Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic structural analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Recordings and Analysis of Atomic Ledge and Dislocation Movements in InGaAs to Nickelide Nanowire Phase Transformation

The formation of low resistance and self‐aligned contacts with thermally stable alloyed phases is a prerequisite for realizing reliable functionality in ultrascaled semiconductor transistors. Detailed structural analysis of the phase transformation accompanying contact alloying can facilitate contact engineering as transistor channels approach a few atoms across. Original in situ heating transmission electron microscopy studies are carried out to record and analyze the atomic scale dynamics of contact alloy formation between Ni and In 0.53 Ga 0.47 As nanowire channels. It is observed that the nickelide reacts on the In 0.53 Ga 0.47 As (111) || Ni 2 In 0.53 Ga 0.47 As (0001) interface with atomic ledge propagation along the Ni 2 In 0.53 Ga 0.47 As direction. Ledges nucleate as a train of strained single‐bilayers and propagate in‐plane as double‐bilayers that are associated with a misfit dislocation of . The atomic structure is reconstructed to explain this phase transformation that involves collective gliding of three Shockley partials in In 0.53 Ga 0.47 As lattice to cancel out shear stress and the formation of misfit dislocations to compensate the large lattice mismatch in the newly formed nickelide phase and the In 0.53 Ga 0.47 As layers. This work demonstrates the applicability of interfacial disconnection (ledge + dislocation) theory in a nanowire channel during thermally induced phase transformation that is typical in metal/III–V semiconductor reactions.

Chen, Renjie↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A Client/Server Architecture for Supporting Science Data Using EPICS Version 4

The Phase 1 grant that serves as a precursor to this proposal, prototyped complex storage techniques for high speed structured data that is being produced in accelerator diagnostics and beam line experiments. It demonstrates the technologies that can be used to archive and retrieve complex data structures and provide the performance required by our new accelerators, instrumentations, and detectors. Phase 2 is proposed to develop a high-performance platform for data acquisition and analysis to provide physicists and operators a better understanding of the beam dynamics. This proposal includes developing a platform for reading 109 MHz data at 10 KHz rates through a multicore front end processor, archiving the data to an archive repository that is then indexed for fast retrieval. The data is then retrieved from this data archive, integrated with the scalar data, to provide data sets to client applications for analysis, use in feedback, and to aid in identifying problem with the instrumentation, plant, beam steering, or model. This development is built on EPICS version 4 , which is being successfully deployed to implement physics applications. Through prior SBIR grants, EPICS version 4 has a solid communication protocol for middle layer services (PVAccess), structured data representation and methods for efficient transportation and access (PVData), an operational hierarchical record environment (JAVA IOC), and prototypes for standard structured data (Normative Types). This work was further developed through project funding to successfully deploy the first service based physics application environment with demonstrated services that provide arbitrary object views, save sets, model, lattice, and unit conversion. Thin client physics applications have been developed in Python that implement quad centering, orbit display, bump control, and slow orbit feedback. This service based architecture has provided a very modular and robust environment that enables commissioning teams to rapidly develop and deploy small scripts that build on powerful services. These services are all built on relational database data stores and scalar data. The work proposed herein, builds on these previous successes to provide data acquisition of high speed data for online analysis clients.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

A framework for the identification of full-field structural dynamics using sequences of images in the presence of non-ideal operating conditions

