have been approvedto augment ESM’s core portfolio. These include efforts for deep post-flight analysis of Mars 2020/MEDLI2 flight data; development ofTPS failure models; improvement of hypersonic wakeflow models; and a recently concluded effort to provide material response models for NuSil-coated PICA heat-shield material. This presentation will discuss each of these investment areas and demonstrate via real mission examples how advances to the state-of-the-art enabled by ESM are directly impacting the missions of today and tomorrow, including InSight, Mars 2020, Mars Sample Return, Orion, and Dragonfly.

Entry Systems Modeling↗

NASA NTRS2002

Research in Computational Astrobiology

We present results from several projects in the new field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. We have developed a procedure for calculating long-range effects in molecular dynamics using a plane wave expansion of the electrostatic potential. This method is expected to be highly efficient for simulating biological systems on massively parallel supercomputers. We have perform genomics analysis on a family of actin binding proteins. We have performed quantum mechanical calculations on carbon nanotubes and nucleic acids, which simulations will allow us to investigate possible sources of organic material on the early earth. Finally, we have developed a model of protobiological chemistry using neural networks.

Chaban, Galina↗

NASA NTRS2000

Computational Nanotechnology of Materials, Devices, and Machines: Carbon Nanotubes

The mechanics and chemistry of carbon nanotubes have relevance for their numerous electronic applications. Mechanical deformations such as bending and twisting affect the nanotube's conductive properties, and at the same time they possess high strength and elasticity. Two principal techniques were utilized including the analysis of large scale classical molecular dynamics on a shared memory architecture machine and a quantum molecular dynamics methodology. In carbon based electronics, nanotubes are used as molecular wires with topological defects which are mediated through various means. Nanotubes can be connected to form junctions.

Srivastava, Deepak↗

NASA NTRS2003

Interfacial Reaction Studies Using ONIOM

In this report, we focus on the calculations of the energetics and chemical kinetics of heterogeneous reactions for Organometallic vapor phase epitaxy (OMVPE). The work described in this report builds upon our own previous thermochemical and chemical kinetics studies. The first of these articles refers to the prediction of thermochemical properties, and the latter one deals with the prediction of rate constants for gaseous homolytic dissociation reactions. The calculations of this investigation are at the microscopic level. The systems chosen consisted of a gallium nitride (GaN) substrate, and molecular nitrogen (N2) and ammonia (NH3) as adsorbants. The energetics for the adsorption and the adsorbant dissociation processes were estimated, and reaction rate constants for the dissociation reactions of free and adsorbed molecules were predicted. The energetics for substrate decomposition was also computed. The ONIOM method, implemented in the Gaussian98 program, was used to perform the calculations. This approach has been selected since it allows dividing the system into two layers that can be treated at different levels of accuracy. The atoms of the substrate were modeled using molecular mechanics6 with universal force fields, whereas the adsorbed molecules were approximated using quantum mechanics, based on density functional theory methods with B3LYP functionals and 6-311G(d,p) basis sets. Calculations for the substrate were performed in slabs of several unit cells in each direction. The N2 and NH3 adsorbates were attached to a central location at the Ga-lined surface.

Cardelino, Beatriz H.↗

NASA NTRSDate not supplied

Wildfire Segmentation From Remotely Sensed Data Using Quantum-Compatible Conditional Vector Quantized-Variational Autoencoders

