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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Kink band and shear band localization in anisotropic perfectly plastic solids

Shear-driven strain localization has been observed in a wide variety of materials and may take the form of shear bands or kink bands. Based on observations of kink bands in plastically anisotropic metallic nanolaminates and single crystal metals, here we posit that, for the specific case of isochoric deformation, the kinematics of kink band formation are indistinguishable from those of plane strain shear band formation. The only distinction between shear bands and kink bands in these systems would then be that kink bands ‘lock up’ at a particular value of material rotation while shear bands may progress to arbitrarily high strains. In order to investigate whether strong material anisotropy is sufficient to arrest shear localization at a geometry that matches the classic kink band geometry, we model the development of a band of simple shear within an anisotropic perfectly plastic material. The resulting analytical model provides the stress state needed to maintain the kinematics of simple shear as a function of material anisotropy, deformation band orientation, and shear strain (or equivalently, material rotation). It is found that plastic anisotropy can promote either kink band or shear band formation depending on the loading orientation. When the deviatoric stress is positive parallel to the plane of anisotropy, shear localization may progress without bound and a shear band is produced. When the deviatoric stress is negative parallel to the plane of anisotropy, shear localization is arrested after a certain material rotation, resulting in a kink band. Examination of the requisite applied stress state during kink band formation provides an explanation for the experimentally-observed ‘lock up’ geometry. Solutions for the band boundary inclination angle are obtained and used to provide bounds on permissible band angles for both shear bands and kink bands.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation

The detection and localization of damage in metallic structures using acoustic emission (AE) monitoring and artificial intelligence technology such as deep learning has been widely studied. However, a current challenge of this approach is the difficulty of obtaining sufficient labeled historical AE signals for the training process of deep learning models. This problem can be approached through the implementation of transfer learning. The innovation of this paper lies in the development of a transfer learning approach for AE source localization on a stainless-steel structure when no historical labeled AE signals are available for training. A finite element model is developed to generate numerical AE signals for the training. Unsupervised domain adaptation (UDA) technology is utilized to reduce the distribution difference between the numerical and the realistic AE signals and to derive the localization results of the unlabeled realistic AE signals. Finally, the results suggest that the proposed approach is capable of localizing AE signals with high accuracy in the absence of labeled training data.

42 ENGINEERING↗
DOE OSTI2024

Core/Shell-Like Localized Emission at Atomically Thin Semiconductor–Au Interface

Localized emission in atomically thin semiconductors has sparked significant interest as single-photon sources. Despite comprehensive studies into the correlation between localized strain and exciton emission, the impacts of charge transfer on nanobubble emission remains elusive. Here, in this paper, we report the observation of core/shell-like localized emission from monolayer WSe 2 nanobubbles at room temperature through near-field studies. By altering the electronic junction between monolayer WSe 2 and the Au substrate, one can effectively adjust the semiconductor to metal junction from a Schottky to an Ohmic junction. Through concurrent analysis of topography, potential, tip-enhanced photoluminescence, and a piezo response force microscope, we attribute the core/shell-like emissions to strong piezoelectric potential aided by induced polarity at the WSe 2 –Au Schottky interface which results in spatial confinement of the excitons. Our findings present a new approach for manipulating charge confinement and engineering localized emission within atomically thin semiconductor nanobubbles. These insights hold implications for advancing the nano and quantum photonics with low-dimensional semiconductors.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Localization dynamics in a centrally coupled system

In systems in which interactions couple a central degree of freedom and a bath, one would expect signatures of the bath's phase to be reflected in the dynamics of the central degree of freedom. This has been recently explored in connection with many-body localized baths coupled with a central qubit or a single-cavity mode - systems with growing experimental relevance in various platforms. Such models also have an interesting connection with Floquet many-body localization via quantizing the external drive, although this has been relatively unexplored. Here we adapt the multilayer multiconfigurational time-dependent Hartree (ML-MCTDH) method, a well-known tree tensor network algorithm, to numerically simulate the dynamics of a central degree of freedom, represented by a d-level system (qudit), coupled to a disordered interacting one-dimensional spin bath. ML-MCTDH allows us to reach ≈10 2 lattice sites, a far larger system size than what is feasible with exact diagonalization or kernel polynomial methods. From the intermediate time dynamics, we find a well-defined thermodynamic limit for the qudit dynamics upon appropriate rescaling of the system-bath coupling. The spin system shows similar scaling collapse in the Edward-Anderson spin-glass order parameter or entanglement entropy at relatively short times. At longer timescales, we see slow growth of the entanglement, which may arise from dephasing mechanisms in the localized system or long-range interactions mediated by the central degree of freedom. Similar signs of localization are shown to appear as well with unscaled system-bath coupling.

