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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tutorial: Machine-Learning-Based CREASE-2D Analysis of 2D SAXS Profiles to Characterize Anisotropic Nanostructures in Soft Materials

We present a tutorial to guide users on how to extend the Computational Reverse Engineering Analysis of Scattering Experiments-2D (CREASE-2D) framework to interpret their experimental two-dimensional small-angle scattering (SAS) data from soft materials (e.g., polymers, peptide amphiphiles, biomolecular fibrils). Unlike most traditional SAS analysis approaches, which typically rely on azimuthally averaged onedimensional (1D) profiles, CREASE-2D utilizes the complete 2D scattering profile to reveal information about anisotropy in the structure. In past applications, CREASE has provided insights into complex structural features, including the cross-sectional shapes of assembled nanostructures and dispersity in these features, which are difficult to discern with existing analytical models. While (1D- ) CREASE has been applied to SANS and SAXS data, this tutorial shares the steps for implementing CREASE-2D using an example of a dipeptide solution system, for which we have SAXS data. We present details for these steps involved in using CREASE-2D to interpret SAXS profiles: how to preprocess SAXS data, define relevant structural features, generate three-dimensional real-space structures for specific values of these features, train a machine learning (ML) surrogate model to predict scattering profiles for given structural features, and optimize these features using genetic algorithms (GA). Then, we use these steps to interpret complex 2DSAXS data collected from dipeptide solutions that, in microscopy images, exhibit nanoscale structures that could be elliptical tubes/ flat tapes/cylinders or a combination of these cross sections. Open-source codes, computational hardware, and software requirements, as well as the strengths and limitations of this protocol, are also presented. We expect researchers working with (soft) biomaterials, peptide amphiphiles, amphiphilic polymer solutions, polymer nanocomposites, and blends of particles/polymers will find this CREASE-2D method and this tutorial of use.

CREASE↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A model for the fragmentation kinetics of crumpled thin sheets

As a confined thin sheet crumples, it spontaneously segments into flat facets delimited by a network of ridges. Despite the apparent disorder of this process, statistical properties of crumpled sheets exhibit striking reproducibility. Experiments have shown that the total crease length accrues logarithmically when repeatedly compacting and unfolding a sheet of paper. Here, we offer insight to this unexpected result by exploring the correspondence between crumpling and fragmentation processes. We identify a physical model for the evolution of facet area and ridge length distributions of crumpled sheets, and propose a mechanism for re-fragmentation driven by geometric frustration. This mechanism establishes a feedback loop in which the facet size distribution informs the subsequent rate of fragmentation under repeated confinement, thereby producing a new size distribution. We then demonstrate the capacity of this model to reproduce the characteristic logarithmic scaling of total crease length, thereby supplying a missing physical basis for the observed phenomenon.

42 ENGINEERING↗
DOE OSTI2024

Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI : Preprint

Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.

artificial intelligence↗
DOE OSTI2020

Giant Superelastic Piezoelectricity in Flexible Ferroelectric BaTiO3 Membranes

Mechanical displacement in commonly used piezoelectric materials is typically restricted to linear or biaxial in nature and to a few percent of the material dimensions. Here in this paper, we show that free-standing BaTiO 3 membranes exhibit nonconventional electromechanical coupling. Under an external electric field, these superelastic membranes undergo controllable and reversible “sushi-rolling-like” 180° folding–unfolding cycles. This crease-free folding is mediated by charged ferroelectric domains, leading to giant >3.8 and 4.6 μm displacements for a 30 nm thick membrane at room temperature and 60 °C, respectively. Further increasing the electric field above the coercive value changes the fold curvature, hence augmenting the effective piezoresponse. Finally, it is found that the membranes fold with increasing temperature followed by complete immobility of the membrane above the Curie temperature, allowing us to model the ferroelectric domain origin of the effect.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Teleconnections of the Quasi–Biennial Oscillation in a multi–model ensemble of QBO–resolving models

