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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Chirality manipulation of ultrafast phase switches in a correlated CDW-Weyl semimetal

Light engineering of correlated states in topological materials provides a new avenue of achieving exotic topological phases inaccessible by conventional tuning methods. Here we demonstrate a light control of correlation gaps in a model charge-density-wave (CDW) and polaron insulator (TaSe 4 ) 2 I recently predicted to be an axion insulator. Our ultrafast terahertz photocurrent spectroscopy reveals a two-step, non-thermal melting of polarons and electronic CDW gap via the fluence dependence of a longitudinal circular photogalvanic current. This helicity-dependent photocurrent reveals continuous ultrafast phase switches from the polaronic state to the CDW (axion) phase, and finally to a hidden Weyl phase as the pump fluence increases. Additional distinctive attributes aligning with the light-induced switches include: the mode-selective coupling of coherent phonons to the polaron and CDW modulation, and the emergence of a non-thermal chiral photocurrent above the pump threshold of CDW-related phonons. The demonstrated ultrafast chirality control of correlated topological states here holds large potentials for realizing axion electrodynamics and advancing quantum-computing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Superconductivity in type-II Weyl-semimetal WTe 2 induced by a normal metal contact

WTe 2 is a material with rich topological properties: it is a 2D topological insulator as a monolayer and a Weyl-semimetal and higher-order topological insulator in a bulk form. Inducing superconductivity in topological materials is a way to obtain topological superconductivity, which lays at the foundation for many proposals of fault tolerant quantum computing. Here, we demonstrate the emergence of superconductivity at the interface between WTe 2 and the normal metal palladium. The superconductivity has a critical temperature of about 1.2 K. By studying the superconductivity in a perpendicular magnetic field, we obtain the coherence length and the London penetration depth. These parameters correspond to a low Fermi velocity and a high density of states at the Fermi level. This hints to a possible origin of superconductivity due to the formation of flatbands. Furthermore, the critical in-plane magnetic field exceeds the Pauli limit, suggesting a non-trivial nature of the superconducting state.

Kononov, Artem↗
DOE OSTI2021

An index for two-dimensional SPT states

We define an index for 2D G-invariant invertible states of bosonic lattice systems in the thermodynamic limit for a finite symmetry group G with a unitary action. Furthermore, we show that this index is an invariant of the symmetry protected phase.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Sneak circuit analysis of instrumentation and control systems

The evolvement and implementation is presented of a systematic means for detecting the sneak prone designs of an electrical system which could result in such unplanned modes so that they can be prevented prior to occurrence. Sneak circuit analysis is shown to be a formalized approach based upon topological techniques. The trees employed are produced from manufacturing detail data processed by a computer to orderly completion. The analysis techniques applied on a variety of NASA programs are shown to be particularly applicable to industrial instrumentation and control systems.

Rankin, J. P.↗
NASA NTRS1991

A method for interactive specification of multiple-block topologies

A method is presented for dealing with the vast amount of topological and other data which must be specified to generate a multiple-block computational grid. Specific uses of the graphical capabilities of a powerful scientific workstation are described which reduce the burden on the user of collecting and formatting such large amounts of data. A program to implement this method, 3DPREP, is described. A plotting transformation algorithm, some useful software tools, notes on programming, and a database organization are also presented. Example grids developed using the method are shown.

Sorenson, Reese L.↗
NASA NTRS1993

Shock-vortex interaction over a 65-degree delta wing in transonic flow

Transonic flow over a 65-deg swept-back, sharp-edged, cropped delta wing is investigated computationally using the time-accurate solution of the unsteady, compressible, full Navier-Stokes equations with an implicit, upwind, flux-difference splitting, finite-volume scheme. Coarse and fine O-H grids are used to obtain the solution. The grid consists of 125 x 85 x 84 points in the wrap-around, normal, and axial directions, respectively. The results are presented for an angle of attack of 20 deg Mach number of 0.85 and Reynolds number of 3.23 x 10 exp 6. With the fine grid, the results show that a system of shocks has been captured over the upper wing surface and that the leading-edge vortex core experiences an unsteady supersonic vortex breakdown after passing through a spanwise shock near the wing trailing edge. The computed results at a certain time are in good agreement with the experimental data. Topological aspects of the vortex breakdown flowfield are also presented and discussed.

