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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Adjoint-optimized nanoscale light extractor for nitrogen-vacancy centers in diamond

Abstract We designed a nanoscale light extractor (NLE) for the efficient outcoupling and beaming of broadband light emitted by shallow, negatively charged nitrogen-vacancy (NV) centers in bulk diamond. The NLE consists of a patterned silicon layer on diamond and requires no etching of the diamond surface. Our design process is based on adjoint optimization using broadband time-domain simulations and yields structures that are inherently robust to positioning and fabrication errors. Our NLE functions like a transmission antenna for the NV center, enhancing the optical power extracted from an NV center positioned 10 nm below the diamond surface by a factor of more than 35, and beaming the light into a ±30° cone in the far field. This approach to light extraction can be readily adapted to other solid-state color centers.

42 ENGINEERING↗
DOE OSTI2017

Freely Expanding Knots of X-Ray-emitting Ejecta in Kepler’s Supernova Remnant

We report measurements of proper motion, radial velocity, and elemental composition for 14 compact X-ray-bright knots in Kepler’s supernova remnant (SNR) using archival Chandra data. The knots with the highest speed show both large proper motions ( μ ∼ 0.″11–0.″14 yr{sup −1}) and high radial velocities ( v ∼ 8700–10,020 km s{sup −1}). For these knots the estimated space velocities (9100 km s{sup −1} ≲ v {sub 3D} ≲ 10,400 km s{sup −1}) are similar to the typical Si velocity seen in supernovae (SNe) Ia near maximum light. High-speed ejecta knots appear only in specific locations and are morphologically and kinematically distinct from the rest of the ejecta. The proper motions of five knots extrapolate back over the age of Kepler’s SNR to a consistent central position. This new kinematic center agrees well with previous determinations, but is less subject to systematic errors and denotes a location about which several prominent structures in the remnant display a high degree of symmetry. These five knots are expanding at close to the free expansion rate (expansion indices of 0.75 ≲ m ≲ 1.0), which we argue indicates either that they were formed in the explosion with a high density contrast (more than 100 times the ambient density) or that they have propagated through regions of relatively low density ( n {sub H} < 0.1 cm{sup −3}) in the ambient medium. X-ray spectral analysis shows that the undecelerated knots have high Si and S abundances, a lower Fe abundance, and very low O abundance, pointing to an origin in the partial Si-burning zone, which occurs in the outer layer of the exploding white dwarf for models of SNe Ia. Other knots show lower speeds and expansion indices consistent with decelerated ejecta knots or features in the ambient medium overrun by the forward shock. Our new accurate location for the explosion site has well-defined positional uncertainties, allowing for a great reduction in the area to be searched for faint surviving donor stars under non-traditional single-degenerate SNe Ia scenarios; because of the lack of bright stars in the search area the traditional scenario remains ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Statistical Interpolation for Surface Reconstruction of PDV and BLR Data

Data collection is becoming more and more dense in dynamic experiments, requiring a variety of diagnostics. Data are detected through such means as holography, Mie scattering / extinction, assay foils, surface imaging, and high-speed photography. The data are measured by radiography, velocimetry, ranging, Fiber Bragg, and pyrometry. The question is how can we unify information from multiple diagnostics and incorporate uncertainties to tell a coherent story about an experiment in a meaningful way? This presentation provides an overview of statistical interpolation by means of Kriging. Kriging involves three basic steps: (1) compute and model covariance spatial structure; (2) compute weights by minimizing mean squared prediction error; and (3) predict at the desired prediction sites.

dynamic experiments, holography, Mie scattering/ex↗
DOE OSTI2018

Evaluating transition metal oxides within DFT-SCAN and SCAN + U frameworks for solar thermochemical applications

Using the strongly constrained and appropriately normed (SCAN) and SCAN+U approximations for describing electron exchange-correlation (XC) within density functional theory, we investigate the oxidation energetics, lattice constants, and electronic structure of binary Ce-, Mn-, and Fe-oxides, which are crucial ingredients for generating renewable fuels using two-step, oxide-based, solar thermochemical reactors. Unlike other common XC functionals, we find that SCAN does not over-bind the O 2 molecule, based on direct calculations of its bond energy and robust agreement between calculated formation enthalpies of main group oxides versus experiments. However, in the case of transition-metal oxides (TMOs), SCAN systematically overestimates (i.e., yields too negative) oxidation enthalpies due to remaining self-interaction errors in the description of their ground-state electronic structure. Adding a Hubbard U term to the transition-metal centers, where the magnitude of U is determined from experimental oxidation enthalpies, significantly improves the qualitative agreement and marginally improves the quantitative agreement of SCAN+U-calculated electronic structure and lattice parameters, respectively, with experiments. Importantly, SCAN predicts the wrong ground-state structure for a few oxides, namely, Ce 2 O 3 , Mn 2 O 3 , and Fe 3 O 4 , while SCAN+U predicts the right polymorph for all systems considered in this work. Furthermore, the SCAN+U framework, with an appropriately determined U, will be required to accurately describe ground-state properties and yield qualitatively consistent electronic properties for most transition-metal and rare earth oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

