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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The effects of microstructure on deformation twinning in Mg WE43

The interplay between microstructure and deformation twinning in a WE43-T6 Mg alloy under uniaxial compression was investigated using a combination of scanning electron microscopy with digital image correlation (SEM-DIC) and crystal plasticity finite element (CPFE) simulation. To improve understanding of the statistical characteristics of deformation twin formation, microstructural effects were characterized in over 1000 grains through metrics including the nominal Schmid Factor, grain size, geometric compatibility factor (m'), residual Burgers vector, and the strain accommodated by neighboring grains. There was a strong correlation between the nominal Schmid Factor and both twin activation and variant selection, but this was not fully deterministic. Deformation twinning also exhibited a strong dependence on existing slip and twinning in the neighboring grain and on the m' value. Within the range of grain sizes present in this condition, grain size was determined to have minimal effect on deformation twinning. Finally, statistical analysis of CPFE simulations was used to further investigate microstructural effects on twinning, and qualitatively captured the effect of the nominal Schmid Factor.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Imaging the dynamics of initial laser-driven shocks and blowoff plasmas in polystyrene under laser-direct-drive fusion conditions

The dynamics of laser-driven shock propagation in solid ablator material, along with the concomitant processes of shinethrough and blowoff plasma plume expansion, at conditions relevant to laser-direct-drive fusion are measured using a tabletop system capable of supporting rapid dataset development with significantly higher resolution compared to existing methods. The experimental results are directly compared with current radiation-hydrodynamic simulations using the two-dimensional code . Discrepancies between experiments and simulations are evidenced and attributed to limitation of simulation to account for important processes involved in the solid-to-plasma transition. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A mesoscale 3D model of irradiated concrete informed via a 2.5 U-Net semantic segmentation

The concrete biological shield in light-water reactors is exposed to neutron and gamma irradiation, which deteriorates the concrete’s mechanical properties in the long term. To assess the irradiation-induced damage, predictive mechanical models are developed and used in parallel with the characterization of irradiated concrete samples. Realistic 3D simulation domains can drastically improve a model’s prediction. In this work, we utilized x-ray computed tomography (XCT) data of a concrete specimen to reconstruct its 3D microstructure. The XCT data shows low contrast between the concrete’s aggregates and cement paste, resulting in poor image segmentation when using traditional unsupervised techniques. To address this issue, we developed and trained a 2.5D U-Net model on only 24 pre-labeled XCT layers to segment 651 layers of the XCT data. The overall F1-score of the model is approximately 96%. Then, we created a 3D finite element (FE) mesh based on the stack of segmented images. The FE model contains radiation-induced expansion, damage, and creep. The constitutive equations are adapted to each phase (aggregates and cement paste). Here, we simulated the effects of neutron irradiation in the concrete specimen as well as the specimen’s mechanical response to uniaxial compression. Finally, model validation was performed using experimental data on similar concrete specimens in the literature.

2.5D U-Net↗
DOE OSTI2025

Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data

Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.

CT↗
DOE OSTI2025

Impact of Grafting Density on the Assembly and Mechanical Properties of Self-Assembled Metal–Organic Framework Monolayers

Polymer-grafted metal–organic frameworks (MOFs) can be used to form free-standing self-assembled MOF monolayers (SAMMs). Polymer chains can be introduced onto MOF surfaces through either the ligands or metal nodes using both grafting-to and grafting-from approaches. However, controlling the grafting density of polymer-grafted MOFs has not yet been achieved, because a means to control the density of grafting sites on the MOF surface has not been developed. In this study, the grafting density of polymer-grafted UiO-66 (UiO = University of Oslo) was controlled by functionalizing a portion of the Zr(IV) secondary building units (SBUs) on a UiO-66 surface with a so-called blocking agent. The remaining sites on the UiO-66 SBUs were functionalized with polymerization initiation groups, and polymers were grown from these sites to obtain particles with variable grafting densities and chain lengths that form SAMMs at an air–water interface. Even under conditions of low grafting density, these materials retain the ability to form SAMMs and their free-standing ability. Changes in particle arrangement within the monolayers were investigated using SEM imaging, and the toughness of the monolayers was evaluated using a film-on-water (FOW) method. Furthermore, coarse-grained molecular dynamics simulations were carried out to elucidate the morphology and mechanical properties of the monolayers. Findings from both experiments and simulations indicate that the toughness of SAMMs is more heavily influenced by the chain length of the grafted polymers than by the overall polymer content in the composite.