Kandil, Osama A.↗
NASA NTRS1995

Microgravity and Charge Transfer in the Neuronal Membrane: Implications for Computational Neurobiology

Evidence from natural and artificial membranes indicates that the neural membrane is a liquid crystal. A liquid-to-gel phase transition caused by the application of superposed electromagnetic fields to the outer membrane surface releases spin-correlated electron pairs which propagate through a charge transfer complex. The propagation generates Rydberg atoms in the lipid bilayer lattice. In the present model, charge density configurations in promoted orbitals interact as cellular automata and perform computations in Hilbert space. Due to the small binding energies of promoted orbitals, their automata are highly sensitive to microgravitational perturbations. It is proposed that spacetime is classical on the Rydberg scale, but formed of contiguous moving segments, each of which displays topological equivalence. This stochasticity is reflected in randomized Riemannian tensor values. Spacetime segments interact with charge automata as components of a computational process. At the termination of the algorithm, an orbital of high probability density is embedded in a more stabilized microscopic spacetime. This state permits the opening of an ion channel and the conversion of a quantum algorithm into a macroscopic frequency code.

Wallace, Ron↗
NASA NTRS1999

Turbulence Model Comparisons for a High-Speed Aircraft

Four turbulence models are described and evaluated for transonic flows over the High-Speed Research/industry baseline configuration known as Reference H by using the thin-layer, upwind, Navier-Stokes solver known as CFL3D. The turbulence models studied are the equilibrium model of Baldwin-Lomax (B-L) with the Degani-Schiff (D-S) modifications, the one-equation Baldwin-Barth (B-B) model, the one-equation Spalart-Allmaras (S-A) model, and Menter's two-equation Shear Stress Transport (SST) model. The flow conditions, which correspond to tests performed in the National Transonic Facility (NTF) at Langley Research Center, are a Mach number of 0.90 and a Reynolds number of 30 x 10 (exp. 6) based on mean aerodynamic chord for angles of attack of 1 deg., 5 deg., and 10 deg. The effects of grid topology and the representation of the actual wind tunnel model geometry are also investigated. Computed forces and surface pressures compare reasonably well with the experimental data for all four turbulence models.

Rivers, Melissa B.↗
NASA NTRSDate not supplied

Simulation of Oxidative Etch Pit Formation and Growth on FiberForm

Erosion of carbon surfaces due to oxidation does not occur uniformly but through the formation of localized etch pits because of active surface sites. These active sites are formed due to the presence of atomic defects on the carbon surface and have much higher reactivity compared to average non-defective sites. Thus, these active sites are the first to react during ablation, resulting in their removal. This causes all the neighboring atoms to be defective, and increasing their reactivity, thus leading to localized carbon removal around these “active” sites. In this manner, these highly reactive defects serve as nucleation sites for the formation and growth of etch pits, with detrimental effects on the structural integrity. In order to understand the influence of these etch pits on the material properties of carbon fiber microstructures, we have developed a new capability within direct simulation Monte Carlo (DSMC) to capture the etch pit formation process. This capability is developed within the DSMC code SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and can model the material removal in the presence of active sites leading to the formation of etch pits. The focus of the current work will be to study the effect of etch pits on the material properties of FiberForm, the precursor substrate of the PICA Thermal Protection System (TPS) material. The microstructure of virgin FiberForm obtained directly from X-ray microtomography scans is used within SPARTA to obtain the ablated geometries with etch pits. These pitted microstructures are then imported into the Porous Microstructure Analysis (PuMA) software and various material properties such as thermal conductivity, elasticity, and permeability are computed. The variation of these properties because of the complex evolution of the surface topology due to the formation of etch pits is studied and analyzed. Furthermore, the effect of pitting is compared to the case of uniform radial shrinking of fibers, which has been the standard for modelling ablation of carbon structures, and significant differences are observed. Thus, a physically realistic model of material removal through the formation of etch pits will be helpful in predicting the degradation of carbon-based TPS more accurately during oxidation; as well as other mechanisms such as spallation, which involves the removal of chunks of material into the flow due to the growth of etch pits. This will ultimately improve our understanding of the failure modes in these materials due to ablation.

