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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Inversion of Many-Beam Bragg Intensities for Phasing by Iterated Projections: Removal of Multiple Scattering Artifacts from Diffraction Data

An iterated projection algorithm (N-Phaser) is developed that reconstructs a scattering potential from N-beam multiple Bragg scattered intensities. The method may be used to eliminate multiple scattering artifacts from electron diffraction data, solving the phase problem and increasing the thicknesses of samples used in materials science, solid-state chemistry, and small molecule crystallography. For high-energy transmission electron diffraction, we show that the algorithm recovers accurate complex structure factors from a wide range of thicknesses, orientations, and relativistic beam energies, and does not require known thickness or atomic-resolution data if sufficient multiple scattering occurs. Furthermore, extensions to Cryo-electron microscopy and Micro-electron diffraction are suggested.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomistic Mechanism Underlying the Si ( 111 ) - ( 7 × 7 ) Surface Reconstruction Revealed by Artificial Neural-Network Potential

The 7×7 reconstruction of the Si(111) surface represents arguably the most fascinating surface reconstruction so far observed in nature. Yet, the atomistic mechanism underpinning its formation remains unclear after it was discovered sixty years ago. Experimentally, it is observed post priori so that analysis of its formation mechanism can only be carried out in analogy with archaeology. Theoretically, density-functional theory (DFT) correctly predicts the Si(111)-(7×7) ground state but is impractical to simulate its formation process; while empirical potentials failed to produce it as the ground state. Developing an artificial neural-network potential of DFT quality, we carried out accurate large-scale simulations to unravel the formation of the Si(111)-(7×7) surface. We reveal a possible step-mediated atom-pop rate-limiting process that triggers massive nonconserved atomic rearrangements, most remarkably, a critical process of collective vacancy diffusion that mediates a sequence of selective dimer, corner-hole, stacking-fault, and dimer-line pattern formation, to fulfill the 7×7 reconstruction. Our findings may not only solve the long-standing mystery of this famous surface reconstruction but they also illustrate the power of machine learning in studying complex structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Morphology selection in dealloying: A phase field study of the coupling among kinetic mechanisms

A phase field model is used to investigate how the corrosion rate and morphology of a dealloying metal is controlled by the kinetic rates of bulk solid diffusion, interfacial diffusivity, and interface dissolution. A specific focus is investigating the manner by which variations in these kinetic parameters synergistically influence the onset of a morphological instability at the solid-liquid interface, which is known to precede rapid dealloying corrosion towards highly topologically complex structures such as bicontinuous porous solids. This work demonstrates that this instability can be suppressed by either an increase of interdiffusion in the solid alloy, or by a decreasing rate of dissolution at the solid-liquid interface. When the instability is suppressed, the result is a relatively planar, passivated dealloying front. Importantly, however, coupled changes in kinetic parameters can also promote the morphological instability and sustain fine-scale ligament and pore formation. Finally, the relevance of the solid-liquid interfacial diffusion for determining the rate of dealloying and ligament formation is highlighted. By elucidating the mechanistic influence of bulk and interfacial kinetic factors on the dealloyed morphology, this work helps to rationalize the contrasting morphologies observed in various dealloying systems.

Diffusion↗
DOE OSTI2024

Tracking copper nanofiller evolution in polysiloxane during processing into SiOC ceramic

Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.

Chemistry↗
DOE OSTI2021

Beamline K11 DIAD: a new instrument for dual imaging and diffraction at Diamond Light Source