OPERATIONAL TOPOLOGY ESTIMATION OF THREE PHASE UNBALANCED POWER DISTRIBUTION SYSTEMS WITH OUTAGES

Distribution grid, in general, is constructionally loopy but a radially operated network. Opening and closing of suitable tie-switches allows transition from one radial topology to another. Tie-switches ensure reliability and provide restoration paths when faults (outages) occur. The estimation of the system's current operational topology is a precursor to implementing any optimal control actions (during normal operation) or restorative actions (during outage condition). The existing literature in topology detection suffers with several limitations including: (1) computationally intensive nonlinear formulations that are not scalable for large distribution systems, (2) methods requiring exhaustive search for the correct topology by enumerating the complete topological search space, and (3) approaches requiring large volumes of time-series measurements and are not applicable for estimating continuously changing operational topology. Furthermore, the existing literature on distribution grid topology estimation cannot be extended to estimate the operational topology during outage conditions. For operational topology estimation during outages, our objective is to estimate both energized radial feeder and the outaged sections. Starting with a radial topology, these methods identify outaged feeder sections and hence, are inapplicable when the current radial operational topology is not known. In this work, we present a mathematical programming approach to estimate the operational topology of a three-phase unbalanced power distribution system under both outage and normal operating conditions. The aforementioned limitations of existing literature were countered by modeling the problem as a mixed-integer linear programming (MILP) problem which minimizes the errors in available measurements while satisfying the power flow and structural constraints of the system. Specically, a minimum weighted least absolute value estimator is proposed that uses the instantaneous line flow measurements, historical/ forecasted load data, and ping measurements from a limited set of smart meters and solves an MILP to identify the operational topology based on a linearized three-phase unbalanced power flow model. The proposed approach is tested on IEEE 123-bus feeder and 1069 bus multi-feeder test system and the numerical results prove the applicability of the proposed method to large three phase unbalanced grids with high errors in measurements. It is observed that the approach performs well even at high percentages of measurement errors.

GANDLURU NAGA, ANANDINI↗
DOE OSTI2023

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗
DOE OSTI2016

An Adaptive Mesh Algorithm: Mesh Structure and Generation

The purpose of Adaptive Mesh Refinement is to minimize spatial errors over the computational space not to minimize the number of computational elements. The additional result of the technique is that it may reduce the number of computational elements needed to retain a given level of spatial accuracy. Adaptive mesh refinement is a computational technique used to dynamically select, over a region of space, a set of computational elements designed to minimize spatial error in the computational model of a physical process. The fundamental idea is to increase the mesh resolution in regions where the physical variables are represented by a broad spectrum of modes in k-space, hence increasing the effective global spectral coverage of those physical variables. In addition, the selection of the spatially distributed elements is done dynamically by cyclically adjusting the mesh to follow the spectral evolution of the system. Over the years three types of AMR schemes have evolved; block, patch and locally refined AMR. In block and patch AMR logical blocks of various grid sizes are overlaid to span the physical space of interest, whereas in locally refined AMR no logical blocks are employed but locally nested mesh levels are used to span the physical space. The distinction between block and patch AMR is that in block AMR the original blocks refine and coarsen entirely in time, whereas in patch AMR the patches change location and zone size with time. The type of AMR described herein is a locally refi ned AMR. In the algorithm described, at any point in physical space only one zone exists at whatever level of mesh that is appropriate for that physical location. The dynamic creation of a locally refi ned computational mesh is made practical by a judicious selection of mesh rules. With these rules the mesh is evolved via a mesh potential designed to concentrate the nest mesh in regions where the physics is modally dense, and coarsen zones in regions where the physics is modally sparse.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Design of a tapered slot waveguide dielectric laser accelerator for sub-relativistic electrons

We propose a dielectric laser accelerator design based on a tapered slot waveguide structure for sub-relativistic electron acceleration. This tapering scheme allows for straightforward tuning of the phase velocity of the accelerating field along the propagation direction, which is necessary for maintaining synchronization with electrons as their velocities increase. Furthermore, the non-resonant nature of this design allows for better tolerance to experimental errors. We also introduce a method to design this continuously tapered structure based on the eikonal approximation, and give a working example based on realistic experimental parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 450 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrates, they avoid calibration errors which can cause CCS accuracy problems and difficulties identifying structurally similar molecules. Furthermore, all measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites selected for the database are from key metabolism pathways such as glycolysis, the pentose phosphate pathway, and the tricarboxylic acid (TCA) cycle, while the secondary metabolites consist of classes such as terpenes and flavonoids, and the xenobiotics represent a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes, allowing insight in their separations and a possible why of classifying unknowns. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added monthly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Importance of elastic finite-size effects: Neutral defects in ionic compounds