The quasi-biennial oscillation (QBO) dominates the interannual variability of the tropical stratosphere and influences other regions of the atmosphere. The high predictability of the QBO implies that its teleconnections could lead to in-creased skill of seasonal and decadal forecasts provided the relevant mechanisms are accurately represented in models. Here modelling and sampling uncertainties of QBO teleconnections are examined using a multi-model ensemble of QBO-resolving atmospheric general circulation models that have carried out a set of coordinated experiments as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi). During Northern Hemisphere winter the stratospheric polar vortex in most of these models strengthens when the QBO near 50 hPa is westerly and weakens when it is easterly, consistent with, but weaker than, the observed response. These weak responses are likely due to model errors, such as systematically weak QBO amplitudes near 50 hPa, affecting the teleconnection. The teleconnection to the North Atlantic Oscillation is less well captured overall, but of similar strength to the observed signal in the few models that do show it. Furthermore, the models do not show clear evidence of a QBO teleconnection to the Northern Hemisphere Pacific sector subtropical jet.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modulation of thermal conductivity of iron-doped ß-Ga2O3 by helium-ion irradiation

This study examines the impact of helium-ion irradiation on the thermal conductivity of ß-Ga2O3. A laser-based spatial domain thermoreflectance technique is used to investigate thermal conductivity map for both un-irradiated and irradiated ß-Ga2O3, which are then validated against simulation results derived from density functional theory-based phonon transport simulations. Since helium bubble evolution was ob- served at the nanoscale using transmission electron microscopy, the simulation study was carried out on eight distinct helium-induced sites in ß-Ga2O3. Our findings indicate a reduction in thermal conductivity for the irradiated samples. Experimental results show a significant reduction in thermal conductivity in irradiated samples, with de- creases of approximately 25% along the [100] direction and 40% along [001] directions. Phonon transport simulations closely replicate these findings, particularly when helium occupying interstitial sites, predicting reductions of ˜53% along [100] and ˜50% along [001] directions. This work underscores the role of irradiation-induced microstructural changes in the heat transport properties of ß-Ga2O3 which is crucial for its application in sensor devices in extreme environments.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Simulation of crumpled sheets via alternating quasistatic and dynamic representations

In this work, we present a method for simulating the large-scale deformation and crumpling of thin, elastoplastic sheets. Motivated by the physical behavior of thin sheets during crumpling, two different formulations of the governing equations of motion are used: (1) a quasistatic formulation that effectively describes smooth deformations, and (2) a fully dynamic formulation that captures large changes in the sheet's velocity. The former is a differential-algebraic system of equations integrated implicitly in time, while the latter is a set of ordinary differential equations (ODEs) integrated explicitly. We adopt a hybrid integration scheme to adaptively alternate between the quasistatic and dynamic representations as appropriate. Further, we demonstrate the capacity of this method to effectively simulate a variety of crumpling phenomena. Finally, we show that statistical properties, notably the accumulation of creases under repeated loading, as well as the area distribution of facets, are consistent with experimental observations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Moisture-mineral interactions drive bacterial and organic matter turnover in glacier-sourced riparian sediments undergoing pedogenesis

Glacial recession is occurring at unprecedented rates resulting in increased sediment accumula-tions in some riverine ecosystems. Increased sediment deposition has implications for ecosystem stability (e.g., floods and river paths) and environmental services (e.g., carbon sequestration). Soils and sediments have an enormous potential to retain carbon (C), predominantly due to sorp-tion to mineral surfaces. However, C persistence may be sensitive to climate-change induced temperature and moisture variations. We coupled ultrahigh resolution organic matter composition classification with bacterial characterization and respiration measurements to test the combined effects of temperature (4 vs 20°C) and moisture (50 vs 100% water-filled pore space) on C turn-over in sediments maintained under different mineralogical conditions (illite-amended vs non-amended). Here we show that the inhibition of CO 2 emissions from the combined effect of in-creased moisture content and illite was reflected in the turnover of key molecular signatures, such as the nominal oxidation state of C, often irrespective of temperature. However, shifts in bacteri-al communities from a coupled moisture-mineral interaction, were temperature-dependent. Our results highlight the importance of moisture in driving mineral-organic interactions and suggest that C in clay-rich, water-saturated sediments is both thermodynamically unfavorable and miner-al-protected from microbial consumption.

