Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “feature exploration”

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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Open string amplitudes: singularities, asymptotics and new representations

Open string amplitudes at tree level have been studied for over fifty years. However, there is no known analytic form for general n-point amplitudes, and their conventional representation in terms of worldsheet integrals does not make many of their most basic physical properties manifest. Recently, a formulation of these amplitudes exposing the underlying “binary geometry” via the use of “u” variables has given us many insights into their basic features. In this paper, we initiate a systematic exploration of fundamental aspects of open string amplitudes from this new point of view. We begin by finding explicit expressions for the factorization of amplitudes at general massive levels, which are seen to be determined by products of lower-point massless amplitudes with shifted kinematics. We then study the asymptotic behavior when subsets of kinematic variables become large, delineating regimes with exponential (generalized hard scattering) and power-law (generalized Regge) behavior. We also give precise expressions for the asymptotics, which reveal another example of the recently observed property of factorization away from poles. We derive new recursion relations for the amplitude, which when repeatedly applied reduce to infinite series representations with a wider domain of convergence than the usual integral representations. For the five-point case, we present a new closed-form expression for the amplitude that for the first time gives its analytic continuation to all of kinematic space. We also discuss novel relations between amplitudes at different kinematic points following from the recently observed “split” factorizations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Strategies for design and synthesis of porous liquids toward carbon capture and separation

Porous liquids (PLs) represent a promising category of sorbents in carbon capture and separation capable of integrating the advantages of flowing liquid and porous solid systems. Well-defined pores were engineered into liquid sorbents via liquifying molecules with stiff interior voids, dissolving rigid porous hosts in flowing liquids, or dispersing porous frameworks in high steric hindrance solvents, producing type I, II, or III PLs, respectively. Unique features of PLs have triggered broad interest in exploring their applications in carbon capture and separation, in which diverse design strategies, synthesis approaches, and enhanced performance have been reported. Here, in this minireview, recent progress in the design, synthesis, and structural engineering of PLs and efforts towards the optimization of their carbon capture and separation behavior will be summarized, including the comparison between PLs with varied types. Porosity engineering into liquid sorbents provides opportunities to resolve challenging issues in conventional sorption and separation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

First-Principles Approach to Extracting Chemical Information from X-ray Absorption Near-Edge Spectra of Ga-Containing Materials

The X-ray absorption near-edge structure (XANES) can provide uniquely detailed information on the coordination environments of important Ga-containing materials with unknown structures, including catalytically active materials. In this work, the Ga K-edge XANES was simulated using first-principles-based methods for seven molecular Ga complexes as well β-Ga 2 O 3 , in order to explore the chemical origins of the experimentally observed features. The theoretical spectra were computed using FEFF, CASTEP, and StoBe, to assess the sensitivity of the results to the computational approach. While the XANES features depend on the Ga coordination environment, they are also sensitive to the electronegativity of the ligands and the symmetry at Ga. The white line position responds to changes in both the core state (due to differential screening) and the valence “p” states (arising from differences in ligand coordination).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Water Promotion (or Inhibition) of Condensation Reactions Depends on Exposed Cerium Oxide Catalyst Facets

Nanoparticles with well-defined facets enable quantitative correlations between surface features and catalytic activity. In this work, we explore the role of geometric and acid–base properties in the mechanism of aldol condensation catalyzed by ceria nanoshapes. In the crucial C–C coupling step, the two carbonyl adsorbates are bound to two adjacent cations. On the CeO 2 (110) plane, all atoms lie on the same layer, favoring the interaction between adsorbates and facilitating the bimolecular C–C coupling. Thus, the initial unimolecular deprotonation is rate-limiting. In contrast, the (100) and (111) planes have an open structure with O on the top layer and Ce on the layer below. The former O layer interferes between adsorbates linked to Ce sites, making the C–C coupling rate-limiting. Water helps in overcoming this spatial hindrance by remote bond polarization via H-bonds. Therefore, water promotion is only observed on those planes for which the bimolecular step is rate-limiting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗
DOE OSTI2020

In situ nanoscale imaging of moiré superlattices in twisted van der Waals heterostructures

