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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

One-Dimensional Electron Gas Confined along Nanowrinkles in a Unidirectional Charge Density Wave Material

Two-dimensional (2D) materials inherently exhibit instabilities. Structurally, this may lead to modulations along the third dimension, e.g., wrinkles. Electronically, 2D instabilities can manifest themselves as charge density waves (CDWs). Although wrinkles can alter anisotropic electronic structures susceptible to forming CDWs, less is known about their impact on broken-symmetry ground states. Here, in this study, using scanning tunneling microscopy and spectroscopy, we investigate the CDW states on the wrinkled surface of DyTe 3 . We identify elongated, parallel nanoscale wrinkles stabilized by ribbon-shaped defects. Interestingly, the CDW order persists across the nanowrinkles with a gradual phase shift but is locally suppressed near the defects, where phase windings occur. In addition, these defects induce quantum confinement effects along the nanowrinkles, indicating the presence of one-dimensional metallic states with hole- like dispersion, while angle-resolved photoemission spectroscopy identifies a gap along the wrinkle direction. We ascribe this discrepancy to strain-induced changes in the Fermi surface, which lead to the closure of the gap at the sites of the nanowrinkles. Taken together, our results underscore the complex interplay between structural features and Fermi surface topology, allowing for the deliberate manipulation of quantum states in strongly correlated systems via local crystal deformations.

nanowrinkles↗
DOE OSTI2024

A strain density function to analyze particle size effects during high velocity impacts of yttria

Here, the impact behavior of a single yttria (Y 2 O 3 ) nanoparticle onto a Y 2 O 3 substrate is studied as a function of particle velocity (300–1200 m/s) and diameter (12–50 nm) using molecular dynamics simulations. To analyze the results, a strain density function is developed to provide both quantitative and qualitative information about the deformation mechanisms that contribute to the final state of the system. This function provides both clear evidence of shear localization and insight into the conditions for which localization occurs during the impact of Y 2 O 3 particles as they approach experimentally relevant sizes. Further analysis shows that localization and fragmentation only occur for Y 2 O 3 impacts with diameters of at least 50 nm, while particles with diameters of 25 nm and smaller deform primarily by amorphization and viscous flow. Implications for the deposition of films of Y 2 O 3 and other rare-earth oxides via the micro cold spray process are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular beam epitaxy and crystal structure of majority a -plane-oriented and substrate-strained Mn 3 Sn thin films grown directly on sapphire (0001)

The Kagome antiferromagnet Mn 3 Sn has garnered much attention due to the presence of exciting properties such as anomalous Hall and Nernst effects. This paper discusses the synthesis of crystalline Mn 3 Sn thin films, prepared on Al 2 O 3 (0001) substrates at 453 ± 5°C using molecular beam epitaxy. The growth is monitored in situ using reflection high energy electron diffraction and measured ex situ using x-ray diffraction, Rutherford back-scattering, and cross-sectional scanning transmission electron microscopy. Our analysis shows the in-plane lattice constants of a 1,M = 4.117 ± 0.027 Å and a 2,M = 4.943 ± 0.033 Å, which is a very unexpected result when compared to the bulk a-plane Mn 3 Sn. This indicates a strain in the film and makes it challenging to provide a straightforward explanation. In an effort to explain our results, we discuss two possible orientation relationships between the Mn 3 Sn films and the sapphire substrates. Samples prepared under these conditions appear to have smooth surfaces locally, but overall the film has a 3D island morphology. First-principles calculations provide atomic models of the Mn 3 Sn (112¯0) lattice on Al 2 O 3 (0001) high symmetry sites, indicating that the L3-R90° is the most stable configuration. A detailed discussion of the experimental data and theoretical results, as well as strain effects, is provided.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Determining Stress Orientation in Rock Valley, Nevada, Using Ambient Seismic Noise