58 GEOSCIENCES↗
DOE OSTI2022

Correlative Nanoscale Imaging of Strained hBN Spin Defects

Spin defects like the negatively charged boron vacancy color center (V B - ) in hexagonal boron nitride (hBN) may enable new forms of quantum sensing with near-surface defects in layered van der Waals heterostructures. Here, the effect of strain on V B - color centers in hBN is revealed with correlative cathodoluminescence and photoluminescence microscopies. Strong localized enhancement and redshifting of the V B - luminescence is observed at creases, consistent with density functional theory calculations showing V B - migration toward regions with moderate uniaxial compressive strain. The ability to manipulate spin defects with highly localized strain is critical to the development of practical 2D quantum devices and quantum sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Strain-Based Chemiresistive Polymer-Coated Graphene Vapor Sensors

Suspended chemiresistive graphene sensors have been fabricated using well-established nanofabrication techniques to generate sensors that are highly sensitive to pyridine and with excellent discrimination between polar and nonpolar analytes. When coated with a polymer surface layer and suspended on 3-D patterned glass electrodes, a hybrid combination of polymer and graphene yields chemiresistive vapor sensors. Expansion and contraction of the polymer layer produces strain on the suspended graphene (Gr). Hence, when organic vapors permeate into the polymer layer, the high gauge factor of the graphene induces substantial electrical resistive changes as folds and creases are induced in the graphene. The hybrid suspended polymer/Gr sensor exhibits substantial responses to polar organic vapors, especially pyridine, while also exhibiting reversibility and increased discrimination between polar and nonpolar analytes compared to previous approaches. This sensor design also allows for potential tunability in the types of polymers used for the reactive surface layer, allowing for use in a variety of potential applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Shape memory in self-adapting colloidal crystals

We report reconfigurable, mechanically responsive crystalline materials are central components in many sensing, soft robotic, and energy conversion and storage devices1,2,3,4. Crystalline materials can readily deform under various stimuli and the extent of recoverable deformation is highly dependent upon bond type1,2,5,6,7,8,9,10. Indeed, for structures held together via simple electrostatic interactions, minimal deformations are tolerated. By contrast, structures held together by molecular bonds can, in principle, sustain much larger deformations and more easily recover their original configurations. In this report we study the deformation properties of well-faceted colloidal crystals engineered with DNA. These crystals are large in size (greater than 100 µm) and have a body-centred cubic (bcc) structure with a high viscoelastic volume fraction (of more than 97%). Therefore, they can be compressed into irregular shapes with wrinkles and creases, and, notably, these deformed crystals, upon rehydration, assume their initial well-formed crystalline morphology and internal nanoscale order within seconds. For most crystals, such compression and deformation would lead to permanent, irreversible damage. The substantial structural changes to the colloidal crystals are accompanied by notable and reversible optical property changes. For example, whereas the original and structurally recovered crystals exhibit near-perfect (over 98%) broadband absorption in the ultraviolet–visible region, the deformed crystals exhibit significantly increased reflection (up to 50% of incident light at certain wavelengths), mainly because of increases in their refractive index and inhomogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electric field reversals resulting from voltage waveform tailoring in Ar/O 2 capacitively coupled plasmas sustained in asymmetric systems

The etching of nanometer scale high-aspect-ratio (HAR) features into dielectric materials in low pressure radio frequency excited plasmas is often accompanied by charge accumulation inside the features which can slow etching rates and produce distortions such as twisting. The intra feature charging is at least partially produced by differences in electron and ion energy and angular distributions (EADs). Positive ions, accelerated to high energies having narrow angular spreads by the sheath electric field, can penetrate deeply into HAR features. Electrons typically arrive at the wafer with nearly thermal and isotropic distributions and do not penetrate deeply into HAR features. These disparities lead to differential charging of the inside of the feature, which can lead to reductions in etch rate and feature distortion due to ion deflection. With in-creasing aspect ratio of features, charging challenges are expected to continue for the foreseeable future. In this work, the use of tailored voltage waveforms in geometrically asymmetric capacitively coupled plasmas sustained in Ar/O 2 at 40 mTorr was computationally investigated with the goal of shaping the EAD of electrons incident onto the substrate to address differential charging. The tailored waveform consisted of a sinusoidal wave and its higher harmonics with a fundamental frequency of 1 MHz. Further, we found that electric field reversals in the sheath and presheath can occur during the anodic portion of the cycle. The electric field reversal increases the energy and decreases the angular spread of electrons incident onto the substrate. The magnitude of the electric field reversal can be controlled by the phase angle of the even harmonics and the gas composition. Due to its electronegative nature, increasing mole fractions of O 2 impedes electron transport to the surface which further increases the electric field reversal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Microscopic ergodicity breaking governs the emergence and evolution of elasticity in glass-forming nanoclay suspensions

