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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗
DOE OSTI2020

Microscale Observation via High-Speed X-ray Diffraction of Alloy 718 During In Situ Laser Melting

The laser melting process is accompanied by rapid evolution in temperature, phase, structure, and strain because of its high heating and cooling rates. In this study, the evolution of grains within a thin solid plate of Ni alloy 718 during laser processing was probed with in situ high-energy x-ray diffraction experiments. The high temporal and spatial resolution available in the measurement allowed us to study the rapid evolution of the melted region beneath the surface of the sample. The characterization of the evolution of secondary phases, i.e., Laves and carbide, was captured despite the weak diffracted peaks caused by small volume fractions. Thermal history was estimated based on changes in the lattice spacing from the thermal contraction upon cooling. In conclusion, the temporal variation in 2θ with azimuthal direction revealed the evolution in anisotropy of lattice spacing and thus of the mechanical state during laser processing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A framework for strategic discovery of credible neural network surrogate models under uncertainty

The widespread integration of deep neural networks in developing data-driven surrogate models for high-fidelity simulations of complex physical systems highlights the critical necessity for robust uncertainty quantification techniques and credibility assessment methodologies, ensuring the reliable deployment of surrogate models in consequential decision-making. Here, this study presents the Occam Plausibility Algorithm for surrogate models (OPAL-surrogate), providing a systematic framework to uncover predictive neural network-based surrogate models within the large space of potential models, including various neural network classes and choices of architecture and hyperparameters. The framework is grounded in hierarchical Bayesian inferences and employs model validation tests to evaluate the credibility and prediction reliability of the surrogate models under uncertainty. Leveraging these principles, OPAL-surrogate introduces a systematic and efficient strategy for balancing the trade-off between model complexity, accuracy, and prediction uncertainty. The effectiveness of OPAL-surrogate is demonstrated through two modeling problems, including the deformation of porous materials for building insulation and turbulent combustion flow for ablation of solid fuels within hybrid rocket motors.

42 ENGINEERING↗
DOE OSTI2022

Unsupervised learning from three-component accelerometer data to monitor the spatiotemporal evolution of meso-scale hydraulic fractures

Enhanced geothermal systems can provide a substantial share of the global energy demand. There exist several hurdles in the engineering implementations of such geothermal systems. One such hurdle is the accurate monitoring of the fracture networks created in subsurface through hydraulic stimulation of these systems. Micro seismicity associated with the stimulation is the primary means to locate the event hypocenters for estimating the stimulated rock volume. Existing methods for location the hypocenters are restricted to only the highest amplitude impulsive signals that are simultaneously detected on several sensors. Consequently, a large portion (usually ~99%) of the measurements are left unused. In this paper, an unsupervised manifold-approximation followed by clustering of 3-component accelerometer data is used to analyze the seismicity recorded on a monitoring well. With this method, a larger portion of the measured signal is used for the monitoring of the hydraulic fracture network. We analyze the EGS Collab experiment 1 microseismic data, recorded at the Sanford Underground Research Facility, South Dakota. Using the data from a single three-component accelerometer, the polarization features viz. Azimuth, incidence, rectilinearity, and planarity are used as inputs for the unsupervised manifold approximation followed by clustering. Our study shows that density-based clusters in the projected 3D space correspond to distinct types of hydraulically fractured zones around the injection point. Finally, we show that the temporal evolution of these clusters can be used to track fracture creation and propagation.

58 GEOSCIENCES↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Examining the potential for detecting simultaneous noble gas and aerosol samples in the international monitoring system radionuclide network