The stress field and the mechanical properties of rocks are important to consider for nuclear explosion monitoring due to their effect on seismic wave radiation from earthquakes and explosions. At the Rock Valley Direct Comparison site, the regional orientation of the maximum horizontal compressive stress (SH max ) is well constrained, but it is unknown whether there are local heterogeneities. Here, I show that stress-induced anisotropy in nonlinear elasticity can be used to estimate the orientation of SH max . Rocks have compliant internal contacts, such as fractures and mineral grain boundaries, that respond to applied strains more strongly than individual mineral crystals. This strain response is asymmetric between compressive and dilatational strains and is affected by anisotropy in the ambient stress field. Traditional seismic velocity measurements are of strain-averaged velocity, which is less sensitive than nonlinear elasticity to the behavior of compliant internal contacts and therefore the stress field and fracture behavior. My results show that the orientation of SH max measured using ambient seismic noise aligns with regional estimates, with some heterogeneity that can also be explained by the limitations of the seismic array. I demonstrate the potential of a passive technique for monitoring the stress field in places that currently lack local measurements.

58 GEOSCIENCES↗
DOE OSTI2022

Atomistic modeling of tensile deformation and fracture of carbon fibers: Nanoscale stress redistribution, effect of local structural characteristics and nanovoids

The mechanisms of tensile deformation and fracture of carbon fibers are investigated in large-scale molecular dynamics simulations. The simulations performed for computational samples with different structural characteristics enable analysis of the structural sensitivity of the mechanical properties. It is found that the carbon fiber nanostructure can be represented by a fine (nanoscale) mixture of stiff and soft regions. Despite the nanoscale structural heterogeneity of the computational fibers, their fracture strain and tensile strength exceed the experimental values by almost an order of magnitude. Here, this observation is explained by the ability of the carbon fiber nanostructure, largely consisting of curved and folded layers of turbostratic carbon, to exhibit continuous nanoscale load redistribution during the deformation. The transient, fluid nature of a percolating cluster of stress-holding structural elements prevents stress localization at the early stage of the deformation and enables the fiber nanostructure to adapt to the increasing load. Overall, the results of the simulations suggest that the design of advanced carbon fiber manufacturing and post-processing methods focused on the elimination of critical mesoscopic structural defects (internal voids, foreign inclusions, and surface flaws) can yield a substantial increase in the strength and fracture strain of carbon fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulation of dilatancy-controlled gas migration processes in saturated bentonite using a coupled multiphase flow and elastoplastic H 2 M model

Dilatancy-controlled gas flow in preferential pathways plays a key role in the safety analysis of radioactive waste repositories. This is particularly the case for bentonite, an often-preferred barrier material. Gas flow in preferential pathways is characterized by localization and spontaneous behavior, which is challenging to simulate in numerical models due to strong hydro-mechanical coupling. To analyze a laboratory experiment in the framework of the DECOVALEX-2023 project, this study introduced a new approach of combining continuous modelling methods with spatial material properties derived from material heterogeneities and experimental observations. The proposed model utilized hydro-mechanical spatial distributions, namely Young's modulus and gas entry pressure, and elastoplasticity combined with a linear swelling model. A conceptual strain-dependent permeability approach simulated dilatancy-controlled gas flow based on hydro-mechanical coupling. To test the effectiveness of the presented approach, a gas injection test in a compacted, saturated bentonite sample was simulated using the open-source code OpenGeoSys 5.8 and compared with experimental observations. The presented methodology is capable of simulating localized gas flow in preferential pathways. The spatial distributions of Young's modulus and gas entry pressure affect the swelling pressure, relative permeability and, in combination with the strain-dependent permeability model, also the intrinsic permeability.

42 ENGINEERING↗
DOE OSTI2024

Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics–Informed Neural Networks

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in data-driven models for learning full-field mechanical responses, such as displacement and strain, from experimental or synthetic data. However, research studies on inferring full-field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, a physics-informed machine learning approach is proposed to identify the elasticity map in nonlinear, large deformation hyperelastic materials. This study reports the prediction accuracies and computational efficiency of physics-informed neural networks (PINNs) in inferring the heterogeneous elasticity maps across materials with structural complexity that closely resemble real tissue microstructure, such as brain, tricuspid valve, and breast cancer tissues. Further, the improved architecture is applied to three hyperelastic constitutive models: Neo-Hookean, Mooney Rivlin, and Gent. Furthermore, the improved network architecture consistently produces accurate estimations of heterogeneous elasticity maps, even when there is up to 10% noise present in the training data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress–strain behavior and an asymmetrical tension–compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predominate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on “discrete twinning” approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress–strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. Additionally, the EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high-resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mesoscale Modeling Approach for Quantifying Microstructure-Aware Micromechanical Responses in Metal Hydrides