DSMC↗
NASA NTRSDate not supplied

Simulation of Oxidative Etch Pit Formation and Growth on FiberForm

Erosion of carbon surfaces due to oxidation does not occur uniformly but through the formation of localized etch pits because of active surface sites. These active sites are formed due to the presence of atomic defects on the carbon surface and have much higher reactivity compared to average non-defective sites. Thus, these active sites are the first to react during ablation, resulting in their removal. This causes all the neighboring atoms to be defective, and increasing their reactivity, thus leading to localized carbon removal around these “active” sites. In this manner, these highly reactive defects serve as nucleation sites for the formation and growth of etch pits, with detrimental effects on the structural integrity. In order to understand the influence of these etch pits on the material properties of carbon fiber microstructures, we have developed a new capability within direct simulation Monte Carlo (DSMC) to capture the etch pit formation process. This capability is developed within the DSMC code SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) and can model the material removal in the presence of active sites leading to the formation of etch pits. The focus of the current work will be to study the effect of etch pits on the material properties of FiberForm, the precursor substrate of the PICA Thermal Protection System (TPS) material. The microstructure of virgin FiberForm obtained directly from X-ray microtomography scans is used within SPARTA to obtain the ablated geometries with etch pits. These pitted microstructures are then imported into the Porous Microstructure Analysis (PuMA) software and various material properties such as thermal conductivity, elasticity, and permeability are computed. The variation of these properties because of the complex evolution of the surface topology due to the formation of etch pits is studied and analyzed. Furthermore, the effect of pitting is compared to the case of uniform radial shrinking of fibers, which has been the standard for modelling ablation of carbon structures, and significant differences are observed. Thus, a physically realistic model of material removal through the formation of etch pits will be helpful in predicting the degradation of carbon-based TPS more accurately during oxidation; as well as other mechanisms such as spallation, which involves the removal of chunks of material into the flow due to the growth of etch pits. This will ultimately improve our understanding of the failure modes in these materials due to ablation.

DSMC↗
DOE OSTI2020

A Learning-based Supervisory Control Architecture for Electric Vehicle Charging System Paired with Energy Storages

A Machine Learning-based predictive model is developed for optimal dispatching energy storage system integrated with Electric Vehicle battery charger. The model is effectively trained using transfer learning algorithm and successfully validated via measurement data to achieve high fidelity and accuracy. The study findings provide possibilities for future development of the presented approach to implement computational heavy predictive algorithms with multi-step predictions in emerging modular bidirectional charger topologies to realize vehicle-to-grid (V2G) technology. The online tuning can be explored using the new measurements obtained during the operation, henceforth, enhancing the controller performance for integrating multiple DERs into distribution power networks that shows huge interest for the utilities and regulatory agencies. Multiple operation scenatios have been evaluated and simulation results are discussed to verify intended performance of the proposed control solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
DOE OSTI2020

Energy Release Rate Approximation for Small Surface Cracks in Three-Dimensional Domains Using the Topological Derivative

The topological derivative describes the variation of a response functional with respect to infinitesimal changes in topology, such as the introduction of an infinitesimal crack or hole. In this three-dimensional fracture mechanics work, we propose an approximation of the energy release rate field associated with a small surface crack of any boundary location, direction, and orientation combination using the topological derivative. Furthermore, this work builds on the work of Silva et al. (“Energy Release Rate Approximation for Small Surface-Breaking Cracks Using the Topological Derivative,” J. Mech. Phys. Solids 59(5), pp. 925–939), in which the authors proposed an approximation of the energy release rate field which was limited to two-dimensional domains. The proposed method is computationally advantageous because it only requires a single analysis. By contrast, current boundary element and finite element-based methods require an analysis for each crack length-location-direction-orientation combination. Furthermore, the proposed method is evaluated on the non-cracked domain, obviating the need for refined meshes in the crack tip region.