Wildfires represent a critical environmental hazard with multifaceted implications for ecosystems, communities, and public health [1]. The escalating frequency and intensity of wildfires globally have intensified the urgency for robust segmentation methodologies to facilitate effective mitigation, response, and recovery strategies [2]. Accurate wildfire segmentation is pivotal for delineating fire boundaries, assessing progression patterns, and prioritizing resource allocation during emergency scenarios. Furthermore, precise segmentation enables stakeholders, including policymakers, environmental scientists, and emergency responders, to formulate evidence-based strategies, thereby minimizing socio-economic disruptions and ecological degradation. Consequently, advancing wildfire segmentation techniques through innovative technological interventions remains a paramount research imperative. Although foundational in wildfire segmentation, traditional deterministic models exhibit inherent limitations that compromise their efficacy in dynamic and uncertain environments. These models often operate on rigid algorithms prioritizing deterministic classifications, thereby overlooking the inherent complexities and uncertainties associated with wildfire behavior and satellite data variability. Such deterministic frameworks tend to produce oversimplified representations that fail to capture the intricate nuances of evolving fire dynamics, spatial heterogeneity, and environmental interactions [1]. Consequently, the deterministic approach’s propensity for uncertainty collapsing [1, 3] hampers the accuracy, reliability, and applicability of segmentation outcomes in real-world scenarios. Contrastingly, stochastic models offer a more nuanced and adaptable framework for wildfire segmentation. By integrating probabilistic elements into the modeling paradigm, stochastic approaches, particularly probabilistic approaches such as variational auto encoders (VAEs) [4], facilitate comprehensive uncertainty assessment, enabling researchers to quantify and incorporate uncertainties into segmentation outcomes effectively. This probabilistic nature empowers stochastic models to encapsulate variability, account for data inconsistencies, and adapt to evolving environmental conditions, enhancing segmentation accuracy, reliability, and robustness. Embracing stochastic methodologies thus catalyzes advancements in wildfire science by fostering a more holistic, adaptive, and resilient segmentation framework. Despite VAEs demonstrating significant promise in various applications, they come with inherent limitations that have garnered attention within the machine learning community. One of the primary drawbacks lies in their reliance on static priors, which essentially assume a fixed distribution for latent variables, thereby limiting the model’s flexibility to capture complex data structures effectively [5]. This static nature leads to suboptimal representations, especially when dealing with complex and high-dimensional data. Additionally, VAEs often struggle with generating sharp and realistic samples, a phenomenon commonly referred to as mode collapse [5, 7, 6]. Furthermore, the optimization process in VAEs, which involves balancing the reconstruction loss and the regularization term, can sometimes be challenging to fine-tune [7]. In recent efforts to address these shortcomings, alternative approaches like Vector Quantized Variational Auto encoders(VQ-VAEs) [7], address the challenges by incorporating discrete latent variables and leveraging techniques that enhance the quality and diversity of generated samples while maintaining efficient training dynamics. VQ-VAEs propose a dynamic prior distribution generation mechanism that diverges from the static priors commonly associated with traditional VAEs. This dynamic approach allows for more adaptive and context-aware latent variable representations, thereby potentially capturing complex data structures more effectively. Unlike autoregressive prior models such as PixelCNN, which, despite their ability to model dependencies across data dimensions, suffer from significant computational inefficiencies and lack flexibility in handling diverse datasets. In our work, we propose to use a generative quantum-compatible approach to help alleviate the shortcomings of autoregressive prior model in VQ-VAEs. Restricted Boltzmann Machines (RBMs) are a viable alternative prior model that can learn prior distributions in a faster and more flexible manner. In this research endeavor, we meticulously curate a state-of-the-art dataset leveraging satellite MODIS data in conjunction with VIIRS fire masks, derived from Fire Radiative Power (FRP), thereby encapsulating diverse wildfire scenarios and environmental contexts. We developed a conditional VQ-VAE architecture with the RBM prior model that is trained in a supervised manner for segmenting wildfire masks. This innovative approach synergistically harnesses deep learning capabilities, enabling the generation of segmentation maps characterized by heightened precision, granularity, and contextual relevance. Furthermore, replacing the autoregressive prior learning method proposed by the original VQ-VAE with a prior density approximation via quantum-compatible RBM facilitates expedited inference processes, augments flexibility in prior sampling, optimizes computational efficiency and establishes a groundbreaking benchmark in wildfire segmentation methodologies.

quantum machine learning↗