Metal hydrides can undergo significant volume changes upon hydrogen uptake and release, which induce a mechanical response that depends not only on the evolving hydrogen composition but also on the microstructure. We present a comprehensive mesoscale modeling framework based on microelasticity theory to quantify the micromechanical responses of metal hydrides, specifically focusing on a hydrogenating polycrystalline MgH 2x particle within a host material as a model micromechanical system. Utilizing digitally generated realistic microstructures and density-functional-theory-derived parameters, we analyzed highly nonuniform local stress profiles in the polycrystalline hydrides under the clamping force exerted by the host during hydrogenation. Our framework also allows us to predict the corresponding strain energy accumulation and mechanical hot spots formation in the hydrides, highlighting their roles in thermodynamic destabilization and mechanical failure, respectively. Through extensive parametric simulations, we further quantified the influence of interface type, crystallinity, grain size, loading ratio, and host stiffness, providing practical guidance for optimizing microstructural design and host material selection. This proposed approach is broadly applicable to micromechanical systems with complex microstructural features involving chemical reaction- and/or phase-transformation-induced deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

GenomeDepot: data management system for microbial comparative genomics

Summary GenomeDepot is an open-source web-based platform for annotation, management, and comparative analysis of microbial genomic sequences and associated data including ortholog families, protein domains, operons, regulatory interactions, strain taxonomy, and sample metadata. GenomeDepot supports rapid creation of websites for user-defined genome collections that include bioinformatic tools for interactive genome browsing, Basic Local Alignment Search Tool (BLAST) search, annotation search, comparative genomic neighborhood visualization, and sequence download. Gene function annotations are generated by a customizable annotation pipeline. The pipeline runs annotation tools in Conda environments and can be easily extended with additional user-specified tools. Availability and implementation GenomeDepot is open source and distributed under the GNU General Public License via GitHub (https://github.com/aekazakov/genome-depot). GenomeDepot is implemented in Python and was tested in Ubuntu Linux. Full installation instructions and documentation are available at https://aekazakov.github.io/genome-depot/. GenomeDepot demo server is freely accessible at https://iseq.lbl.gov/demogd/.

Kazakov, Alexey [Lawrence Berkeley National Labora↗
DOE OSTI2022

Topological supramolecular network enabled high-conductivity, stretchable organic bioelectronics

Intrinsically stretchable bioelectronic devices based on soft and conducting organic materials have been regarded as the ideal interface for seamless and biocompatible integration with the human body. A remaining challenge is to combine high mechanical robustness with good electrical conduction, especially when patterned at small feature sizes. We develop a molecular engineering strategy based on a topological supramolecular network, which allows for the decoupling of competing effects from multiple molecular building blocks to meet complex requirements. We obtained simultaneously high conductivity and crack-onset strain in a physiological environment, with direct photopatternability down to the cellular scale. We further collected stable electromyography signals on soft and malleable octopus and performed localized neuromodulation down to single-nucleus precision for controlling organ-specific activities through the delicate brainstem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Thioredoxin VdTrx1, an unconventional secreted protein, is a virulence factor in Verticillium dahliae

