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At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

NASA NTRS2026

Investigating Dual Electrospinning as a Means of Enhancing Passive Thermal Control Coatings for Cryogenic Propellant Storage in Extraterrestrial Environments

Passive thermal control is necessary as space exploration becomes increasingly widespread. Materials with superior optical properties (high solar reflectance and infrared emittance) are critical for passive thermal control because they can reject most of the incident solar radiation and promote thermal emission from cryogenic propellant storage tanks, enabling the extraterrestrial storage of cryogens. We have demonstrated in previous studies that electrospun nanofibers exhibit exceptional optical properties, offering significant benefits for passive radiative cooling in space. Particularly, electrospun polyvinylidene fluoride-co-hexafluoropropylene PVDF-HFP nanofibers demonstrate exceptionally high solar reflectance (>99%) and strong thermal emittance (measured at ~300 K). However, they exhibit nanostructural changes in the presence of atomic oxygen, which is prevalent in Low Earth Orbit. This study focuses on creating a unique blend of polymeric (PVDF-HFP) and ceramic-based (silica) nanofibers by leveraging the chemical stability and atomic oxygen resistance of silica, using the dual electrospinning manufacturing method. This approach aims to preserve the structural properties of the polymeric counterpart without compromising its optical performance, thereby providing an innovative method for manufacturing environmentally resilient passive thermal control nanofibers with desirable optical and thermal control functionalities for extraterrestrial storage of cryogenic propellants.

Chieloka Ibekwe↗

DOE OSTI2021

Nonlinear Matrix Approximation with Radial Basis Function Components

We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components. An RBF component is a generalization of the outer product between a pair of vectors, where an RBF function replaces the scalar multiplication between individual vector elements. Even though the RBF functions are positive definite, the summation across components is not restricted to convex combinations and allows us to compute the decomposition for any real matrix that is not necessarily symmetric or positive definite. We formulate the problem of seeking such a decomposition as an optimization problem with a nonlinear and non-convex loss function. Several modern versions of the gradient descent method, including their scalable stochastic counterparts, are used to solve this problem. We provide extensive empirical evidence of the effectiveness of the RBF decomposition and that of the gradient-based fitting algorithm. While being conceptually motivated by singular value decomposition (SVD), our proposed nonlinear counterpart outperforms SVD by drastically reducing the memory required to approximate a data matrix with the same L2 error for a wide range of matrix types. For example, it leads to 2 to 6 times memory save for Gaussian noise, graph adjacency matrices, and kernel matrices. Moreover, this proximity-based decomposition can offer additional interpretability in applications that involve, e.g., capturing the inner low-dimensional structure of the data, retaining graph connectivity structure, and preserving the acutance of images.

Rebrova, Elizaveta↗

DOE OSTI2023

Nanometer flat blazed x-ray gratings using ion beam figure correction

With the development of nanometer accuracy stitching interferometry, ion beam figuring (IBF) of x-ray mirrors can now be achieved with unprecedented performance. However, the process of producing x-ray diffraction gratings on these surfaces may degrade the figure quality due to process errors introduced during the ruling of the grating grooves. To address this challenge, we have investigated the post-production correction of gratings using IBF, where stitching interferometry is used to provide in-process feedback. A concern with ion beam correction in this case is that ions will induce enough surface mobility of atoms to cause smoothing of the grating structure and degradation of diffraction efficiency. In this study we found however that it is possible to achieve a nanometer-level planarity of the global grating surface with IBF, while preserving the grating structure. The preservation was so good, that we could not detect a change in the diffraction efficiency after ion beam correction. This is of major importance in achieving ultra-high spectral resolution, and the preservation of brightness for coherent x-ray beams.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Coarse-graining Hamiltonian systems using WSINDy

