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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Gravity-driven controls on fluid and carbonate precipitation distributions in fractures

Abstract Many challenges related to carbon-dioxide ( $$\hbox {CO}_2$$ CO 2 ) sequestration in subsurface rock are linked to the injection of fluids through induced or existing fracture networks and how these fluids are altered through geochemical interactions. Here, we demonstrate that fluid mixing and carbonate mineral distributions in fractures are controlled by gravity-driven chemical dynamics. Using optical imaging and numerical simulations, we show that a density contrast between two miscible fluids causes the formation of a low-density fluid runlet that increases in areal extent as the fracture inclination decreases from 90 $$^\circ$$ ∘ (vertical fracture plane) to 30 $$^\circ$$ ∘ . The runlet is sustained over time and the stability of the runlet is controlled by the gravity-driven formation of 3D vortices that arise in a laminar flow regime. When homogeneous precipitation was induced, calcium carbonate covered the entire surface for horizontal fractures (0 $$^\circ$$ ∘ ). However, for fracture inclinations greater than 10 $$^\circ$$ ∘ , the runlet formation limited the areal extent of the precipitation to less than 15% of the fracture surface. These insights suggest that the ability to sequester $$\hbox {CO}_2$$ CO 2 through mineralization along fractures will depend on the fracture orientation relative to gravity, with horizontal fractures more likely to seal uniformly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Laser-metal interaction dynamics during additive manufacturing resolved by detection of thermally-induced electron emission

In situ monitoring is required to improve the understanding and increase the reliability of additive manufacturing methods such as laser powder bed fusion (LPBF). Current diagnostic methods for LPBF capture optical images, X-ray radiographs, or measure the emission of thermal or acoustic signals from the component. Herein, a methodology based on the thermal emission of electrons - thermionic emission - from the metal surface during LPBF is proposed which can resolve laser-material interaction dynamics. The high sensitivity of thermionic emission to surface temperature and surface morphology is revealed to enable precise determination of the transition between conduction and keyhole mode melting regimes. Increases in thermionic emission are correlated to laser scanning conditions that give rise to pore formation and regions where surface defects are pronounced. The information presented here is a critical step in furthering our understanding and validation of laser-based metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The edges of galaxies: Tracing the limits of star formation

The outskirts of galaxies have been studied from multiple perspectives for the past few decades. However, it is still unknown if all galaxies have clear-cut edges similar to everyday objects. We address this question by developing physically motivated criteria to define the edges of galaxies. Based on the gas density threshold required for star formation, we define the edge of a galaxy as the outermost radial location associated with a significant drop in either past or ongoing in situ star formation. We explore ~1000 low-inclination galaxies with a wide range in morphology (dwarfs to ellipticals) and stellar mass (10 7 M ⊙ < M * < 10 12 M ⊙ ). The location of the edges of these galaxies (R edge ) were visually identified as the outermost cutoff or truncation in their radial profiles using deep multi-band optical imaging from the IAC Stripe82 Legacy Project. We find this characteristic feature at the following mean stellar mass density, which varies with galaxy morphology: 2.9 ± 0.10 M ⊙ pc -2 for ellipticals, 1.1 ± 0.04 M ⊙ pc -2 for spirals, and 0.6 ± 0.03 M ⊙ pc -2 for present-day star-forming dwarfs. Additionally, we find that R edge depends on its age (colour) where bluer galaxies have larger R edge at a fixed stellar mass. The resulting stellar mass–size plane using R edge as a physically motivated galaxy size measure has a very narrow intrinsic scatter (≲0.06 dex). These results highlight the importance of new deep imaging surveys to explore the growth of galaxies and trace the limits of star formation in their outskirts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Euclid I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg 2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

cosmology↗
DOE OSTI2023

Insulators at fractional fillings in twisted bilayer graphene partially aligned to hexagonal boron nitride