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

Alignment of Polarization against an Electric Field in van der Waals Ferroelectrics

Polarization in ferroelectrics can be switched in the direction of an applied electric field by dipole reorientation, enabling numerous applications and fundamental phenomena. In this study, we demonstrate that, in the van der Waals (vdW) layered ferrielectric Cu In P 2 S 6 , a unique mechanism exists where polarization aligns against the direction of the applied electric field, seemingly in violation of the fundamental properties of a dipolar solid. The mechanism is the result of the electric field driving the Cu atoms unidirectionally across the vdW gaps, which is distinctively different from dipole reorientation. The crossing of Cu atoms is the fundamental process of ionic conductivity, yet it is compatible with the existence of polarization. These phenomena are confirmed by nanoscale imaging and spectroscopy of ferroelectric capacitors, coupled with dynamic density-functional-theory simulations. The symbiotic relationship of ferroelectric and ionic phenomena enables alternative approaches to control polarization and necessitates a change in perspective on nucleation, domain-wall dynamics, and other ferroelectric and electromechanical characteristics in material systems where ionic and ferroelectric phenomena manifest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Influence of Light Atoms on Quantification of Atomic Column Positions in Distorted Perovskites with HAADF-STEM

Measurement of picometer-scale atomic displacements by aberration-corrected STEM has become invaluable in the study of crystalline materials, where it can elucidate ordering mechanisms and local heterogeneities. HAADF-STEM imaging, often used for such measurements due to its atomic number contrast, is generally considered insensitive to light atoms such as oxygen. Light atoms, however, still affect the propagation of the electron beam in the sample and, therefore, the collected signal. In this work, we demonstrate experimentally and through simulations that cation sites in distorted perovskites can appear to be displaced by several picometers from their true positions in shared cation-anion columns. The effect can be decreased through careful choice of sample thickness and beam voltage or can be entirely avoided if the experiment allows reorientation of the crystal along a more favorable zone axis. Therefore, it is crucial to consider the possible effects of light atoms and crystal symmetry and orientation when measuring atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Strategies for Controlling the Spatial Orientation of Single Molecules Tethered on DNA Origami Templates Physisorbed on Glass Substrates: Intercalation and Stretching

Nanoarchitectural control of matter is crucial for next-generation technologies. DNA origami templates are harnessed to accurately position single molecules; however, direct single molecule evidence is lacking regarding how well DNA origami can control the orientation of such molecules in three-dimensional space, as well as the factors affecting control. Here, we present two strategies for controlling the polar (θ) and in-plane azimuthal (Φ) angular orientations of cyanine Cy5 single molecules tethered on rationally-designed DNA origami templates that are physically adsorbed (physisorbed) on glass substrates. By using dipolar imaging to evaluate Cy5's orientation and super-resolution microscopy, the absolute spatial orientation of Cy5 is calculated relative to the DNA template. The sequence-dependent partial intercalation of Cy5 is discovered and supported theoretically using density functional theory and molecular dynamics simulations, and it is harnessed as our first strategy to achieve θ control for a full revolution with dispersion as small as ±4.5°. In our second strategy, Φ control is achieved by mechanically stretching the Cy5 from its two tethers, being the dispersion ±10.3° for full stretching. These results can in principle be applied to any single molecule, expanding in this way the capabilities of DNA as a functional templating material for single-molecule orientation control. The experimental and modeling insights provided herein will help engineer similar self-assembling molecular systems based on polymers, such as RNA and proteins.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Modeling and experimental validation of dynamical effects in Bragg coherent x-ray diffractive imaging of finite crystals

Bragg coherent diffractive imaging (BCDI) is a noninvasive microscopy technique that can visualize the shape and internal lattice deviations of crystals with nanoscale spatial resolution and picometer deformation sensitivity. Its strain imaging capability relies on Fourier transform–based iterative phase retrieval algorithms, which are mostly developed under the kinematical approximation. Such approximation prohibits the application of BCDI on larger crystals, which are commonly seen in most emerging functional materials. Understanding the dynamical effect in BCDI, as well as developing a validated method for modeling BCDI at the dynamical diffraction limit, is crucial for applying BCDI to hierarchical systems that contain micron-sized crystals and grains. Thus we report a comparative study on the impact of dynamical diffraction effects by comparing the reconstruction results from two measurements of the same crystal. Forward simulation is implemented to show subtle changes of interference fringes in the diffraction pattern due to the dynamical diffraction, and is compared directly with the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques↗
DOE OSTI2020

Time-resolved in situ visualization of the structural response of zeolites during catalysis