Abstract Weak form equation learning and surrogate modeling has proven to be computationally efficient and robust to measurement noise in a wide range of applications including ODE, PDE, and SDE discovery, as well as in coarse-graining applications, such as homogenization and mean-field descriptions of interacting particle systems. In this work we extend this coarse-graining capability to the setting of Hamiltonian dynamics which possess approximate symmetries associated with timescale separation. A smooth $$\varepsilon$$ ε -dependent Hamiltonian vector field $$X_\varepsilon$$ X ε possesses an approximate symmetry if the limiting vector field $$X_0=\lim _{\varepsilon \rightarrow 0}X_\varepsilon$$ X 0 = lim ε → 0 X ε possesses an exact symmetry. Such approximate symmetries often lead to the existence of a Hamiltonian system of reduced dimension that may be used to efficiently capture the dynamics of the symmetry-invariant dependent variables. Deriving such reduced systems, or approximating them numerically, is an ongoing challenge. We demonstrate that WSINDy can successfully identify this reduced Hamiltonian system in the presence of large perturbations imparted in the $$\varepsilon >0$$ ε > 0 regime, while remaining robust to extrinsic noise. This is significant in part due to the nontrivial means by which such systems are derived analytically. WSINDy naturally preserves the Hamiltonian structure by restricting to a trial basis of Hamiltonian vector fields. The methodology is computationally efficient, often requiring only a single trajectory to learn the global reduced Hamiltonian, and avoiding forward solves in the learning process. In this way, we argue that weak-form equation learning is particularly well-suited for Hamiltonian coarse-graining. Using nearly-periodic Hamiltonian systems as a prototypical class of systems with approximate symmetries, we show that WSINDy robustly identifies the correct leading-order system, with dimension reduced by at least two, upon observation of the relevant degrees of freedom. While our main contribution is computational, we also provide a contribution to the literature on averaging theory by proving that first-order averaging at the level of vector fields preserves Hamiltonian structure in nearly-periodic Hamiltonian systems. This provides theoretical justification for our approach as WSINDy’s computations occur at the level of Hamiltonian vector fields. We illustrate the efficacy of our proposed method using physically relevant examples, including coupled oscillator dynamics, the Hénon–Heiles system for stellar motion within a galaxy, and the dynamics of charged particles.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Block-Structured Operator Inference for Coupled Multiphysics Model Reduction

This work presents a block-structured formulation of Operator Inference as a way to learn structured reduced-order models for multiphysics systems. The approach specifies the governing equation structure for each physics component and the structure of the coupling terms. Once the multiphysics structure is specified, the reduced-order model is learned from snapshot data following the nonintrusive Operator Inference methodology. In addition to preserving physical system structure, which in turn permits preservation of system properties such as stability and second-order structure, the block-structured approach has the advantages of reducing the overall dimensionality of the learning problem and admitting tailored regularization for each physics component. The numerical advantages of the block-structured formulation over a monolithic Operator Inference formulation are demonstrated for aeroelastic analysis, which couples aerodynamic and structural models. For the benchmark test case of the AGARD 445.6 wing, block-structured Operator Inference provides an average 20% online prediction speedup over monolithic Operator Inference across subsonic and supersonic flow conditions in both the stable and fluttering parameter regimes while preserving the accuracy achieved with monolithic Operator Inference.

42 ENGINEERING↗

DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗

DOE OSTI2025

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗

NASA NTRSDate not supplied

Overlap Preservation Using Loosely-Coupled Boundary Conditions for Body-Fitted Structured Overset Grids

Several improvements are made to overlap preservation in the automated approach to generating overset structured meshes. A loosely-coupled boundary condition (LCBC) is introduced to maintain optimal overlap for surface meshes generated from overlapping initial curves. Extension of the LCBC scheme to three-dimensional volume meshing is also presented. Test cases include various rotary wing vehicles from NASA’s Revolutionary Vertical Lift Technology (RVLT) project, and the wing-body geometry from the NASA Juncture Flow Experiment. Results demonstrate improvements in donor stencil quality from the enhanced overlap between neighboring surface and volume meshes.