At partial fillings of its flat electronic bands, magic-angle twisted bilayer graphene (MATBG) hosts a rich variety of competing correlated phases that show sample-to-sample variations. Divergent phase diagrams in MATBG are often attributed to the sublattice polarization energy scale, tuned by the degree of alignment of the hexagonal boron nitride (hBN) substrates typically used in van der Waals devices. Unaligned MATBG exhibits unconventional superconductor and correlated insulator phases, while nearly perfectly aligned MATBG/hBN exhibits zero-field Chern insulating phases and lacks superconductivity. Here we use scanning tunneling microscopy and spectroscopy (STM/STS) to observe gapped phases at partial fillings of the flat bands of MATBG in a new intermediate regime of sublattice polarization, observed when MATBG is only partially aligned (θ Gr-hBN ≈ 1.65°) to the underlying hBN substrate. Under this condition, MATBG hosts not only phenomena that naturally interpolate between the two sublattice potential limits, but also unexpected gapped phases absent in either of these limits. At charge neutrality, we observe an insulating phase with a small energy gap (Δ < 5 meV) likely related to weak sublattice symmetry breaking from the hBN substrate. In addition, we observe new gapped phases near fractional fillings ν = ±1/3 and ν = ±1/6, which have not been previously observed in MATBG. Importantly, energy-resolved STS unambiguously identifies these fractional filling states to be of single-particle origin, possibly a result of the super-superlattice formed by two moiré superlattices. Finally, our observations emphasize the power of STS in distinguishing single-particle gapped phases from many-body gapped phases in situations that could be easily confused in electrical transport measurements, and demonstrate the use of substrate engineering for modifying the electronic structure of a moiré flat-band material.

Physics↗
DOE OSTI2020

Ultrasonication-assisted trace amount solvent synthesis of Cs 4 PbBr 6 crystal with ultra-bright green light emission

Cs 4 PbBr 6 crystals have been synthesized by an ultrasonication-assisted trace amount polar solvent method. The prepared green Cs 4 PbBr 6 material was found to have high photoluminescence (PL) brightness and 10 ns PL lifetime. The prepared green light emitting device can achieve the maximum brightness of 3.8 × 10 9 cd/m 2 , which is nearly 100 times higher than a wick. The white light emitting device based on Cs 4 PbBr 6 crystals has better performance than commercial products, which can cover 32.3% of the color gamut and achieves 107.3% coverage for International Commission on Illumination (CIE)1931 and 84.8% coverage for CIE1976.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spall and subsequent recompaction of copper under shock loading

Research was undertaken to study spall and subsequent recompaction of oxygen-free high-thermal-conductivity copper using a single-stage large-bore light gas gun capable of planar impacts. Gun experiments were conducted that produced an initial spall in the target with a subsequent recompaction of the spall damage/layer by the use of layered impactors. Symmetric spall experiments at similar conditions were also conducted as a control to the recompaction experiments. Photonic Doppler velocimetry was used to obtain the velocity history of the target’s back surface; these velocity histories were analyzed, and the results were compared to numerical simulations. After recovery of selected samples, the microstructure was analyzed using optical imaging microscopy and electron backscatter diffraction. Recompaction waves were clearly observed in the time-resolved data obtained at the back surface of the targets. Two different series of experiments were performed to understand the effect of damage morphology on the stress required for spall recompaction. In the initial series, the peak pressure of the first shock was systematically increased to alter the amount of damage in the material. While in the second series, the peak pressure of the second shock was increased, keeping the magnitude of the first shock relatively constant to understand the effect of peak stress on the recompaction process. Findings clearly show that recompaction results in a perturbed band of the microstructure at the location of the expected spall plane in all cases except where the peak stress of the second shock is lower than the critical value.

, recompaction↗
DOE OSTI2021

Raster Thomson scattering in large-scale laser plasmas produced at high repetition rate

We present optical Thomson scattering measurements of electron density and temperature in a large-scale (~2 cm) exploding laser plasma produced by irradiating a solid target with a high energy (5-10 J) laser pulse at high repetition rate (1 Hz). The Thomson scattering diagnostic matches this high repetition rate. Unlike previous work performed in single shots at much higher energies, the instrument allows point measurements anywhere inside the plasma by automatically translating the scattering volume using motorized stages as the experiment is repeated at 1 Hz. Measured densities around 4×10 16 cm -3 and temperatures around 7 eV result in a scattering parameter near unity, depending on the distance from the target. The measured spectra show the transition from collective scattering close to the target to non-collective scattering at larger distances. Densities obtained by fitting the weakly collective spectra agree to within 10% with an irradiance calibration performed via Raman scattering in nitrogen.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Membrane potential sensing: Material design and method development for single particle optical electrophysiology