Zeolites form an important class of materials that are widely used in various fields. Their unique properties come primarily from their size, shape, and connectivity of their sub-nm crystalline voids, the Si/Al ratio of the anionic framework, and the number and the nature of charge-balancing cations.The inhomogeneous distribution of the Si/Al ratio within crystals, and hence the cation density, the presence of organic residues, and their inhomogeneous distribution within crystals sensitively affect their performances because these factors influencethe intra-crystalline diffusion rates of the reactants and products. However, the information regarding these inhomogeneities in zeolite crystals cannot be obtained by conventional analytical tools because they only provide information regardingthe average properties of zeolite crystals. Here we employin situX-ray free electron laser-based time-resolved coherent X-ray diffraction imaging to investigate the internal deformations originating from the inhomogeneous Cu ion distributions in Cu-exchanged ZSM-5 zeolite crystals during the deoxygenation of nitrogen oxides with propene. We show that the interactions between the reactants and the active sites lead to an unusual strain distribution,which is confirmed by density functional theory simulations. Moreover, this elucidates the factors responsible for distinct active regions,which are essential to maximizing some applications with enhanced performances. These observations provide insights into the role of structural inhomogeneity in zeolites during a catalytic processand will assist the future design of zeolites for their applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

On the initiation and evolution of dielectric breakdown in auto-magnetizing liner experiments

Auto-magnetizing (AutoMag) liners are cylindrical tubes composed of discrete metallic helices encapsulated in insulating material; when driven with a ~2 MA, ~100-ns prepulse on the 20 MA, 100-ns rise time Z accelerator, AutoMag targets produced >150 T internal axial magnetic fields. Once the current rise rate of the pulsed power driver reaches sufficient magnitude, the induced electric fields in the liner cause dielectric breakdown of the insulator material and, with sufficient current, the cylindrical target radially implodes. The dielectric breakdown process of the insulating material in AutoMag liners has been studied in experiments on the 500–900 kA, ~100-ns rise time Mykonos accelerator. Multi-frame gated imaging enabled the first time-resolved observations of photoemission from dynamically evolving plasma distributions during the breakdown process in AutoMag targets. Using magnetohydrodynamic simulations, we calculate the induced electric field distribution and provide a detailed comparison to the experimental data. We find that breakdown in AutoMag targets does not primarily depend on the induced electric field in the gaps between conductive helices as previously thought. Finally, to better control the dielectric breakdown time, a 12–32 mJ, 170 ps ultraviolet (λ = 266 nm) laser was implemented to irradiate the outer surface of AutoMag targets to promote breakdown in a controlled manner at a lower internal axial field. Here, the laser had an observable effect on the time of breakdown and subsequent plasma evolution, indicating that pulsed UV lasers can be used to control breakdown timing in AutoMag.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Full-field quantitative visualization of shock-driven pore collapse and failure modes in PMMA

The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression response of porous materials at the local, individual pore scale is not well understood. This study examines, quantitatively, the collapse phenomenon of a single spherical void in PMMA at shock stresses ranging from 0.4 to 1.0 GPa. Using a newly developed internal digital image correlation technique in conjunction with plate impact experiments, full-field quantitative deformation measurements are conducted in the material surrounding the collapsing pore for the first time. The experimental results reveal two failure mode transitions as shock stress is increased: (i) the first in situ evidence of shear localization via adiabatic shear banding and (ii) dynamic fracture initiation at the pore surface. Numerical simulations using thermo-viscoplastic dynamic finite element analysis provide insights into the formation of adiabatic shear bands (ASBs) and stresses at which failure mode transitions occur. Further numerical and theoretical modeling indicates the dynamic fracture to occur along the weakened material inside an adiabatic shear band. Finally, analysis of the evolution of pore asymmetry and models for ASB spacing elucidate the mechanisms for the shear band initiation sites, and elastostatic theory explains the experimentally observed ASB and fracture paths based on the directions of maximum shear.