1-dimensional spin chains↗
DOE OSTI2024

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Improved Localization Precision and Angular Resolution of a Cylindrical, Time-Encoded Imaging System From Adaptive Detector Movements

To the first order, the localization precision and angular resolution of a cylindrical, time-encoded imaging (c-TEI) system is governed by the geometry of the system. Improving either measure requires increasing the mask radius or decreasing the detector diameter, both of which are undesirable. Here, we propose an alternative option of repositioning the detector within the mask to increase the detector-to-mask distance in the direction of a source, thereby improving the localization precision and angular resolution in that direction. Since the detector-to-mask distance only increases for a small portion of the field of view (FOV), we propose implementing adaptive imaging where one leverages data collected during the measurement to optimize the system configuration. This article utilizes both simulations and experiments to set upper bounds on the potential gain from adaptive detector movements for one and two sources in the FOV. When only one source is present, adaptive detector movements can improve the localization precision and angular resolution by 20% for a source at 90 cm and by 32% for a far-field source. When two sources are present, adaptive detector movements can improve localization precision and angular resolution by up to 50% for sources that are ~10° apart (90 cm from the system). We experimentally verify these results through maximum likelihood estimation of the source position(s) and image reconstruction of point sources that are close together. As a demonstration of an adaptive imaging algorithm, we image a complex arrangement of special nuclear material at the Zero Power Physics Reactor facility at Idaho National Laboratory.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2022

Adaptive Hierarchical Cyber Attack Detection and Localization in Active Distribution Systems

Development of a cyber security strategy for the active distribution systems is challenging due to the inclusion of distributed renewable energy generations. Here this paper proposes an adaptive hierarchical cyber attack detection and localization framework for distributed active distribution systems via analyzing electrical waveforms. Cyber attack detection is based on a sequential deep learning model, via which even minor cyber attacks can be identified. The two-stage cyber attack localization algorithm first estimates the cyber attack sub-region, and then localize the specified cyber attack within the estimated subregion. We propose a modified spectral clustering-based network partitioning method for the hierarchical cyber attack ‘coarse’ localization. Next, to further narrow down the cyber attack location, a normalized impact score based on waveform statistical metrics is proposed to obtain a ‘fine’ cyber attack location by characterizing different waveform properties. Finally, compared with classical and state-of-art methods, a comprehensive quantitative evaluation with two case studies shows promising estimation results of the proposed framework.

42 ENGINEERING↗
DOE OSTI2025

Signatures of local nitrogen adaptation in the Brachypodium distachyon root microbiome

Plants associate with diverse microbiomes that impact their fitness, yet the contribution of the microbiome to plant adaptation is uncertain. As plant recruitment of its microbiome can be both highly variable and genetically determined, we hypothesized this recruitment process may be the result of adaptive evolution, and contributing to plant local adaptation. We investigated the evolution and adaptive benefit of plant–microbiome recruitment by characterizing the rhizosphere communities across a genotypic panel of Brachypodium distachyon in a common garden experiment. By linking microbial communities to their host genotype's historic environment, we identified signatures of selection on plant–microbiome recruitment. Plant–microbiome composition was significantly correlated with the host genotype's historic environment, with enrichment of microbial traits aligned to local resource conditions. For example, genotypes from low-nitrogen environments recruited communities enriched in nitrogen acquisition traits. In a complementary experiment evaluating plant nitrogen response, these same genotypes were well-adapted to low-nitrogen environments, contingent on the presence of key nitrogen-cycling microbes. These results suggest that local adaptation in plants may partially be mediated by recruitment of beneficial microbiomes. This perspective suggests that plant adaptation may be an emergent property of host–microbe interactions, where evolutionary responses favor traits that promote recruitment of locally beneficial microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis

Local Fourier analysis is a useful tool for predicting and analyzing the performance of many efficient algorithms for the solution of discretized PDEs, such as multigrid and domain decomposition methods. The crucial aspect of local Fourier analysis is that it can be used to minimize an estimate of the spectral radius of a stationary iteration, or the condition number of a preconditioned system, in terms of a symbol representation of the algorithm. In practice, this is a “minimax” problem, minimizing with respect to solver parameters the appropriate measure of work, which involves maximizing over the Fourier frequency. Often, several algorithmic parameters may be determined by local Fourier analysis in order to obtain efficient algorithms. Analytical solutions to minimax problems are rarely possible beyond simple problems; the status quo in local Fourier analysis involves grid sampling, which is prohibitively expensive in high dimensions. In this paper, we propose and explore optimization algorithms to solve these problems efficiently. Finally, several examples, with known and unknown analytical solutions, are presented to show the effectiveness of these approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Insights into Plastic Localization by Crystallographic Slip from Emerging Experimental and Numerical Approaches

Advanced experimental and numerical approaches are being developed to capture the localization of plasticity at the nanometer scale as a function of the multiscale and heterogeneous microstructure present in metallic materials. These innovative approaches promise new avenues to understand microstructural effects on mechanical properties, accelerate alloy design, and enable more accurate mechanical property prediction. This article provides an overview of emerging approaches with a focus on the localization of plasticity by crystallographic slip. New insights into the mechanisms and mechanics of strain localization are addressed. The consequences of the localization of plasticity by deformation slip for mechanical properties of metallic materials are also detailed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Emergence of Local Magnetic Moment in Ternary TaWSe 2 Single Crystal via Atomic Clustering

Ternary transition metal dichalcogenides (TMDs) provide a versatile platform to explore novel electronic and magnetic ground states via compositional substitution and local structural modulations. Using a combination of scanning tunneling microscopy and spectroscopy (STM/S), magnetic property measurements, and density functional theory (DFT) calculations, the emergence of local magnetic moments driven by the clustering of Ta atoms in ternary TaWSe 2 single crystals is analyzed. STM topography reveals triangular clusters of Ta atoms embedded within W-rich regions of TaWSe 2 . These clusters exhibit a consistent shape and an orderly arrangement throughout the surfaces. DFT calculations show that these Ta clusters induce local strain, giving rise to localized magnetic moments. The magnetic behavior is further corroborated by temperature-dependent magnetization measurements, which exhibit a magnetic anomaly at ∼50 K. In conclusion, this study offers a pathway to engineer magnetism in TMD systems with potential applications in spintronic and quantum materials.

DFT↗
DOE OSTI2024

Local Chemical Enhancement and Gating of Organic Coordinated Ionic-Electronic Transport

Superior properties in organic mixed ionic-electronic conductors (OMIECs) over inorganic counterparts have inspired intense interest in biosensing, soft-robotics, neuromorphic computing, and smart medicine. However, slow ion transport relative to charge transport in these materials is a limiting factor. Here, it is demonstrated that hydrophilic molecules local to an interfacial OMIEC nanochannel can accelerate ion transport with ion mobilities surpassing electrophoretic transport by more than an order of magnitude. Furthermore, ion access to this interfacial channel can be gated through local surface energy. This mechanism is applied in a novel sensing device, which electronically detects and characterizes chemical reaction dynamics local to the buried channel. The ability to enhance ion transport at the nanoscale in OMIECs as well as govern ion transport through local chemical signaling enables new functionalities for printable, stretchable, and biocompatible mixed conduction devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Probing and Tuning Strain‐Localized Exciton Emission in 2D Material Bubbles at Room Temperature

In monolayer transition metal dichalcogenides bubbles-nanoscale deformations typically exhibiting a dome-like shape-Excitons are confined by the strain effect, which exhibits extraordinary emission properties, such as single photon generation, enhanced light emission, and spectrally tunable excitonic states. While the strain profiles of these bubbles are extensively studied, this work provides an approach 1) to directly visualize the associated exciton properties in bubbles formed in WSe2 monolayer, revealing an intrinsic emission wavelength shift of ≈40 nm, and 2) actively modify local strain, enabling further exciton emission tuning over a range of 50 nm. These are achieved by emission mapping and nanoindentation using a dielectric near-field probe, which enables the detection of local emission spectra and emission lifetimes within individual bubbles. Statistical analysis of 67 bubbles uncovers an emission wavelength distribution centered around 780 nm. Furthermore, saturation behavior in the power-dependent studies and the associated lifetime change reveal the localized nature of the strain-induced states. These findings provide direct insights into the strain-localized emission dynamics in bubbles and establish a robust framework for non-destructive, reversible, and predictable nanoscale emission control, presenting a potential avenue for developing next-generation tunable quantum optical sources.