The purpose of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) is to establish a legally binding ban on nuclear weapon test explosions or any other nuclear explosions. The Preparatory Commission for the CTBT Organization (CTBTO PrepCom) is developing the International Monitoring System (IMS) that includes a global network of 80 stations to monitor for airborne radionuclides upon entry into force of the CTBT. All 80 radionuclide stations will monitor for particulate radionuclides and at least half of the stations will monitor for radioxenon. The airborne radionuclide monitoring is an important verification technology both for the detection of a radionuclide release and in the determination of whether the release event originates from a nuclear explosion as opposed to an industrial use of nuclear materials. Nuclear power plants and many medical isotope production facilities release radioxenon into the atmosphere. Low levels of a few particulate isotopes, such as iodine, may also be released. Detections of multiple isotopes are useful for screening the radionuclide samples for relevance to the Treaty. This paper examines the anticipated joint detections in the IMS of noble gas and particulate isotopes from underground nuclear explosions where breaches in the underground containment vents from low levels to up to 1% of the radionuclide inventory of the resulting fission products to the atmosphere. Detection probabilities are based on 844 simulated release events spaced out at 17 release locations and one year in time. Six different release (venting) scenarios, including two fractionated scenarios, were analyzed. When ranked by detection probability, 11 particulate isotopes and one noble gas isotope ( 133 Xe) appear in the top 20 isotopes for all six release scenarios. Using the 11 particulate isotopes and the one noble gas isotope, the IMS has nearly the same detection probability as when 45 particulate and 4 noble gas isotopes are used. Thus, a limited list of relevant radionuclides may be sufficient for treaty verification purposes. The probability that at least one particulate and at least one radioxenon isotope would be detected in the IMS from the release events ranged from 0.15 to 0.86 depending on the release scenario.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

The effect of hydroxyl spacing in diols on the solvation structure, dynamics, and transport properties of choline chloride-based deep eutectic solvents

Deep eutectic solvents (DESs) are a class of liquids that offer great potential in alleviating some of the challenges present in today's long-term energy storage methods because they have physical properties that are favorable for storable electrolyte solutions. In this work, a series of glycols (ethylene glycol, 1,3-propanediol, 1,4-butanediol, and 1,5-pentanediol) were studied as potential hydrogen bond donors (HBD) with a common choline chloride (ChCl) as the hydrogen bond acceptor (HBA). The solvation dynamics of the prepared systems were studied by measuring the solvent reorganization response using femtosecond transient absorption spectroscopy (fs-TA). Conductivity, viscosity, density, ET(30) polarity, and dynamics of the prepared DESs were analyzed, with a particular interest in determining the effect of HBD chain length on these parameters. Here, classical molecular dynamics simulations were employed to investigate how the local liquid structure, solvent dynamics, and bulk solvent properties vary with changes in glycol chain length.

Conductivity↗
DOE OSTI2025

Morphological Heterogeneity Impact of Film Solid-State Cathode on Utilization and Fracture Dynamics

Structural heterogeneity in solid-state batteries can impact material utilization and fracture mechanisms. Crystallographically oriented lithium cobalt oxide film cathodes serve as a model electrode system for exploring how void distribution contributes to stress relief and build up during cycling. Real- and reciprocal-space operando and ex situ synchrotron based experiments are utilized to understand structural changes across multiple length scales contribute to stress generation and fracture. Nanotomography uncovers a depth-dependent porosity variation in the pristine electrode and highlights preferential fracture in regions of lower porosity during delithiation. Energy-dispersive X-ray diffraction and 3D X-ray absorption near-edge spectroscopy (XANES) reveal the underutilization of cathode material in these regions. 3D XANES also confirms preferential delithiation near the sub-grain boundaries. Chemo-mechanical modeling coupled with site-specific mechanical characterization demonstrate how stress accumulation in dense regions of the electrode leads to fracture and underutilization of active material. In conclusion, our findings reveal the importance of materials design to alleviate stress in small-volume changing cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Deterministic Fabrication of Large-Area, High-Crystallinity Oxide Moiré Superlattices