42 ENGINEERING↗
DOE OSTI2024

Massive all-atom analysis of 2D materials with quantum properties (Final report)

Improvements in microscopy have enabled the acquisition of data at a scale that is difficult to process manually, making automated machine learning approaches to analyzing experimental images essential. In this project, we developed and applied machine learning (ML) workflows for atomic resolution scanning transmission electron microscopy (STEM) images. This development included improving both methodology as well as generating user-friendly codes. We developed machine learning architectures which, after training, automatically identify the location and types of defects throughout a material. We used these data to produce class-averaged images of 2D atomic coordinates with up to 0.3 pm precision, uncovering the structure and oscillations of long-range strain fields around point defects in WSe 2-2x Te 2x . We also resolved a long-standing problem in this field in the training of ML models, a lack of labeled experimental data, by developing a cycle-GAN that transformed simulated-generated labeled data into labeled data indistinguishable from experiment and therefore suitable for training. This removed the remaining parts of the ML data processing workflow where human intervention was still critical and therefore a bottleneck to working at scale. Codes have been developed and released for this full machine learning workflow. ML approaches to partially automate STEM acquisition were also developed. Finally we applied ML and other advanced data processing methods to several materials science problems in two-dimensional materials, including studying the evolution of hyperuniformity with defect concentration in WSe2, understanding phase transformations in transition metal dichalcogenides during in-situ heating in the STEM, and exploring how 2D interfaces transform from twisted into aligned structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Challenges in simulating ground interacting nuclear explosions

This paper summarizes recent above-ground nuclear explosion simulations as part of a broader effort to better characterize conditions within a fireball that may influence the chemical evolution of bomb materials and other materials entrained from the local explosion environment. A critical component of this work is validation against historic footage of atmospheric testing, requiring that we understand how the frequency-dependent sensitivity of the utilized film footage influences data captured in such images. We focus first on the early physics of a nuclear explosion in the atmosphere before discussing some of the technical challenges we seek to capture in late-time models that include more complex emplacement conditions and subsurface features. We discuss required physics packages (compressible hydrodynamics, radiation transport, as well as necessary ancillary tables such as equations of state (EOS) and opacities). Additionally, we note reasonable “shortcuts” one may make and their limitations, e.g., using ideal gas EOS, replacing spectrally resolved radiation with spectrally averaged radiation, and exchanging deterministic transport with diffusion. We then discuss an approach to achieving an equilibrated initial stress state for problems where buoyancy and subsurface lithostatic stress are important. Our methodology is presented in the context of LLNL’s ALE3D multiphysics code but may readily be implemented in other codes. In this paper, we start with a description of the challenges of NUDET simulations, followed by a presentation of the simulated intensity (flux) as it would appear on an analysis of the Dixie test. We then progressively introduce additional complexity in subsequent sections (near-surface burst and gravity initialization) before concluding.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

In-Situ SEM High Strain Rate Testing of Large Diameter Micropillars Followed by TEM and EBSD Postmortem Analysis

Background Dislocation dynamic simulations are intended as a tool to understand and predict the mechanical behavior of metallic materials, but its prediction has never been directly verified by experiments due to differences in specimen strain rate and size. Objective In this work, a comprehensive experimental framework is proposed to attempt direct comparison between experiments and discrete dislocation dynamics (DDD) modelling. Methods By integrating high-throughput sample fabrication and a customized testing apparatus, the sample size and strain rate typically employed in DDD simulations are explored experimentally. Constitutive properties such as stress-strain response are measured, and microstructural information is obtained from transmission electron microscopy (TEM) imaging, electron backscatter diffraction (EBSD), and TEM-based orientation mapping. Results Magnesium and copper were selected, as case studies, to demonstrate the newly developed experimental procedure. Measured stress-strain responses for Mg are consistent with those obtained with a miniaturized Hopkison bar experiments. Furthermore, by exploiting the validated workflow, the effect of strain rate on micropillar heterogeneous deformation and associated dislocation plasticity were revealed. Conclusion The work establishes a methodology for the systematic study of not only metals but also other materials and structures at the microscale and high strain rates.

42 ENGINEERING↗
DOE OSTI2020

Topologically derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene

In this work, we develop a continuum dislocation description of twist and stretch moiré superlattices in two-dimensional material bilayers. The continuum formulation is based on the topological constraints introduced by the periodic dislocation network associated with the moiré structure. The approach is based on solving analytically for the structural distortion and displacement fields that satisfy the topological constraints and that minimize the total energy. The total energy is described by both the strain energy of each individual distorted layer and a Peierls-Nabarro-like interfacial contribution arising from stacking disregistry. The dislocation core emerges naturally within the formalism as a result of the competition between the two contributions. The approach presented here captures the structure and energetics of twist and stretch moiré superlattices of dislocations with arbitrary direction and character, without assuming an analytical solution a priori and while accounting naturally for dislocation-dislocation image interactions. In comparisons to atomistic simulations using classical potentials, the maximum structure deviation is 6%, while the maximum line energy deviation is 0.019 eV/Å. Several applications of our model are shown, including predicting the variation of structure with twist angle and describing dislocation line tension and junction energies.

36 MATERIALS SCIENCE↗