Recent developments in the ability to automatically and efficiently extract natural frequencies, damping ratios, and full-field mode shapes from video of vibrating structures has great potential for reducing the resources and time required for performing experimental and operational modal analysis at very high spatial resolution. Furthermore, these techniques have the added advantage that they can be implemented remotely and in a non-contact fashion. Emerging full-field imaging techniques therefore have potential to allow the identification of the modal properties of structures in regimes that used to be challenging. For instance, these techniques suggest that the high spatial resolution structural identification could be performed on an aircraft during flight using a ground or aircraft-based imager. They also have the potential to identify the dynamics of microscopic systems. In order to realize this capability it will be necessary to develop techniques that can extract full-field structural dynamics in the presence of non-ideal operating conditions. In this work, we develop a framework for the deployment of emerging algorithms that allow the automatic extraction of high-resolution, full-field modal parameters in the presence of non-ideal operating conditions. One of the most notable non-ideal operating conditions is the rigid body motion of both the structure being measured as well as the imager performing the measurement. We demonstrate an instantiation of the framework by showing how it can be used to address, in-plane, translational, rigid body motion. The development of a frame-to-frame keypoint–based technique for identifying full-field structural dynamics in the presence of either rigid body motion is presented and demonstrated in the context of the framework for the deployment of full-field structural identification techniques in the presence of non-ideal operating conditions. It is expected that this framework will ultimately help enable the collection of full-field structural dynamics using measurement platforms including unmanned aerial vehicles, robotic telescopes, satellites, imagers mounted in high-vibration environments (seismic, industrial, harsh weather), characterization of microscopic structures, and human-carried imagers. If imager-based structural identification techniques mature to the point that they can be used in non-ideal field conditions, it could open up the possibility that the structural health monitoring community will be able to think beyond monitoring individual structures, to full-field structural integrity monitoring at the city scale.

Dasari, Sudeep↗
DOE OSTI2015

Analysis of Strand-Specific RNA-Seq Data Using Machine Learning Reveals the Structures of Transcription Units in Clostridium thermocellum

The identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Moreover, among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available athttps://code.google.com/p/seqtu/. We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.

09 BIOMASS FUELS↗
DOE OSTI2014

Risk Analysis Virtual ENvironment

RAVEN has 3 major functionalities: 1. Provides a Graphical User Interface for the pre- and post-processing of the RELAP-7 input and output. 2. Provides the capability to model nuclear power plants control logic for the RELAP-7 code and dynamic control of the accident scenario evolution. This capability is based on a software structure that realizes a direct connection between the RELAP-7 solver engine (MOOSE) and a python environment where the variables describing the plant status are accessible in a scripting environment. RAVEN support the generation of the probabilistic scenario control by supplying a wide range of probability and cumulative distribution functions and their inverse functions. 3. Provides a general environment to perform probability risk analysis for RELAP-7, RELAP-5 and any generic MOOSE based applications. The probabilistic analysis is performed by sampling the input space of the coupled code parameters and it is enhanced by using modern artificial intelligence algorithms that accelerate the identification of the areas of major risk (in the input parameter space). This environment also provides a graphical visualization capability to analyze the outcomes. Among other approaches, the classical Monte Carlo and Latin Hypercube sampling algorithms are available. For the acceleration of the convergence of the sampling methodologies, Support Vector Machines, Bayesian regression, and collocation stochastic polynomials chaos are implemented. The same methodologies here described could be used to solve optimization and uncertainties propagation problems using the RAVEN framework.

Rabiti, Cristian↗
DOE OSTI2025

Influence of isoelectronic mass modulation on phonon decay and transport in layered pnictogen-carbon systems

This study systematically investigates the structural, electronic, and thermal transport properties of layered pnictogen–carbon (Pn 2 C 2 ; Pn = P, As, Sb, Bi) monolayers, revealing a profound influence of isoelectronic mass modulation on phonon dynamics and thermal conductivity. Through first-principles calculations and lattice dynamics analysis, we demonstrate that increasing the atomic mass of pnictogens leads to elongated Pn-C bonds, weakened interatomic interactions, and enhanced phonon-phonon scattering, resulting in a dramatic reduction in lattice thermal conductivity (κ). Specifically, κ decreases exponentially from 65.6 W/m-K in P 2 C 2 to an ultralow 0.37 W/m-K in Bi 2 C 2 , driven by suppressed acoustic-optical phonon gaps Δ$^{Γ}_{A-0}$, increased anharmonicity, and reduced phonon lifetimes and group velocities. The transition from semiconducting to metallic behavior in heavier pnictogen-based systems further enhances phonon-electron scattering, contributing to thermal conductivity suppression. Structural analysis highlights the strengthening of out-of-plane C—C bonds and the contraction of C—Pn—C bond angles, which disrupt in-plane phonon transport. Further, these findings establish a design framework for engineering ultralow-κ materials through chemical substitution and structural tuning, offering significant potential for thermoelectric and thermal management applications. This work provides fundamental insights into phonon decay mechanisms and thermal transport in 2D materials, paving the way for advanced phononic and energy-efficient devices.