Abstract Direct visualization of nanometer-scale properties of moiré superlattices in van der Waals heterostructure devices is a critically needed diagnostic tool for study of the electronic and optical phenomena induced by the periodic variation of atomic structure in these complex systems. Conventional imaging methods are destructive and insensitive to the buried device geometries, preventing practical inspection. Here we report a versatile scanning probe microscopy employing infrared light for imaging moiré superlattices of twisted bilayers graphene encapsulated by hexagonal boron nitride. We map the pattern using the scattering dynamics of phonon polaritons launched in hexagonal boron nitride capping layers via its interaction with the buried moiré superlattices. We explore the origin of the double-line features imaged and show the mechanism of the underlying effective phase change of the phonon polariton reflectance at domain walls. The nano-imaging tool developed provides a non-destructive analytical approach to elucidate the complex physics of moiré engineered heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Towards automating structural discovery in scanning transmission electron microscopy *

Abstract Scanning transmission electron microscopy is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric domain walls, extended defects, or second phase inclusions. Selecting regions to image for structural and chemical discovery via atomically resolved imaging has traditionally proceeded via human operators making semi-informed judgements on sampling locations and parameters. Recent efforts at automation for structural and physical discovery have pointed towards the use of ‘active learning’ methods that utilize Bayesian optimization with surrogate models to quickly find relevant regions of interest. Yet despite the potential importance of this direction, there is a general lack of certainty in selecting relevant control algorithms and how to balance a priori knowledge of the material system with knowledge derived during experimentation. Here we address this gap by developing the automated experiment workflows with several combinations to both illustrate the effects of these choices and demonstrate the tradeoffs associated with each in terms of accuracy, robustness, and susceptibility to hyperparameters for structural discovery. We discuss possible methods to build descriptors using the raw image data and deep learning based semantic segmentation, as well as the implementation of variational autoencoder based representation. Furthermore, each workflow is applied to a range of feature sizes including NiO pillars within a La:SrMnO 3 matrix, ferroelectric domains in BiFeO 3 , and topological defects in graphene. The code developed in this manuscript is open sourced and will be released at github.com/nccreang/AE_Workflows .

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Novel machine-learning method for spin classification of neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonant structure whose shape is determined in part by the angular-momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is, therefore, paramount. In this project, we apply machine learning to automate the quantum number assignments using only the resonances' energies and widths and not relying on detailed transmission or capture measurements. The classifier used for quantum number assignment is trained using stochastically generated resonance sequences whose distributions mimic those of real data. Here we explore the use of several physics-motivated features for training our classifier. These features amount to out-of-distribution tests of a given resonance's widths and resonance-pair spacings. We pay special attention to situations where either capture widths cannot be trusted for classification purposes or where there is insufficient information to classify resonances by the total spin J. We demonstrate the efficacy of our classification approach using simulated and actual 52 Cr resonance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Multiple origins of extra electron diffractions in fcc metals

Diffuse intensities in the electron diffraction patterns of concentrated face-centered cubic solid solutions have been widely attributed to chemical short-range order, although this connection has been recently questioned. This article explores the many nonordering origins of commonly reported features using a combination of experimental electron microscopy and multislice diffraction simulations, which suggest that diffuse intensities largely represent thermal and static displacement scattering. A number of observations may reflect additional contributions from planar defects, surface terminations incommensurate with bulk periodicity, or weaker dynamical effects.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning applied to classifying neutron resonances

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit resonance structure whose shape is determined in part by the angular momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. In this project, we apply a machine learning technique, namely decision trees, to automate the quantum number assignments. The tree is trained from simulated data generated to mimic the errors found in real data. We explore the use of several physics-motivated features for training our trees, including the nearest neighbor spacing distribution, cumulative level distribution, and channel width distributions. Initial results using random matrix theory motivated fits which demonstrated that we can determine resonance spin groups somewhat reliably. If we use these fits as features in our trees, we can train them to spot outliers corresponding to misassigned resonances. We found that with the large number of features used in this project that the decision tree tended to over t training data resulting in poor performance with respect to the test data. By reducing the number of features, we can achieve nearly perfect assignment of quantum numbers with our training data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Discovery of highly ionized species in the ultraviolet spectrum of Feige 24

A high-resolution ultraviolet spectrum of the nearby (90 pc) white dwarf binary Feige 24 (DA + M1-2 V) obtained with the International Ultraviolet Explorer satellite (IUE) reveals two sets of absorption features in the species C IV, Si IV, and N V. The low-velocity component (V approximately 1 km/s) arises from the local interstellar gas apparently ionized by the white dwarf. The second component, at high velocities (V approximately +83 km/s), arises in the atmosphere of the white dwarf in the Feige 24 system. The presence of this large velocity shift supplies the first strong evidence for narrow absorption cores due to high-temperature species in a white dwarf atmosphere. Observations around the orbital period will provide a direct measurement of the gravitational redshift and the mass of the white dwarf. The inferred hydrogen density is 0.008 per cu cm toward this source.