Small system sizes are a well known source of error in DFT calculations, yet computational constraints frequently dictate the use of small supercells, often as small as 96 atoms in oxides and compound semiconductors. In ionic compounds, electrostatic finite size effects have been well characterised, but self-interaction of charge neutral defects is often discounted or assumed to follow an asymptotic behaviour and thus easily corrected with linear elastic theory. Here we show that elastic effect are also important in the description of defects in ionic compounds and can lead to qualitatively incorrect conclusions if inadequatly small supercells are used; moreover, the spurious self-interaction does not follow the behaviour predicted by linear elastic theory. Considering the exemplar cases of metal oxides with fluorite structure, we show that numerous previous studies, employing 96-atom supercells, misidentify the ground state structure of (charge neutral) Schottky defects. We show that the error is eliminated by employing larger cells (324, 768 and 1500 atoms), and careful analysis determines that elastic effects, not electrostatic, are responsible. The spurious self-interaction was also observed in non-oxide ionic compounds and irrespective of the computational method used, thereby resolving long standing discrepancies between DFT and force-field methods, previously attributed to the level of theory. The surprising magnitude of the elastic effects are a cautionary tale for defect calculations in ionic materials, particularly when employing computationally expensive methods (e.g. hybrid functionals) or when modelling large defect clusters. We propose two computationally practicable methods to test the magnitude of the elastic self-interaction in any ionic system. In commonly studies oxides, where electrostatic effects would be expected to be dominant, it is the elastic effects that dictate the need for larger supercells | greater than 96 atoms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Maximizing machine learning interatomic potential transferability for the discovery of the novel stellated octadecagon Bi18-Pt24 cage structure

Achieving true transferability remains the central challenge for Machine Learning Interatomic Potentials (ML-IAPs) in modeling complex bimetallic nanoclusters across their vast potential energy surfaces. We systematically investigate data selection strategies to optimize the Chebyshev Interaction Model for Efficient Simulation (ChIMES) potential for the Bi-Pt nanoclusters by comparing three innovative sampling methods: Principal Component Analysis (PCA)/k-means (structural diversity), t-distributedStochasticNeighborEmbedding (t-SNE)/k-means (force-space diversity), and hierarchical clustering. Quantitatively, the PCA/k-means strategy proved most effective for global accuracy, yielding the lowest force errors and achieving energy root mean square errors (RMSE) values competitive with Density Functional Theory (DFT), demonstrating excellent accuracy (19.16meV/atom). Structural validation on 34 unique DFT-optimized isomers further confirmed the potential’s high fidelity, with the best model PCA/k-means reproducing structures with an average root mean square deviation (RMSD) of 0.10 Å. However, the t-SNE methods, by maximizing diversity in the force space, demonstrated superior extrapolative power, leading to the more precise prediction of a novel stellated octadecagon Bi18⁢Pt24 cage structure, demonstrating the potential for exploring previously unseen morphologies. Our results establish a clear methodology for strategic data sampling that successfully maximizes ML-IAP transferability, providing an accurate and computationally efficient tool that accelerates the theoretical discovery of complex bimetallic architectures.

Vangheluwe, Raphaël [Université Paris-Saclay, CNRS↗
DOE OSTI2017

Canonical symplectic structure and structure-preserving geometric algorithms for Schrödinger–Maxwell systems

An infinite dimensional canonical symplectic structure and structure-preserving geometric algorithms are developed for the photon–matter interactions described by the Schrödinger–Maxwell equations. The algorithms preserve the symplectic structure of the system and the unitary nature of the wavefunctions, and bound the energy error of the simulation for all time-steps. This new numerical capability enables us to carry out first-principle based simulation study of important photon–matter interactions, such as the high harmonic generation and stabilization of ionization, with long-term accuracy and fidelity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: N-body Mock Challenge for Galaxy Clustering Measurements