2D materials↗
DOE OSTI2015

Monte Carlo generators for studies of the 3D structure of the nucleon

In this study, extraction of transverse momentum and space distributions of partons from measurements of spin and azimuthal asymmetries requires development of a self consistent analysis framework, accounting for evolution effects, and allowing control of systematic uncertainties due to variations of input parameters and models. Development of realistic Monte-Carlo generators, accounting for TMD evolution effects, spin-orbit and quark-gluon correlations will be crucial for future studies of quark-gluon dynamics in general and 3D structure of the nucleon in particular.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Prediction of B1 to B10 phase transition in LuN under pressure: An ab-initio investigation

Ab-initio total energy calculations have been performed in lutetium nitride (LuN) as a function of hydrostatic compression to understand the high pressure behavior of this compound. Our calculations predict a phase transition from ambient rocksalt type structure (B1 phase) to a tetragonal structure (B10 phase) at ~ 240 GPa. The phase transition has been identified as first order in nature with volume discontinuity of ~ 6%. The predicted high pressure phase has been found to be stable up to at least 400 GPa, the maximum pressure up to which calculations have been performed.Further, to substantiate the results of static lattice calculations analysis of lattice dynamic stability of B1 and B10 phase has been carried out at different pressures. Apart from this, we have analyzed the lattice dynamic stability CsCl type (B2) phase around the 240 GPa, the pressure reported for B1 to B2 transition in previous all-electron calculations by Gupta et al. 2013. We find that the B2 structure is lattice dynamically unstable at this pressure and remains unstable up to ~ 400 GPa, ruling out the possibility of B1 to B2 phase transition at least up to ~ 400 GPa. Further, the theoretically determined equation of state has been utilized to derive various physical quantities such as zero pressure equilibrium volume, bulk modulus, and pressure derivative of bulk modulus of B1 phase at ambient conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Hygrothermal behavior of polybenzimidazole

Poly[2,2’-(m-phenylene)-5,5’-bibenzimidazole] (PBI) is used in extremely high temperature harsh environment applications. It is a unique engineering material that is formed into parts by powder-sintering at temperatures as high as 500 °C. Recently, ever increasing demands for high temperature polymers have led to significant interest in PBI such that engineering guidelines could be established for its application in high temperature and highly humid environments. The goal of this work was to understand the material science of PBI in hot-wet environments at temperatures up to 288 °C. Thermal gravimetric analysis and mass spectrometry were employed to identify the degraded volatile products. The molecular scale damping behavior of PBI was probed using dynamic mechanical analysis. The changes in tensile properties and fracture toughness due to environmental exposure were also characterized. Upon heating above 250 °C, moisture-containing PBI exhibits obvious molecular structure change. Evidence of crosslinking and degradation is observed. With 288 °C hot water treatment severe degradation of PBI is observed. As a result, fundamental structure-property relationships of PBI affected by these higher temperature, high moisture content environments are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Noncanonical folding of peptoid oligomers: Formation of a closed conformation in nonpolar solvent

Peptoids provide a versatile platform for foldamer design, yet their conformational behavior in low-dielectric media remains poorly understood. The structural characteristics of N-1-phenylethylglycine (Nspe) homo-oligomers were inves-tigated in chloroform, a solvent that mimics the interior of lipid bilayers, using nuclear magnetic resonance (NMR) spec-troscopy and molecular dynamics (MD) simulations. Nspe7 populated two distinct compact conformations, while Nspe10 adopted a single homogeneous conformation related to the previously reported Nspe9 threaded-loop structure. Integrated experimental and computational analysis reveals that these structures are stabilized by cooperative end-to-end intramo-lecular hydrogen bonding, cis-trans backbone isomerism, and hydrophobic side-chain shielding. The resulting structures minimize exposed polar surface area, demonstrating a closed conformation in the low-dielectric environment. These find-ings establish specific chain-length requirements for achieving well-defined closed conformations. This work provides insights into peptoid folding in nonpolar media, enabling rational design strategies for solvent-directed conformational switching systems.