2D materials bubbles↗
DOE OSTI2026

Demystifying Piecewise and Localized Scatter Correction Methods

Multiplicative scatter is a common source of noise in near-infrared spectroscopy and other related instrumental techniques. A wide variety of methods are commonly used for the correction of multiplicative scatter. However, the majority of such methods assume that the parameters that describe the scatter are constant throughout the measured spectrum, which is often not the case. This work investigates a family of methods that perform scatter correction using local regions of neighboring wavelengths in order to better account for wavelength-dependent scattering. The methods in question are piecewise standard normal variate, localized standard normal variate, piecewise multiplicative scatter correction, and localized multiplicative scatter correction. This work describes the theoretical and algorithmic foundations of the family of local region-based scatter correction methods and compares their application and optimization at a qualitative and quantitative level using several datasets.

NIR spectroscopy↗
DOE OSTI2021

Radial storage efficiency for CO 2 injection: Quantifying effectiveness of local flow control methods

Basin-scale geologic carbon sequestration will require hundreds of injection wells, each of which has costs related to property rights and regulatory requirements that correlate with the areal size of the carbon dioxide plume. These surface-footprint-related issues motivate maximizing storage efficiency radially away from each well. Radial storage efficiency (RSE) is defined here as the ratio of the volumetrically weighted carbon dioxide free-phase saturation within a given radius away from the injection well to the available pore space within that same radius. Maximizing RSE effectively minimizes the radial extent of the CO 2 plume. Optimizing RSE around individual wells requires local flow control injection strategies that can increase the uniformity of the filling of pore space around the well over the entire length of the perforated injection interval despite differences in local formation transmissivity. The goal of uniform filling of the storage reservoir starting from the well outward is to maximize carbon dioxide sweep and trapping locally outward from the well in all of the layers of the storage region before buoyancy forces predominate and drive carbon dioxide upward where it will spread laterally under lower-permeability layers. Example simulations of carbon dioxide injection into a layered storage system with and without local flow control are presented to show the advantage of uniformly filling all layers and how RSE can be used to quantify storage efficiency for the two different injection approaches. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

03 NATURAL GAS↗
DOE OSTI2021

Predictability of Localized Plasmonic Responses in Nanoparticle Assemblies

Design of nanoscale structures with desired optical properties is a key task for nanophotonics. In this work, the correlative relationship between local nanoparticle geometries and their plasmonic responses is established using encoder-decoder neural networks. In the im2spec network, the relationship between local particle geometries and local spectra is established via encoding the observed geometries to a small number of latent variables and subsequently decoding into plasmonic spectra; in the spec2im network, the relationship is reversed. Surprisingly, these reduced descriptions allow high-veracity predictions of local responses based on geometries for fixed compositions and surface chemical states. Analysis of the latent space distributions and the corresponding decoded and closest (in latent space) encoded images yields insight into the generative mechanisms of plasmonic interactions in the nanoparticle arrays. Ultimately, this approach creates a path toward determining configurations that yield the spectrum closest to the desired one, paving the way for stochastic design of nanoplasmonic structures.

nanoparticle arrays↗
DOE OSTI2021

Signal Origin of Electrochemical Strain Microscopy and Link to Local Chemical Distribution in Solid State Electrolytes

Electrochemical strain microscopy (ESM) is a distinguished method to characterize Li-ion mobility in energy materials with extremely high spatial resolution. The exact origin of the cantilever deflection when the technique is applied on solid state electrolytes (SSEs) is currently discussed in the literature. Under-standing local properties and influences on ion mobility in SSEs is of utmost importance to improve such materials for next generation batteries. Here, the exact signal formation process of ESM when applied on sodium super ionic conductor (NASICON)-type SSE containing Na- and Li-ions is investigated. Changes in the dielectric properties, which are linked to the local chemical composition, are found to be responsible for the observed contrast in the deflection of the cantilever instead of a physical volume change as a result of Vegard´s Law. The cantilever response is strongly reduced in areas of high sodium content which is attributed to a reduction of the tip-sample capacitance in comparison to areas with high lithium content. This is the first time a direct link between electrostatic forces in contact mode and local chemical information is demonstrated on SSEs. Furthermore, the results open up new possibilities in information gain since dielectric proper-ties are sensitive to subtle changes in local chemical composition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vision-based localization for cooperative robot-CNC hybrid manufacturing

Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.

Hybrid manufacturing↗