The Dual Imaging and Diffraction (DIAD) beamline at Diamond Light Source is a new dual-beam instrument for full-field imaging/tomography and powder diffraction. This instrument provides the user community with the capability to dynamically image 2D and 3D complex structures and perform phase identification and/or strain mapping using micro-diffraction. The aim is to enable in situ and in operando experiments that require spatially correlated results from both techniques, by providing measurements from the same specimen location quasi-simultaneously. Using an unusual optical layout, DIAD has two independent beams originating from one source that operate in the medium energy range (7–38 keV) and are combined at one sample position. Here, either radiography or tomography can be performed using monochromatic or pink beam, with a 1.4 mm × 1.2 mm field of view and a feature resolution of 1.2 µm. Micro-diffraction is possible with a variable beam size between 13 µm × 4 µm and 50 µm × 50 µm. One key functionality of the beamline is image-guided diffraction, a setup in which the micro-diffraction beam can be scanned over the complete area of the imaging field-of-view. This moving beam setup enables the collection of location-specific information about the phase composition and/or strains at any given position within the image/tomography field of view. The dual beam design allows fast switching between imaging and diffraction mode without the need of complicated and time-consuming mode switches. Real-time selection of areas of interest for diffraction measurements as well as the simultaneous collection of both imaging and diffraction data of (irreversible) in situ and in operando experiments are possible.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Characterizing Sub-Cohorts via Data Normalization and Representation Learning

The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipeline for refining the process of cohort selection based on medical concepts recorded in the electronic health records (EHRs). The pipeline extracts EHR data for a given cohort and normalizes this data using standard vocabularies. Then a stacked denoising autoencoder is used to embed the normalized patient vectors in a low dimensional space, where the patients are subsequently clustered into sub-cohorts. The goal is to represent the cohort in a standard format and abstract variants of sub-populations. As a use-case, we applied the pipeline to 1.8 million Veterans diagnosed with major depressive disorder (MDD), and identified four meaningful sub-cohorts using the features learned by the autoencoder. Then, each sub-cohort was explored using a set of keywords for interpretation.

Rush III, Everett↗
DOE OSTI2025

Multi-Resolution UAV Path Replanning for Inspection of Tailings Dams

Autonomous inspection of large and complex structures with a commercial unmanned aerial vehicle (UAV) is a challenging problem that has been addressed in recent years. In this paper, we address the global motion planning problem of creating autonomous inspection missions for UAVs considering photogrammetry constraints. We focus on the inspection of large tailings dams, which are dam structures used to store waste byproducts of mining. Our method uses a prior sparse point cloud of the dam to generate a voxel grid, where paths satisfying photogrammetry constraints are tested for collisions. We then apply the A* algorithm as a local planner to avoid obstacles within the global mission. Moreover, we address the problem of changing routes online by using octree-based multi-resolution grids for efficient and fast pathfinding. Our results, obtained using tridimensional maps of an actual coal mine tailings dam, show that using octrees for multi-resolution motion planning is faster than using a fixed voxel grid in online missions while inspecting large structures.

42 ENGINEERING↗
DOE OSTI2020

Viscoelastic Material Characterization and Modeling of Photovoltaic Module Packaging Materials for Direct Finite-Element Method Input

Numerical tools, such as the finite-element method, are increasingly used to design and evaluate the photovoltaic (PV) modules, providing for the reduction of development time and improved performance and reliability. However, high-fidelity material models are necessary to accurately model the complex structural behavior of the involved packaging materials. A common simplification used in recent years is to model the polymer materials (i.e., encapsulant and backsheet) as linear elastic, which will lead to inaccurate results. Therefore, in this work, we present a thorough characterization of the time- and temperature-dependent mechanical response of predominant PV module encapsulant and backsheet materials. Based on this material characterization, we developed and experimentally validated generalized Maxwell models to describe each material's viscoelastic response. In addition, we included measurements of the coefficient of thermal expansion and presented all material models in such a fashion for direct input into commercial finite-element method modeling software.