We develop a series of N-body data challenges, functional to the final analysis of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) galaxy sample. The challenges are primarily based on high-fidelity catalogues constructed from the Outer Rim simulation - a large box size realization (3h(-1) Gpc) characterized by an unprecedented combination of volume and mass resolution, down to 1.85 x 10(9) h(-1)M(circle dot). We generate synthetic galaxy mocks by populating Outer Rim haloes with a variety of halo occupation distribution (HOD) schemes of increasing complexity, spanning different redshift intervals. We then assess the performance of three complementary redshift space distortion (RSD) models in configuration and Fourier space, adopted for the analysis of the complete DR16 eBOSS sample of Luminous Red Galaxies (LRG5). We find all the methods mutually consistent, with comparable systematic errors on the Alcock-Paczynski parameters and the growth of structure, and robust to different HOD prescriptions - thus validating the robustness of the models and the pipelines used for the baryon acoustic oscillation (BAO) and full shape clustering analysis. In particular, all the techniques are able to recover and alpha(11) to within 0.9 per cent, and f sigma(8) to within 1.5 per cent. As a by-product of our work, we are also able to gain interesting insights on the galaxy-halo connection. Our study is relevant for the final eBOSS DR16 'consensus cosmology', as the systematic error budget is informed by testing the results of analyses against these high-resolution mocks. In addition, it is also useful for future large-volume surveys, since similar mock-making techniques and systematic corrections can be readily extended to model for instance the Dark Energy Spectroscopic Instrument (DESI) galaxy sample.

cosmology: theory, large-scale structure of Univer↗
DOE OSTI2016

Interfacial Atomic Structure of Twisted Few-Layer Graphene

A twist in bi- or few-layer graphene breaks the local symmetry, introducing a number of intriguing physical properties such as opening new bandgaps. Therefore, determining the twisted atomic structure is critical to understanding and controlling the functional properties of graphene. Combining low-angle annular dark-field electron microscopy with image simulations, we directly determine the atomic structure of twisted few-layer graphene in terms of a moiré superstructure which is parameterized by a single twist angle and lattice constant. This method is shown to be a powerful tool for accurately determining the atomic structure of two-dimensional materials such as graphene, even in the presence of experimental errors. Using coincidence-site-lattice and displacement-shift-complete theories, we show that the in-plane translation state between layers is not a significant structure parameter, explaining why the present method is adequate not only for bilayer graphene but also a few-layered twisted graphene.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Signal-Compensation-Based Adaptive PID Control for Fused Magnesia Smelting Processes

For fused magnesia smelting processes, the proportional-integral-derivative (PID) controller is difficult to regulate the smelting currents within desired ranges due to unexpected variations of the dynamics caused by material feeding operations. To solve this problem, we first proposed its dynamic model composed of a linear model and an uncertain nonlinear dynamic system that describes the unknown time-varying dynamics of nonlinearity and strong couplings among controlled variables. Then, using the accurately calculated value of the uncertain part at the previous sampling time instant and the tracking error that reflects the influence of its change rate, we developed a feedforward and a one-step optimal control to obtain two signal compensators to eliminate the impact of frequent variations of the uncertainties. For the compensators, we proposed a weight selection method to minimize the sum of the squared tracking error with ensured closed-loop stability. Based on the abovementioned modeling and control structure, we finally developed a novel adaptive PID controller augmented with signal compensators to control the whole process. Industrial applications have shown that the proposed method can always keep the tracking error and the control input within their targeted ranges, leading to a significantly reduced energy consumption per ton and increased fused magnesia production.

Wang, Weizhou↗
DOE OSTI2016

Comparison of weak lensing by NFW and Einasto halos and systematic errors

Recent N-body simulations have shown that Einasto radial profiles provide the most accurate description of dark matter halos. Predictions based on the traditional NFW functional form may fail to describe the structural properties of cosmic objects at the percent level required by precision cosmology. We computed the systematic errors expected for weak lensing analyses of clusters of galaxies if one wrongly models the lens density profile. Even though the NFW fits of observed tangential shear profiles can be excellent, viral masses and concentrations of very massive halos (∼> 10{sup 15}M{sub ⊙}/h) can be over- and underestimated by 0∼ 1 per cent, respectively. Misfitting effects also steepen the observed mass-concentration relation, as observed in multi-wavelength observations of galaxy groups and clusters. Based on shear analyses, Einasto and NFW halos can be set apart either with deep observations of exceptionally massive structures (∼> 2×10{sup 15}M{sub ⊙}/h) or by stacking the shear profiles of thousands of group-sized lenses (∼> 10{sup 14}M{sub ⊙}/h)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quality control of mislocalized and orphan proteins

A healthy and functional proteome is essential to cell physiology. However, this is constantly being challenged as most steps of protein metabolism are error-prone and changes in the physico-chemical environment can affect protein structure and function, thereby disrupting proteome homeostasis. Among a variety of potential mistakes, proteins can be targeted to incorrect compartments or subunits of protein complexes may fail to assemble properly with their partners, resulting in the formation of mislocalized and orphan proteins, respectively. Quality control systems are in place to handle these aberrant proteins, and to minimize their detrimental impact on cellular functions. Here, we discuss recent findings on quality control mechanisms handling mislocalized and orphan proteins. We highlight common principles involved in their recognition and summarize how accumulation of these aberrant molecules is associated with aging and disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

Chemistry↗