Oxide twistronics extends moiré engineering beyond van der Waals materials, offering a promising platform for accessing emergent interfacial phenomena arising from the strong coupling of lattice, charge, and orbital degrees of freedom in complex oxides. However, deterministic fabrication of high-crystallinity oxide moiré superlattices over large lateral dimensions remains challenging due to the three-dimensional bonding network of oxides. Here, we demonstrate a scalable, generalized fabrication strategy that enables the formation of high-crystallinity oxide moiré superlattices with clean, chemically bonded interfaces and precisely controlled twist angles down to nominal values of 0.1°, achieving subdegree twist-angle accuracy across large contiguous lateral dimensions approaching the millimeter scale. Using NaNbO3 as a model system, we show that the resulting interlayer coupling drives pronounced structural reconstruction that modifies both the phase structure and ferroelectric domain configuration. Synchrotron-based X-ray 3D reciprocal space mapping reveals the emergence of a single-phase state in twisted bilayers, in contrast to the mixed-phase structure observed in single-layer membranes prior to twist assembly. The structural signatures are further consistent with gradual lattice rotation distributed along the thickness direction that may accommodate interfacial shear strain, distinct from reconstruction observed in van der Waals moiré systems which primarily occurs through in-plane stacking rearrangement. This collective lattice response is correlated with twist-dependent nanoscale electromechanical modulations observed by piezoresponse force microscopy. These results establish a scalable materials platform for oxide twistronics and support the implementation of twist-engineered functionalities in practical, macroscale device architectures.

Ghanbari, Reza [North Carolina State University (N↗
DOE OSTI2020

Analysis of Electric and Magnetic Lightning-Generated Wave Amplitudes Measured by the Van Allen Probes

Herein we provide a statistical analysis of both electric and magnetic field wave amplitudes of very low frequency lightning-generated waves (LGWs) based on the equivalent of 11.5 years of observations made by the Van Allen Probes encompassing ~24.6 × 10 6 survey mode measurements. We complement this analysis with data from the ground-based World Wide Lightning Location Network to explore differences between satellite and ground-based measurements. LGW mean amplitudes are found to be low compared with other whistler mode waves (1 ± 1.6 pT and 19 ± 59 μV/m). Extreme events (1/5,000) can reach 100 pT and contributes strongly to the mean power below $L$ = 2. We find excellent correlations between World Wide Lightning Location Network-based power and wave amplitudes in space at various longitudes. We reveal strong dayside ionospheric damping of the LGW electric field. LGW amplitudes drop for $L$ < 2, contrary to the Earth's intense equatorial lightning activity. We conclude that it is difficult for equatorial LGW to propagate and remain at $L$ < 2.

Electric wave power↗
DOE OSTI2020

Analysis of Fault Zone Resonance Modes Recorded by a Dense Seismic Array Across the San Jacinto Fault Zone at Blackburn Saddle

We present observations and modeling of spatial eigen-functions of resonating waves within fault zone waveguide, using data recorded on a dense seismic array across the San Jacinto Fault Zone (SJFZ) in southern California. The array consists of 5-Hz geophones that cross the SJFZ with ~10-30 m spacing at the Blackburn Saddle near the Hemet Stepover. Wavefield snapshots after the S wave arrival are consistent for more than 50 near-fault events, suggesting that this pattern is controlled by the fault zone structure rather than source properties. Data from example event with high signal to noise ratio shows three main frequency peaks at ~1.3 Hz, ~2.0 Hz, and ~2.8 Hz in the amplitude spectra of resonance waves averaged over stations near the fault. The data are modeled with analytical expressions for eigen-functions of resonance waves in a low-velocity layer (fault zone) between two quarter-spaces. Using a grid search-based method, we investigate the possible width of the waveguide, location within the array, and shear wave velocities of the media that fit well the resonance signal at ~1.3 Hz. The results indicate a ~300 m wide damaged fault zone layer with ~65% S wave velocity reduction compared to the host rock. The SW edge of the low-velocity zone is near the mapped fault surface trace, indicating that the damage zone is asymmetrically located at the regionally faster NE crustal block. The imaging resolution of the fault zone structure can be improved by modeling fault zone resonance modes and trapped waves together.