Understanding how plant pathogenic fungi adapt to their hosts is of critical importance to securing optimal crop productivity. In response to pathogenic attack, plants produce reactive oxygen species (ROS) as part of a multipronged defense response. Pathogens, in turn, have evolved ROS scavenging mechanisms to undermine host defense. Thioredoxins (Trx) are highly conserved oxidoreductase enzymes with a dithiol-disulfide active site, and function as antioxidants to protect cells against free radicals, such as ROS. However, the roles of thioredoxins in Verticillium dahliae , an important vascular pathogen, are not clear. Through proteomics analyses, we identified a putative thioredoxin (VdTrx1) lacking a signal peptide. VdTrx1 was present in the exoproteome of V. dahliae cultured in the presence of host tissues, a finding that suggested that it plays a role in host-pathogen interactions. We constructed a VdTrx1 deletion mutant Δ VdTrx1 that exhibited significantly higher sensitivity to ROS stress, H 2 O 2 , and tert -butyl hydroperoxide ( t -BOOH). In vivo assays by live-cell imaging and in vitro assays by western blotting revealed that while VdTrx1 lacking the signal peptide can be localized within V. dahliae cells, VdTrx1 can also be secreted unconventionally depending on VdVps36, a member of the ESCRT-II protein complex. The Δ VdTrx1 strain was unable to scavenge host-generated extracellular ROS fully during host invasion. Deletion of VdTrx1 resulted in higher intracellular ROS levels of V. dahliae mycelium, displayed impaired conidial production, and showed significantly reduced virulence on Gossypium hirsutum , and model plants, Arabidopsis thaliana and Nicotiana benthamiana . Thus, we conclude that VdTrx1 acts as a virulence factor in V. dahliae .

Tian, Li↗
DOE OSTI2020

Probing local electrochemistry via mechanical cyclic voltammetry curves

Understanding the mechanical response of an electrode during electrochemical cycling and its correlation to the device electrochemical performance is crucial to improving the performance of insertion-type energy storage devices, electrochemical actuators, water purification, ion separation and neuromorphic computing applications. Here, we visualized the electro-chemo-mechanical coupling behaviors during charge storage of anhydrous and hydrated WO 3 electrodes via in situ atomic force microscopy (AFM) and developed the concept of mechanical cyclic voltammetry (mCV) curves. The relationship between electrochemical current and strain was investigated with simplified models and the results revealed that the proton insertion/deinsertion process could be described through potential-dependent electro-chemo-mechanical coupling coefficients which might indicate changes in insertion processes during electrode cycling. The mCV mapping results highlight the local heterogeneity and show that the charging processes varied across the electrode. These local variations could be further correlated to local morphology, crystal orientations or chemical compositions with proper electrode designs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2026

PRISMA: PARALLEL REFINEMENT AND INTEGRATION SYSTEM FOR MULTI-AZIMUTHAL ANALYSIS

The Parallel Refinement and Integration System for Multi-azimuthal Analysis (PRISMA, version 1.1.0) is a Python application for processing X-ray diffraction (XRD) image data. PRISMA wraps GSAS-II to perform azimuthally-binned peak refinement, computes per-frame strain and d-spacing from those fits, and provides three PyQt5 graphical interfaces: (1) a Recipe Builder for selecting GSAS-II control (.imctrl) files, optional mask (.immask) files or threshold-ased masking, reference and experiment image sets, peaks, zimuthal range and bin size, and an optional ceria-based auto-calibration; (2) a Batch Processor that uses Dask on local workstations and pure MPI (mpi4py.futures.MPICommExecutor) on HPC to distribute GSAS-II refinement across cores or compute nodes and write results to a 4-dimensional (peaks x frames x azimuths x measurements) Zarr dataset; and (3) a Data Analyzer that renders heatmaps of fit parameters, strain, frame-to-frame deltas, and percent-change-vs-reference, and exports user-defined subsections to CSV or Excel. The peak-refinement algorithm is deterministic. Benchmark on ALCF Crux: a 20,000-image set, single-peak fit in frame mode with 44 azimuthal bins on 128 nodes x 128 workers, 48 seconds total wall time.