We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spatio-temporal ablation dynamics and plasma chemistry of aluminum induced by temporally modulated ytterbium fiber laser

Here, in this work, we studied single-pulse ablation dynamics of a temporally modulated continuous wave laser-material interaction with Al using in situ multimodal time-resolved diagnostics that describe in detail the associated physical and chemical processes. Time-resolved scattering, emission imaging, and optical emission spectroscopy unveiled a sequence of events spread out across three distinct phases: (i) early phase ablation process, associated with particle generation and liquid Al column formation (<20 μs), (ii) secondary detonation when sufficient ejected material is accumulated over the surface (20-50 μs), and (iii) molten liquid Al pool oscillation on the surface, followed by large droplet ejection from the liquid pool (100-500 μs). Atomic Al and AlO were observed with optical emission spectroscopy at different ratios during the entire lifetime of the event, verifying the formation of oxidized Al vapor upon its interaction with air. Morphological and compositional characterization confirmed surface oxidation and material re-solidification in the form of protrusions produced during the irradiation process. This work provides insights into the complex physical and chemical mechanisms of single-pulse ablation in the sub-millisecond laser pulse regime, which are critically important for parameter optimization in a variety of laser processing, microfabrication, and deposition applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Compact high repetition rate Thomson parabola ion spectrometer

Here, we present the development of a compact Thomson parabola ion spectrometer capable of characterizing the energy spectra of various ion species of multi-MeV ion beams from >10 20 W/cm 2 laser produced plasmas at rates commensurate with the highest available from any of the current and near-future PW-class laser facilities. This diagnostic makes use of a polyvinyl toluene based fast plastic scintillator (EJ-260), and the emitted light is collected using an optical imaging system coupled to a thermoelectrically cooled scientific complementary metal–oxide–semiconductor camera. This offers a robust solution for data acquisition at a high repetition rate, while avoiding the added complications and nonlinearities of micro-channel plate based systems. Different ion energy ranges can be probed using a modular magnet setup, a variable electric field, and a varying drift-distance. We have demonstrated operation and data collection with this system at up to 0.2 Hz from plasmas created by irradiating a solid target, limited only by the targeting system. With the appropriate software, on-the-fly ion spectral analysis will be possible, enabling real-time experimental control at multi-Hz repetition rates.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Direct mechanistic connection between acoustic signals and melt pool morphology during laser powder bed fusion

Various nondestructive diagnostic techniques have been proposed for in situ process monitoring of laser powder bed fusion (LPBF), including melt pool pyrometry, whole-layer optical imaging, acoustic emission, atomic emission spectroscopy, high speed melt pool imaging, and thermionic emission. Correlations between these in situ monitoring signals and defect formation have been demonstrated with acoustic signals having been shown to predict pore formation with especially high confidence in recent machine learning studies. Here, in this work, time-resolved acoustic data are collected in both the conduction and keyhole welding regimes of LPBF-processed Ti-6Al-4V alloy. A non-dimensionalized Strouhal number analysis, used in whistle aeroacoustics, is applied to demonstrate that the acoustic signals recorded in the keyhole regimes can be directly associated with the vapor depression morphology. This mechanistic understanding developed from whistle aeroacoustics shows that acoustic monitoring during the LPBF process can provide a direct probe into the vapor depression dynamics and defect occurrence, especially in the keyhole regimes relevant to printing and defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2020

Bragg grating inscription in photosensitive materials by an optical replication process

This paper examines the feasibility of producing multiplexed Bragg gratings for use as diffractive optical elements (DOEs) by coherent optical replication of a surface-relief phase grating into thick-film photosensitive materials. The use of such DOEs in light guide plates (LGPs) for optical imaging systems ensures energy-efficient light input into and output from LGPs and allows one to minimise their weight and size. We present simulation results for the interference structure fabrication process and recording of a series of multiplexed diffraction gratings in photosensitive materials. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Glass/glass photovoltaic module reliability and degradation: a review