58 GEOSCIENCES↗
DOE OSTI2022

Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials science. However, naive Monte Carlo approaches, on which such calculations are often dependent, struggle to scale to complex materials in many state-of-the-art disciplines such as the design of high entropy alloys or multi-component catalysts. To address this issue, we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ensemble. Furthermore, we show that the resulting models are transferable across wide ranges of thermodynamic conditions and can be implemented with any internal energy model U, allowing integration into many existing materials workflows. We demonstrate the applicability of this approach to the simulation of benchmark systems (AgPd, CuAu) that exhibit diverse thermodynamic behavior in their phase diagrams. Finally, we discuss remaining challenges in model development and promising research directions for future improvements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spin-optomechanical cavity interfaces by deep subwavelength phonon-photon confinement

A central goal of quantum information science is transferring qubits between space, time, and modality. Spin-based systems in solids are promising quantum memories, but high-fidelity transfer of their quantum states to telecom optical fields remains challenging. Here, we introduce a phonon-mediated interface between spins in a diamond nanobeam optomechanical crystal and telecom optical fields by a simultaneous deep-subwavelength confinement of optical and acoustic fields with mode volumes $V_{\textrm{mech}}$$/Λ^3_\textrm{p} ~ 10^{-5}$ and $V_{\textrm{opt}}$$/λ^3 ~ 10^{−3}$, respectively. This confinement boosts the spin-mechanical coupling rate of Group-IV silicon vacancy (SiV − ) centers by an order of magnitude to ~ 32 MHz while retaining high acousto-optical couplings. The optical cavity couples to the spin irrespective of the emitter’s native excited states, avoiding spectral diffusion. Using Quantum Monte Carlo simulations, we estimate heralded entanglement fidelities exceeding 0.96 between two such interfaces. We anticipate broad utility beyond diamond emitter-telecom systems to most solid-state quantum memories.

Raniwala, Hamza [Massachusetts Inst. of Technology↗
DOE OSTI2023

Hallucination of closed repeat proteins containing central pockets

In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dark-field X-ray microscopy with structured illumination for three-dimensional imaging

Dark-field X-ray microscopy is a lens-based technique that enables real-space imaging of heterogeneous micro- and meso-scale ordered materials. However, achieving accurate three-dimensional (3D) reconstruction often requires meticulous sample alignment or rastering, requiring complex rotational setups and extended acquisition times. To address these challenges, we introduce a structured illumination technique optimized for 3D imaging of ordered materials at sub-micrometer length scales. Our approach employs a coded aperture to spatially modulate the incident X-ray beam, enabling 3D structural reconstruction from images captured at various aperture positions. Unlike current 3D imaging approaches, which often rely on rotational or rastering methods, our technique uses scanning X-ray silhouettes of the coded aperture for depth resolution along the diffraction axis. This eliminates the need for sample rotation or rastering, resulting in a highly stable and efficient imaging modality. We validated the efficacy of this approach through experimental imaging of an isolated twin domain within a bulk single crystal of an iron pnictide using a dark-field X-ray microscope. This advancement aligns with the enhanced brightness upgrades of modern synchrotron radiation facilities, unlocking new possibilities for high-resolution imaging of ordered materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration

Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a passivating layer on a variety of titanium alloys for structural and functional applications. These oxides tend to be structurally diverse, featuring polymorphic phases, grain boundaries, and amorphous regions that generate a disparate set of unique local environments for hydrogen. Here, we introduce a workflow that can efficiently and accurately navigate this complexity. First, a machine learning force field, trained on ab initio molecular dynamics simulations, was used to generate amorphous configurations. Density functional theory calculations were then performed on these structures to identify local oxygen environments, which were compared against experimental observations. Second, to classify subtle differences across the disordered configuration space, we employ a graph-based sampling procedure. Finally, local hydrogen binding energies and hopping kinetics are computed using exhaustive density functional theory calculations on representative configurations. Here, we leverage this methodology to show that hydrogen binding energetics are described by local oxygen coordination, which in turn is affected by stoichiometry, and form the basis of hopping kinetics and diffusion. Together these results imply that hydrogen incorporation and transport in TiO x can be tailored through compositional engineering, with implications for improving the performance and durability of titanium-derived alloys in hydrogen environments.

36 MATERIALS SCIENCE↗