Lorenzo Martin, Maria De La Cinta [Argonne Nationa↗
DOE OSTI2020

Needle-Like Ferroelastic Domains in Individual Ferroelectric Nanoparticles

Superior structural, physical and electronic properties make ferroelectric nanocrystals essential in enabling a range of next-generation devices. Ferroelectric responses are determined by crystal structure and domain morphology. The ability to reversibly displace, create and annihilate elastic domains is critical to device applications. Whereas electric-field control has been demonstrated for ferroelectric 180° surface domain walls and vortices, similar control of ferroelastic domains and domain boundaries within individual nanocrystals remains challenging. Using controlled external compressive and tensile axial stress, deterministic and reversible control of highly mobile ferroelastic domains and axial polarization in three dimensions is demonstrated in this study. While many studies exist on ferroelastic domains in thin films and bulk, little is known about ferroelastic interactions at the single nanoparticle level, especially involving domain boundaries. Through combining Bragg coherent X-ray diffractive imaging and Landau theory, strain gradients in individual BaTiO3 nanocrystals are shown to stabilize needle-like ferroelastic twin domains. These domains are highly labile under applied axial stress, producing a locally enhanced electric polarization mediated by a ferroelectric phase transition. The efficacy of Bragg coherent X-ray diffractive imaging in studying in operando domains in three-dimensions is demonstrated, while synergy with theory provides a paradigm for domain boundary engineering and potential for nanoscale functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An experimental and kinetic modeling study of cyclopentane and dimethyl ether blends

Cyclopentane is a suitable naphthene, or cycloalkane, in a palette for multi-component gasoline surrogate fuels due to its presence in market fuels and its relevance to alkyl substituted cyclopentanes also present. However, the previous oxidation studies of cyclopentane have primarily focused on neat mixtures. Blending cyclopentane with dimethyl ether in this work therefore serves to inform our understanding of, and improve predictive models for, multi-component mixtures. Here, the auto-ignition of cyclopentane/dimethyl ether blends was studied in a high-pressure shock tube and in a rapid compression machine. A wide range of temperatures (650 – 1350 K) and elevated pressures of 20 and 40 bar were studied at equivalence ratios of 0.5, 1.0 and 2.0 in air for two blending ratios (30/70 and 70/30 mole% cyclopentane/di-methyl ether mixtures). A detailed kinetic model for cyclopentane was revised to capture the measured ignition delay times and apparent heat release rates in this study. Literature ignition delay time, jet-stirred reactor, and laminar burning velocity measurements of neat cyclopentane were used as additional validation. Improvements to the kinetic model were based on recent literature studies related to sub-models including cyclopentene and cyclopentadiene which allowed the removal of previous local rate-constant optimizations. Low temperature reactivity of cyclopentane was found to be controlled by the branching ratio between concerted elimination of HO͘ 2 and the strained formation of Q&#775OOH radicals in agreement with previous studies. In this study, the low branching ratio of Q&#775OOH formation increases the influence of a competing consumption pathway for cyclopentyl-peroxy (CPTO͘ 2 J) radicals. The sensitivity of the simulated ignition delay times to the formation of cyclopentyl hydroperoxide (CPTO 2 H), from CPTO͘ 2 J and HO͘ 2 , is discussed. The current model is used to analyze the influence of dimethyl ether on the reactivity of cyclopentane in the context of previous literature studies of dimethyl ether binary blends with ethanol and toluene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices

Solid-state devices made from correlated oxides, such as perovskite nickelates, are promising for neuromorphic computing by mimicking biological synaptic function. However, comprehending dopant action at the nanoscale poses a formidable challenge to understanding the elementary mechanisms involved. Here, we perform operando infrared nanoimaging of hydrogen-doped correlated perovskite, neodymium nickel oxide (H-NdNiO 3 , H-NNO), devices and reveal how an applied field perturbs dopant distribution at the nanoscale. This perturbation leads to stripe phases of varying conductivity perpendicular to the applied field, which define the macroscale electrical characteristics of the devices. Hyperspectral nano-FTIR imaging in conjunction with density functional theory calculations unveils a real-space map of multiple vibrational states of H-NNO associated with OH stretching modes and their dependence on the dopant concentration. Moreover, the localization of excess charges induces an out-of-plane lattice expansion in NNO which was confirmed by in situ X-ray diffraction and creates a strain that acts as a barrier against further diffusion. Our results and the techniques presented here hold great potential for the rapidly growing field of memristors and neuromorphic devices wherein nanoscale ion motion is fundamentally responsible for function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