Glass/glass (G/G) photovoltaic (PV) module construction is quickly rising in popularity due to increased demand for bifacial PV modules, with additional applications for thin-film and building-integrated PV technologies. G/G modules are expected to withstand harsh environmental conditions and extend the installed module lifespan to greater than 30 years compared to conventional glass/backsheet (G/B) modules. With the rapid growth of G/G deployment, understanding the outdoor performance, degradation, and reliability of this PV module construction becomes highly valuable. In this review, we present the history of G/G modules that have existed in the field for the past 20 years, their subsequent reliability issues under different climates, and methods for accelerated testing and characterization of both cells and packaging materials. We highlight some general trends of G/G modules, such as greater degradation when using poly(ethylene-co-vinyl acetate) (EVA) encapsulants, causing the industry to move toward polyolefin-based encapsulants. Transparent backsheets have also been introduced as an alternative to the rear glass for decreasing the module weight and aiding the effusion of trapped gaseous degradation products in the laminate. New amendments to IEC 61215 standard protocols for G/G bifacial modules have also been proposed so that the rear side power generation and UV exposure will be standardized. We further summarize a suite of destructive and non-destructive characterization techniques, such as current-voltage scans, module electro-optical imaging, adhesion tests, nanoscale structural/chemical investigation, and forensic analysis, to provide deeper insights into the fundamental properties of the module materials degradation and how it can be monitored in the G/G construction. This will set the groundwork for future research and product development.

14 SOLAR ENERGY↗
DOE OSTI2026

Magneto-optical study of Nb thin films for superconducting qubits

Abstract Among the recognized sources of decoherence in superconducting qubits, the spatial inhomogeneity of the superconducting state and the possible presence of magnetic-flux vortices remain comparatively underexplored. Niobium is commonly used as a structural material in transmon qubits that host Josephson junctions, and excess dissipation anywhere in the transmon can become a bottleneck that limits overall quantum performance. The metal/substrate interfacial layer may simultaneously host pair-breaking loss channels (e.g. two-level systems) and control thermal transport, thereby affecting dissipation and temperature stability. Here, we use quantitative magneto-optical imaging of the magnetic-flux distribution to characterize the homogeneity of the superconducting state and the critical current density, j c , in niobium films fabricated under different sputtering conditions. The imaging reveals distinct flux-penetration regimes, ranging from a nearly ideal Bean critical state to strongly nonuniform thermo-magnetic dendritic avalanches. By fitting the measured magnetic-induction profiles, we extract j c and try to correlate it with film physical properties and with measured qubit internal quality factors. Our results indicate that the Nb/Si interlayer can be a significant contributor to decoherence and should be considered an important factor that must be optimized.

Datta, Amlan [Ames National Laboratory; Iowa State↗
DOE OSTI2020

Deep transfer learning for star cluster classification: I. application to the PHANGS– HST survey

ABSTRACT We present the results of a proof-of-concept experiment that demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in Hubble Space Telescope(HST) ultraviolet-optical imaging of nearby spiral galaxies ($D\lesssim 20\, \textrm{Mpc}$) in the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS)–HST survey. Given the relatively small nature of existing, human-labelled star cluster samples, we transfer the knowledge of state-of-the-art neural network models for real-object recognition to classify star clusters candidates into four morphological classes. We perform a series of experiments to determine the dependence of classification performance on neural network architecture (ResNet18 and VGG19-BN), training data sets curated by either a single expert or three astronomers, and the size of the images used for training. We find that the overall classification accuracies are not significantly affected by these choices. The networks are used to classify star cluster candidates in the PHANGS–HST galaxy NGC 1559, which was not included in the training samples. The resulting prediction accuracies are 70 per cent, 40 per cent, 40–50 per cent, and 50–70 per cent for class 1, 2, 3 star clusters, and class 4 non-clusters, respectively. This performance is competitive with consistency achieved in previously published human and automated quantitative classification of star cluster candidate samples (70–80 per cent, 40–50 per cent, 40–50 per cent, and 60–70 per cent). The methods introduced herein lay the foundations to automate classification for star clusters at scale, and exhibit the need to prepare a standardized data set of human-labelled star cluster classifications, agreed upon by a full range of experts in the field, to further improve the performance of the networks introduced in this study.

Wei, Wei↗