TTT↗

DOE OSTI2024

Hierarchical Biogenic-Based Thermal Insulation Foam

Biogenic-based foam, renowned for its sustainable and eco-friendly properties, is emerging as a promising thermal insulating material with the potential to significantly enhance energy efficiency and sustainability in building applications. However, its relatively high thermal conductivity, large-pore configurations, and energy-intensive manufacturing processes hinder its widespread use. Here, we report on the scalable, one-pot synthesis of biogenic foams achieved by integrating recycled paper pulp and in situ nanoporous silica formation, resulting in a hierarchical structure comprising both micropores and nanopores. Ambient solvent-exchange drying can preserve the pore structure by reducing the capillary forces during the drying process. The resulting flame-retardant and hydrophobic foam exhibits low density (0.110 g/cm 3 ), ideal porosity (70.69%), excellent thermal conductivity (0.033 W/(m·K)), and impressive compressive strength (1.48 MPa at 80% strain). Furthermore, this recyclable biogenic foam, with its hierarchical pore structure and environmental durability, shows great potential for energy-efficient building applications.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Deformational sequence of a portion of the Michipicoten greenstone belt, Chabanel Township, Ontario

Detailed mapping at a scale of one inch = 400 feet is being carried out within a fume kill, having excellent exposure, located in the southwestern portion of the Michipicoten Greenstone Belt near Wawa, Ontario. The rocks are metasediments and metavolcanics of lower greenschist facies. U-Pb geochronology indicates that they are at least 2698 + or - 11 Ma old. The lithologic packages strike northeast to northwest, but the dominant strike is approximately east-west. Sedimentary structures and graded bedding are well preserved, aiding in the structural interpretation of this multiply deformed area. At least six phases of deformation within a relatively small area of the Michipicoten Greenstone Belt have been tentatively identified. These include the following structural features in approximate order of occurrence: (0) soft-sediment structures; (1) regionally overturned rocks, flattened pebbles, bedding parallel cleavage, and early, approximately bedding parallel faults; (2) northwest to north striking cleavage; (3) northeast striking cleavage and associated folds, and at least some late movement on approximately bedding parallel faults; (4) north-northwest and northeast trending faults; and (5) diabase dikes and associated fracture cleavages. Minor displacement of the diabase dikes occurs on faults that appear to be reactivated older structures.

Shrady, C. H.↗

NASA NTRS1990

Electric power scheduling: A distributed problem-solving approach

Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity. The value-driven free-market economic model is such a tool.

Mellor, Pamela A.↗

NASA NTRS1990

Electric power scheduling - A distributed problem-solving approach

Mellor, Pamela A.↗

NASA NTRS1992

The Manson impact structure - Its contribution to impact materials observed at the Cretaceous/Tertiary boundary

The Manson impact structure (MIS) in Iowa is an excellently preserved complex crater that formed 65.7 Ma ago at the K/T boundary. Drill and seismic data have been used to identify three primary terranes within the 35-km diameter crater: (1) an outermost ring graben composed of listric normal fault blocks that structurally preserve Paleozoic and Cretaceous strata, impact ejecta, and possibly earliest Tertiary lake sediments; (2) a crater moat region of slumped and fallback materials overlain by Tertiary lake sediments in most areas; and (3) a central peak of uplifted basement rock capped in many areas by impact breccia. It is argued that concentrations of Ir at a K/T boundary exposure near Gubbio, Italy and clasts of glass reported from the K/T boundary in Haiti are consistent with possible production in the MIS.

Anderson, Raymond R.↗

NASA NTRS2006

Chemical Mapping of Proterozoic Organic Matter at Sub-Micron Spatial Resolution

We have used a NanoSIMS ion microprobe to map sub-micron-scale distributions of carbon, nitrogen, sulfur, silicon, and oxygen in organic microfossils and laminae from the approximately 0.85 Ga Bitter Springs Formation of Australia. The data provide clues about the original chemistry of the microfossils, the silicification process, and biosignatures of specific microorganisms and microbial communities. Chemical maps of fossil unicells and filaments reveal distinct wall-and sheath-like structures enriched in C, N and S, consistent with their accepted biological origin. Surprisingly, organic laminae, previously considered to be amorphous, also exhibit filamentous and apparently compressed spheroidal structures defined by strong enrichments in C, N and S. By analogy to data from the well-preserved microfossils, these structures are interpreted as being of biological origin, most likely representing densely packed remnants of microbial mats. Because the preponderance of organic matter in Precambrian sediments is similarly "amorphous," our findings open a large body of generally neglected material to in situ structural, chemical, and isotopic study. Our results also offer new criteria for assessing biogenicity of problematic kerogenous materials and thus can be applied to assessments of poorly preserved or fragmentary organic residues in early Archean sediments and any that might occur in meteorites or other extraterrestrial samples.