Oh, Jinyoung↗
DOE OSTI2020

Stabilized Electrode/Electrolyte Interphase by a Saturated Ionic Liquid Electrolyte for High-Voltage NMC532/Si-Graphite Cells

Nonaqueous electrolyte has become one of the technical barriers in enabling Li-ion battery comprising of a high voltage cathode and high capacity anode. Here, we demonstrate a saturated piperidinum bis(fluorosulfonyl)imide ionic liquid (IL) with a LiFSI salt not only supports the redox reaction on the cathode at high voltages, but also shows exceptional kinetic stability on the lithiated anode as evidenced by its improved cycling performance in a NMC532/Si-graphite full cells cycled between 4.6 and 3.0 V. On the basis of the spectroscopic/microscopic analysis and molecular dynamics (MD) simulations, the superior performance of the cells is attributed to the formation of solid-electrolyte-interphase on both electrode as well as unique solvation structure where a deadlocked coordination network is established at the saturated state, which prevents transition metal dissolution into the electrolyte via a solvation process.

25 ENERGY STORAGE↗
DOE OSTI2017

Hallmarks of Hunds coupling in the Mott insulator Ca 2 RuO 4

A paradigmatic case of multi-band Mott physics including spin-orbit and Hund's coupling is realized in Ca2RuO4. Progress in understanding the nature of this Mott insulating phase has been impeded by the lack of knowledge about the low-energy electronic structure. Here we provide-using angle-resolved photoemission electron spectroscopy-the band structure of the paramagnetic insulating phase of Ca2RuO4 and show how it features several distinct energy scales. Comparison to a simple analysis of atomic multiplets provides a quantitative estimate of the Hund's coupling J=0.4 eV. Furthermore, the experimental spectra are in good agreement with electronic structure calculations performed with Dynamical Mean-Field Theory. The crystal field stabilization of the dxy orbital due to c-axis contraction is shown to be essential to explain the insulating phase. These results underscore the importance of multi-band physics, Coulomb interaction and Hund's coupling that together generate the Mott insulating state of Ca2RuO4.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

Ferroelectric, piezoelectric, and dielectric properties of BiScO{sub 3}-PbTiO{sub 3}-Pb(Cd{sub 1/3}Nb{sub 2/3})O{sub 3} ternary high temperature piezoelectric ceramics

(0.95-x)BiScO{sub 3}-xPbTiO{sub 3}-0.05Pb(Cd{sub 1/3}Nb{sub 2/3})O{sub 3} (BS-xPT-PCN) high temperature piezoelectric ceramics near the morphotropic phase boundary (MPB) have been synthesized by traditional solid-state reaction methods. The microstructural morphology, phase structure, and electrical properties of BS-xPT-PCN ceramics were investigated in detail. X-ray diffraction analysis indicated BS-xPT-PCN ceramics have a pure perovskite structure. The coexistence of rhombohedral and tetragonal phases at MPB composition enhanced the polarizability by the coupling between two dynamically equivalent energy states, resulting in the improved piezoelectric and ferroelectric properties at MPB vicinity. The BS-xPT-PCN (x = 0.60) ceramics possess the optimal piezoelectric and ferroelectric properties with d{sub 33} = 505pC/N, k{sub p} = 55.9%, k{sub t} = 36.5%, strain = 0.23% (under the electric field 37.5 kV/cm), and P{sub r} = 39.7 {mu}C/cm{sup 2}. High temperature dielectric behaviors showed diffuse phase transition in BS-xPT-PCN ceramics. The Curie temperature T{sub c} was found to increase from 371 Degree-Sign C to 414 Degree-Sign C with x increasing from 0.58 to 0.62. All these results together with the good thermal stabilities make the BS-xPT-PCN ceramics promising candidates for high temperature piezoelectric applications.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Effectiveness of organoclays as compatibilizers for multiphase polymer blends – A sustainable route for the mechanical recycling of co-mingled plastics