FEM↗
DOE OSTI2024

Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch-screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass-forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, in this work, we explore the application of an open-source pre-trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics-informed machine learning (PIML)-predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top-performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Elongated galactan side chains mediate cellulose–pectin interactions in engineered Arabidopsis secondary cell walls

SUMMARY The plant secondary cell wall is a thickened matrix of polysaccharides and lignin deposited at the cessation of growth in some cells. It forms the majority of carbon in lignocellulosic biomass, and it is an abundant and renewable source for forage, fiber, materials, fuels, and bioproducts. The complex structure and arrangement of the cell wall polymers mean that the carbon is difficult to access in an economical and sustainable way. One solution is to alter the cell wall polymer structure so that it is more suited to downstream processing. However, it remains difficult to predict what the effects of this engineering will be on the assembly, architecture, and properties of the cell wall. Here, we make use of Arabidopsis plants expressing a suite of genes to increase pectic galactan chain length in the secondary cell wall. Using multi‐dimensional solid‐state nuclear magnetic resonance, we show that increasing galactan chain length enhances pectin–cellulose spatial contacts and increases cellulose crystallinity. We also found that the increased galactan content leads to fewer spatial contacts of cellulose with xyloglucan and the backbone of pectin. Hence, we propose that the elongated galactan side chains compete with xyloglucan and the pectic backbone for cellulose interactions. Due to the galactan topology, this may result in comparatively weak interactions and disrupt the cell wall architecture. Therefore, introduction of this strategy into trees or other bioenergy crops would benefit from cell‐specific expression strategies to avoid negative effects on plant growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Nanofabrication and inspection of fuel capsules for inertial confinement fusion

3D nanofabrication via Two-Photon Polymerization (TPP) provides a unique capability of flexibly fabricating complex structures over 1D-3D dimensions and µm-cm scales with resolutions below 100 nm. In the past years, the Laser-Assisted Nano Engineering (LANE) Group at the University of Nebraska-Lincoln (UNL) has been working closely with the Laboratory of Laser Energetics (LLE) in developing practical TPP approaches to fabricating various target structures for Inertial Confinement Fusion (ICF). At the same time, fuel capsules for ICF experiments should be inspected for surface and wall-embedded defects. Plastics materials [e.g., for example polystyrene (PS)] are the common materials used to make fuel capsules. However, during their manufacturing, capsules usually contain defects (vacuoles) embedded inside the shell walls, which may distort the implosion processes and influence the ICF performance of the capsules. The size of vacuoles is usually in a range from 100 to 2000 nm. Coherent anti-Stokes Raman scattering (CARS) microscope offers the capabilities of inspecting and characterizing the capsule defects. Furthermore, cryo-CARS microscopy was developed to explore how fuel isotope distributed inside target when icing that could not be diagnosed before.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Production of microchannel plates using nano-scale additive manufacturing

Microchannel plate (MCP) detectors have been the workhorse detector for many applications, including space borne ultra-violet imaging and spectrographic instruments. Recent advances in additive manufacturing (AM) have enabled fabrication of complex structures with nano-scale resolution facilitating the production of highly customizable MCPs. Using AM to produce MCPs potentially has many advantages over traditional fused glass substrates, including better material control (e.g., more robust glasses or ceramics), better control of microscopic features (e.g., unique pore geometries to improve performance), and better control of macroscopic features (e.g., printing precision curved surfaces for focal plane matching). Through a collaboration with industry, national laboratory, and university partners, small format microcapillary array substrates were produced using a standard polymer photoresin. In conclusion, these substrates were functionalized using atomic layer deposition and their performance was compared to current state-of-the-art Pb-glass and borosilicate-glass MCPs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Field-controlled dynamics of skyrmions and monopoles

Magnetic monopoles, despite their ongoing experimental search as elementary particles, have inspired the discovery of analogous excitations in condensed matter systems. In chiral condensed matter systems, emergent monopoles are responsible for the onset of transitions between topologically distinct states and phases, such as in the case of transitions from helical and conical phase to A-phase comprising periodic arrays of skyrmions. By combining numerical modeling and optical characterizations, we describe how different geometrical configurations of skyrmions terminating at monopoles can be realized in liquid crystals and liquid crystal ferromagnets. We demonstrate how these complex structures can be effectively manipulated by external magnetic and electric fields. Furthermore, we discuss how our findings may hint at similar dynamics in other physical systems and their potential applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Multiplexed CRISPR-Cas9 mutagenesis of rice PSBS1 noncoding sequences for transgene-free overexpression