Dupree, A. K.↗
NASA NTRS1986

A viscoplastic constitutive theory for metal matrix composites at high temperature

A viscoplastic constitutive theory is presented for representing the high-temperature deformation behavior of metal matrix composites. The point of view taken is a continuum one where the composite is considered a material in its own right, with its own properties that can be determined for the composite as a whole. It is assumed that a single preferential (fiber) direction is identifiable at each material point (continuum element) admitting the idealization of local transverse isotropy. A key ingredient in this work is the specification of an experimental program for the complete determination of the material functions and parameters for characterizing a particular metal matrix composite. The parameters relating to the strength of anisotropy can be determined through tension/torsion tests on longitudinally and circumferentially reinforced thin-walled tubes. Fundamental aspects of the theory are explored through a geometric interpretation of some basic features analogous to those of the classical theory of plasticity.

Robinson, D. N.↗
NASA NTRS1988

A viscoplastic constitutive theory for metal matrix composites at high temperature

A viscoplastic constitutive theory is presented for representing the high temperature deformation behavior of metal matrix composites. The point of view taken is a continuum one where the composite is considered a material in its own right, with its own properties that can be determined for the composite as a whole. It is assumed that a single preferential (fiber) direction is identifiable at each material point (continuum element) admitting the idealization of local transverse isotropy. A key ingredient is the specification of an experimental program for the complete determination of the material functions and parameters for characterizing a particular metal matrix composite. The parameters relating to the strength of anisotropy can be determined through tension/torsion tests on longitudinally and circumferentially reinforced thin walled tubes. Fundamental aspects of the theory are explored through a geometric interpretation of some basic features analogous to those of the classical theory of plasticity.

Robinson, David N.↗
NASA NTRS1987

A viscoplastic constitutive theory for metal matrix composites at high temperature

A viscoplastic theory is presented for representing the high-temperature deformation behavior of metal matrix composites. The point of view taken is a continuum one where the composite is considered a material in its own right, with its own properties that can be determined for the composite as a whole. It is presumed that a single preferential (fiber) direction is identifiable at each material point (continuum element) admitting the idealization of local transverse isotropy. A key ingredient in this work is the specification of an experimental program for the complete determination of the material functions and parameters for characterizing a particular metal matrix composite. The parameters relating to the strength of anisotropy can be determined through tension/torsion tests on longitudinally and circumferentially reinforced thin-walled tubes. Fundamental aspects of the theory are explored through a geometric interpretation of some basic features analogous to those of the classical theory of plasticity.

Robinson, D. N.↗
NASA NTRS1990

Camera artifacts in IUE low-dispersion spectra

Sky-background images obtained by the International Ultraviolet Explorer (IUE) were analyzed to study artificial spectral features (camera artifacts) in low-dispersion spectra. The artifacts mimic emission features and have been present in long-exposure spectra since the launch of the IUE satellite. The camera artifacts are strong in spectra characterized by long exposure times because they scale in time-integrated flux with the background level, which increases during the exposure due to camera phosphorescence. The artifacts cannot be detected in spectra obtained from short, direct exposures of flat-field lamps or standard stars. Plots of average sky-background spectra for the three operational IUE cameras (SWP, LWP, and LWR) are given to aid scientists in the identification of artifacts in their spectra.

Crenshaw, D. Michael↗
NASA NTRS1990

Mapping photopolarimeter spectrometer instrument feasibility study for future planetary flight missions

Evaluations are summarized directed towards defining optimal instrumentation for performing planetary polarization measurements from a spacecraft platform. An overview of the science rationale for polarimetric measurements is given to point out the importance of such measurements for future studies and exploration of the outer planets. The key instrument features required to perform the needed measurements are discussed and applied to the requirements for the Cassini mission to Saturn. The resultant conceptual design of a spectro-polarimeter photometer for Cassini is described in detail.

Source record↗
NASA NTRS2001

Input Decimated Ensembles

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

Tumer, Kagan↗