Oehler, Dorothy Z.↗

NASA NTRS1990

Structural behavior of composites with progressive fracture

Structural characteristics such as natural frequencies and buckling loads with corresponding mode shapes were investigated during progressive fracture of multilayer, angle-plied polymer matrix composites. A computer program was used to generate the numerical results for overall mechanical response of damaged composites. Variations in structural characteristics as a function of the previously applied loading were studied. Results indicate that most of the overall structural properties were preserved throughout a significant proportion of the ultimate fracture load. For the cases studied, changes in structural behavior began to occur after 70 percent of the ultimate fracture load was applied. However, the individual nature of the structural change was rather varied depending on the laminate configuration, fiber orientation, and the boundary conditions.

Minnetyan, Levon↗

DOE OSTI2024

Enriched Molecular-Level View of Saline Wetland Soil Carbon by Sensitivity-Enhanced Solid-State NMR

Soil organic matter (SOM) plays a major role in mitigating greenhouse gas emission and regulating earth’s climate, carbon cycle, and biodiversity. Wetland soils account for one-third of all SOM; however, globally, coastal wetland soils are eroding faster due to increasing sea-level rise. Our understanding of carbon sequestration dynamics in wetlands lags behind that of upland soils. Here, we employ solid-state nuclear magnetic resonance (ssNMR) to investigate the molecular-level structure of biopolymers in wetland soils spanning 11 centuries. High-resolution multidimensional spectra, enabled by dynamic nuclear polarization (DNP), demonstrate enduring preservation of molecular structures within herbaceous plant cores, notably condensing aromatic motifs and carbohydrates, even over a millennium, with the preserved cores constituting a decreasing minority among molecules from decomposition and repolymerization with depth and age. Such preserved cores occur alongside molecules from the decomposition of loosely packed parent biopolymers. These findings emphasize the relative vulnerability of coastal wetland SOM when exposed to oxygenated water due to geological and anthropogenic changes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Correlative montage parallel array cryo-tomography for in situ structural cell biology

Abstract Imaging large fields of view while preserving high-resolution structural information remains a challenge in low-dose cryo-electron tomography. Here we present robust tools for montage parallel array cryo-tomography (MPACT) tailored for vitrified specimens. The combination of correlative cryo-fluorescence microscopy, focused-ion-beam milling, substrate micropatterning, and MPACT supports studies that contextually define the three-dimensional architecture of cells. To further extend the flexibility of MPACT, tilt series may be processed in their entirety or as individual tiles suitable for sub-tomogram averaging, enabling efficient data processing and analysis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A Micrometer‐Sized Silicon/Carbon Composite Anode Synthesized by Impregnation of Petroleum Pitch in Nanoporous Silicon

Porous silicon (Si)/carbon nanocomposites have been extensively explored as a promising anode material for high-energy lithium (Li)-ion batteries (LIBs). However, shrinking of the pores and sintering of Si in the nanoporous structure during fabrication often diminishes the full benefits of nanoporous Si. Herein, a scalable method is reported to preserve the porous Si nanostructure by impregnating petroleum pitch inside of porous Si before high-temperature treatment. The resulting micrometer-sized Si/C composite maintains a desired porosity to accommodate large volume change and high conductivity to facilitate charge transfer. It also forms a stable surface coating that limits the penetration of electrolyte into nanoporous Si and minimizes the side reaction between electrolyte and Si during cycling and storage. A Si-based anode with 80% of pitch-derived carbon/nanoporous Si enables very stable cycling of a Si||Li(Ni0.5Co0.2Mn0.3)O 2 (NMC532) battery (80% capacity retention after 450 cycles). It also leads to low swelling in both particle and electrode levels required for the next generation of high-energy LIBs. In conclusion, the process also can be used to preserve the porous structure of other nanoporous materials that need to be treated at high temperatures.

anode materials↗