We prepare and characterize multiphase systems in which small amounts of recycled polymer, namely polyethylene terephtalate (PET) ground from waste bottles, are dispersed in a co-continuous blend of high-density polyethylene (HDPE) and polypropylene (PP). Some of such ternary systems are also filled with plate-like clay nanoparticles with different polarities, in order to assess their influence on the morphology and mechanical behaviour of the blends. On the basis of preliminary wettability considerations and inspections by means of scanning electron microscopy (SEM), the PET is found to preferentially locate within the PP phase. Such a positioning is desirable in order to minimize the presence of multiple interfaces, which is one of the major issues in the recycling process of co-mingles plastics. By means of SEM, dynamic-mechanical analysis and tensile tests we show that the addition of a filler with low polarity, which locates at the PET-matrix interface, has relevant implications on the structure and properties of the ternary systems, refining their morphology at the micro-scale and enhancing their high-temperature mechanical behaviour.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Revealing atomic-scale switching pathways in van der Waals ferroelectrics

Two-dimensional (2D) van der Waals (vdW) materials hold the potential for ultrascaled ferroelectric (FE) devices due to their silicon compatibility and robust polarization down to atomic scale. However, the inherently weak vdW interactions enable facile sliding between layers, introducing complexities beyond those encountered in conventional ferroelectric materials and presenting substantial challenges in uncovering intricate switching pathways. Here, we combine atomic-resolution imaging under in situ electrical biasing conditions with first-principles calculations to unravel the atomic-scale switching mechanisms in SnSe, a vdW group IV monochalcogenide. Our results uncover the coexistence of a consecutive 90° switching pathway and a direct 180° switching pathway from antiferroelectric (AFE) to FE order in this vdW system. Atomic-scale investigations and strain analysis reveal that the switching processes simultaneously induce interlayer sliding and compressive strain, while the lattice remains coherent despite the presence of multidomain structures. These findings elucidate vdW ferroelectric switching dynamics at atomic scale and lay the foundation for the rational design of 2D ferroelectric nanodevices.

Li, Xinyan [Rice University, Houston, TX (United S↗
DOE OSTI2016

SUNSPOT ROTATION AS A DRIVER OF MAJOR SOLAR ERUPTIONS IN THE NOAA ACTIVE REGION 12158

We studied the development conditions of sigmoid structure under the influence of the magnetic non-potential characteristics of a rotating sunspot in the active region (AR) 12158. Vector magnetic field measurements from the Helioseismic Magnetic Imager and coronal EUV observations from the Atmospheric Imaging Assembly reveal that the erupting inverse-S sigmoid had roots at the location of the rotating sunspot. The sunspot rotates at a rate of 0°–5° h{sup −1} with increasing trend in the first half followed by a decrease. The time evolution of many non-potential parameters had a good correspondence with the sunspot rotation. The evolution of the AR magnetic structure is approximated by a time series of force-free equilibria. The non-linear force-free field magnetic structure around the sunspot manifests the observed sigmoid structure. Field lines from the sunspot periphery constitute the body of the sigmoid and those from the interior overlie the sigmoid, similar to a flux rope structure. While the sunspot was rotating, two major coronal mass ejection eruptions occurred in the AR. During the first (second) event, the coronal current concentrations were enhanced (degraded), consistent with the photospheric net vertical current; however, magnetic energy was released during both cases. The analysis results suggest that the magnetic connections of the sigmoid are driven by the slow motion of sunspot rotation, which transforms to a highly twisted flux rope structure in a dynamical scenario. Exceeding the critical twist in the flux rope probably leads to the loss of equilibrium, thus triggering the onset of the two eruptions.

79 ASTRONOMY AND ASTROPHYSICS↗