42 ENGINEERING↗
DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗
DOE OSTI2021

Simplifying computational workflows with the Multiscale Atomic Zeolite Simulation Environment (MAZE)

Zeolites, an important class of 3-dimensional nanoporous materials, have been widely explored for a variety of applications including gas storage, separations, and catalysis. As the properties of these aluminosilicate materials depend on a number of factors (e.g., framework topology, Si/Al ratio, extra-framework cations etc.), detailed experiments (e.g., catalytic properties, adsorption capacities etc.) are often limited to only a handful of materials. Computational methods have played an important role in (1) providing molecular level insights to rationalize experimental observations, and (2) screening large libraries of zeolites to identify promising candidates for experimental synthesis and validation. Different levels of theory and computational chemistry codes are necessary to describe the range of relevant phenomena such as adsorption (e.g., grand canonical Monte Carlo), diffusion (e.g., molecular dynamics), and chemical reactions (e.g., density functional theory). Manipulation of atomic structures, handling of input files, and developing robust workflows becomes quite cumbersome. To mitigate these challenges, we describe the development of the Multiscale Atomic Zeolite Simulation Environment (MAZE) – a Python package that simplifies zeolite-specific calculation workflows by providing a user-friendly interface for systematically manipulating zeolite structures

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Room temperature persisting surface charge carriers driven by intense terahertz electric fields in a topological insulator Bi 2 Se 3

Topologically protected surface current is highly promising for next-generation low-dissipation and disorder-tolerant quantum electronics and computing. Yet, electric transport from the co-existing bulk state dominates the responses of the Dirac surface state, especially at elevated temperatures relevant to technological applications. Here, we present an approach that convincingly showcases the generation, disentanglement, and precise control of enduring surface charge carriers on a topological insulator, Bi 2 Se 3 , with high bulk conductivity, all achieved at room temperature. By using pump–probe modulation spectroscopy under ultrabroadband driving tunable from 4 meV to 1.55 eV, we show the terahertz (THz) field-induced surface carriers by discovering their initial temporal responses dominant over high density trivial bulk carriers. Strikingly, the response of the induced surface carrier responses persists for more than ~5 ps and is enhanced by reducing pump photon energy. The dynamics and lifetime of the distinct surface response manifest themselves as the enhanced THz pump-induced THz transmission, which directly correlates with the transient negative THz conductivity. Increasing the THz driving field reduces the induced surface carrier lifetime and identifies, particularly, an optimal pump field of E s ~ 224 kV cm -1 for generating the dominant surface response relative to the bulk. This surface carrier dominant regime is suppressed by a joint effect of enhanced surface-bulk scattering and a more rapid saturation of surface excitation compared to the bulk that sets in above E s . The controllability of room temperature topologically surface carriers through pump photon energy offer compelling possibilities for extending this approach to other topological complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Computationally Directed Discovery of MoBi 2

Incorporating bismuth, the heaviest element stable to radioactive decay, into new materials enables the creation of emergent properties such as permanent magnetism, superconductivity, and nontrivial topology. Understanding the factors that drive Bi reactivity is critical for the realization of these properties. Using pressure as a tunable synthetic vector, we can access unexplored regions of phase space to foster reactivity between elements that do not react under ambient conditions. Furthermore, combining computational and experimental methods for materials discovery at high-pressures provides broader insight into the thermodynamic landscape than can be achieved through experiment alone, informing our understanding of the dominant chemical factors governing structure formation. Herein, we report our combined computational and experimental exploration of the Mo–Bi system, for which no binary intermetallic structures were previously known. Using the ab initio random structure searching (AIRSS) approach, we identified multiple synthetic targets between 0–50 GPa. Highpressure in situ powder X-ray diffraction experiments performed in diamond anvil cells confirmed that Mo–Bi mixtures exhibit rich chemistry upon the application of pressure, including experimental realization of the computationally predicted CuAl 2 -type MoBi 2 structure at 35.8(5) GPa. Electronic structure and phonon dispersion calculations on MoBi 2 revealed a correlation between valence electron count and bonding in high-pressure transition metal–Bi structures as well as identified two dynamically stable ambient pressure polymorphs. Our study demonstrates the power of the combined computational–experimental approach in capturing highpressure reactivity for efficient materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