We report a study combining x-ray photon correlation spectroscopy (XPCS) with in situ rheology to investigate the microscopic dynamics and mechanical properties of aqueous suspensions of the synthetic hectorite clay Laponite, which is composed of charged, nanometer-scale, disk-shaped particles. The suspensions, with particle concentrations ranging from 3.25 to 3.75 wt%, evolve over time from a fluid to a soft glass that displays aging behavior. The XPCS measurements characterize the localization of the particles during the formation and aging of the soft-glass state. The fraction of localized particles f 0 increases rapidly during the early formation stage and grows more slowly during subsequent aging, while the characteristic localization length r loc steadily de- creases. Despite the strongly varying rates of aging at different concentrations, both f 0 and r loc scale with the elastic shear modulus G' in a manner independent of concentration. During the later aging stage, the scaling between r loc and G' agrees quantitatively with a prediction of naive mode coupling theory. Breakdown of agreement with the theory during the early formation stage indi- cates the prevalence of dynamic heterogeneity, suggesting the soft solid forms through precursors of dynamically localized clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cosimulating Integrated Energy Systems With Heterogeneous Digital Twins: Matching a Connected World

Energy system integration promises in-creased resiliency and the unlocking of synergies, while also contributing to our goal of decarbonization. It is enabled by both old and new technologies, glued together with data and digital services. Hydrolyzers, heat pumps, distributed renewable generation, smart buildings, and the digital grid edge are all currently the subject of integration with the power system and the energy sector at large. To plan and operate such a multidisciplinary and multisectoral system properly, insight, tools, and expertise are all needed. Further, this is exactly where the state of the art fails to deliver: tools for integrated energy systems (IESs) are still in their infancy, and many times, even academia treats these sectors separately, producing experts in each of them but not across.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Effects of nitrogen enrichment on tree carbon allocation: A global synthesis

Aim: Increased atmospheric nitrogen deposition may have profound effects on tree carbon allocation dynamics. However, a comprehensive understanding of how nitro-gen (N) enrichment influences carbon (C) allocation across plant functional processes and tree organs in individual trees remains elusive. Location: Global forest ecosystems. Time period: 1990–2018. Major taxa studied: Trees. Methods: We compiled data from 75 N addition experiments and conducted a meta-analysis to evaluate the responses of C source (photosynthesis), sinks (growth and respiration) and storage (non-structural carbohydrate concentrations) in different tree organs (foliage, above-ground wood and roots) to N enrichment. Results: N enrichment significantly enhanced C supply via photosynthesis (+39.6%, n = 128). C allocation to growth (biomass increment/production) significantly in-creased in foliage (+15.9%, n = 68) and above-ground wood (+31.8%, n = 64; bole, branch, stem and/or twig) with increasing N availability, but not in roots, whereas allocation increased in roots via increasing fine root turnover rate (+22.6%, n = 11). N fertilization significantly increased C allocation to respiration in above-ground wood (+46.6%, n = 12) and roots (+5.5%, n = 57), but not in foliage. N addition decreased non-structural carbohydrate (NSC) concentrations in foliage (-5.4%, n = 16) and roots (-5.0%, n = 21), but increased NSC in above-ground wood (+6.1%, n = 22). In addition, N enrichment effects were strongly affected by moderator variables. Main conclusions: Our results demonstrate that N addition increased C allocation to growth and respiration more strongly than C allocation to NSC storage, and increased C allocation to above-ground parts more strongly than to below-ground parts. Our results are useful for better understanding the response of tree functional processes at organ level to N enrichment. The existing data also reveal that more long-term ex-perimental studies on mature trees in tropical and boreal forests are urgently needed to provide a basis for forecasting tree responses to N enrichment at the global scale.

Li, Weibin↗
DOE OSTI2020

Pattern formation on free surfaces via plastic buckling and periodic folding

Spontaneous formation of surface patterns such as folds and creases is widely observed in engineered systems, such as thin films and machined surfaces, as well as in natural systems such as floral petals and leaves. A recognized route for their formation is via surface elastic instabilities. Here we demonstrate an alternate route for their formation —plastic buckling and folding—that occurs when ductile materials are subject to large-strain (>1) deformation. Using in situ imaging of simple-shear deformation of polypropylene, we delineate the mechanics underlying formation of folds and the resulting surface morphology. Here, the fold pattern shows a single wavelength that scales linearly with the size of the plastic zone. An analytical model predicts onset of the plastic buckling instability and characteristics of the folds. Besides obvious applications for controllably generating surface features over large areas, our results suggest a contributing mechanism for origin of surface roughness in solids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