Understanding CRISPR-Cas9’s capacity to produce native overexpression (OX) alleles would accelerate agronomic gains achievable by gene editing. To generate OX alleles with increased RNA and protein abundance, we leveraged multiplexed CRISPR-Cas9 mutagenesis of noncoding sequences upstream of the rice PSBS1 gene. We isolated 120 gene-edited alleles with varying non-photochemical quenching (NPQ) capacity in vivo—from knockout to overexpression—using a high-throughput screening pipeline. Overexpression increased OsPsbS1 protein abundance two- to threefold, matching fold changes obtained by transgenesis. Increased PsbS protein abundance enhanced NPQ capacity and water-use efficiency. Across our resolved genetic variation, we identify the role of 5'UTR indels and inversions in driving knockout/knockdown and overexpression phenotypes, respectively. Complex structural variants, such as the 252-kb duplication/inversion generated here, evidence the potential of CRISPR-Cas9 to facilitate significant genomic changes with negligible off-target transcriptomic perturbations. Our results may inform future gene-editing strategies for hypermorphic alleles and have advanced the pursuit of gene-edited, non-transgenic rice plants with accelerated relaxation of photoprotection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

High-Pressure Electrides: A Quantum Chemical Perspective

It has long been assumed that all matter will adopt simple close-packed lattices and become metallic under pressure, in accordance with the Thomas–Fermi–Dirac (TFD) model. However, this model struggles to explain pressure-driven complex structural transitions that have been observed in elements, including sodium, challenging our conventional understanding of compressed matter. Moreover, in stark contrast to the TFD model, first-principles calculations suggest that various elements and compounds become electrides under pressure. Electrides, characterized by concentrations of charge density at interstitial regions, can be thought of as ionic compounds where electrons behave as the anions. Though ambient-pressure molecular electrides have been extensively studied via experiments and computations, high-pressure electrides (HPEs) are not well-understood. The identification and characterization of HPEs have been, to date, based purely on theory, including topological analysis of the electron density and the electron localization function. Here, we review these theoretical analysis tools and suggest guidelines that can be used to classify systems as electrides. Moreover, we describe models used to rationalize the electronic structure of HPEs, drawing parallels with ambient-pressure molecular systems, and encourage the development of experimental techniques that provide evidence for the theoretically calculated charge localization.

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

Vidyut3d: A Non-Equilibrium Plasma Modeling Tool [SWR-24-101]

Vidyut3d is a massively-parallel plasma-fluid solver for low-temperature plasmas (LTPs) that supports both local field (LFA) and local mean energy (LMEA) approximations, as well as complex gas and surface-phase chemistry. The solver supports 2D and 3D domains, and uses AMReX's adaptive mesh refinement capabilities to increase the grid resolution around complex structures (e.g. streamer heads and sheaths) while maintaining a tractable problem size. Vidyut specializes in simulating various types of gas-phase discharges, as well as plasma/surface interactions and surface chemistry (e.g. for plasma-mediated catalysis applications). The solver also supports hybrid CPU/GPU parallelization strategies, and has demonstrated excellent scaling on various HPC architectures for problem sizes consisting of O(100 M) control volumes.

Sitaraman, Hariswaran↗
DOE OSTI2020

Experimental investigation of the crush performance of prepreg platelet molding compound tubes

This work presents an experimental study characterizing the crush performance of hollow cylindrical tubes made with prepreg platelet molding compound (PPMC). PPMC is a composite material system that uses platelets from chopped and slit unidirectional prepreg as the basis for a molding compound. This material system has a higher fiber volume fraction and better mechanical properties than traditional short fiber systems and can be molded into complex geometries unlike continuous fiber systems. As such, this material system shows promise for use with complex structural members in vehicles. The failure morphology and specific energy absorption of the material are evaluated with different thickness-to-diameter geometries and test speeds. In addition, this work investigates how PPMC components compare to traditional continuous fiber components and finds that PPMC performs as well as continuous fiber layups with similar effective laminate stiffnesses.

Materials Science↗