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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mechanisms of Three-Dimensional Solid-Phase Epitaxial Crystallization of Strontium Titanate

Strontium titanate (SrTiO 3 , STO) is a complex metal oxide with a cubic perovskite crystal structure. Due to its easily described and understood crystal structure in the cubic phase, STO is an ideal model system for exploring the mechanistic details of solid-phase epitaxy (SPE) in complex oxides. SPE is a crystallization approach that aims to guide crystal growth at low homologous temperatures to achieve targeted microstructures. Beyond planar thin films, SPE can also exploit the addition of a chemically inert, noncrystallizing, amorphous obstacle in the path of crystallization to generate complex three-dimensional structures. The introduction of this mask fundamentally alters the SPE process, inducing a transition from two- to three-dimensional geometries and from vertical to lateral crystal growth under the influence of the crystal/mask/amorphous boundary. Using a combination of molecular dynamics simulations and experiments, we identify several unique phenomena in the nanoscale growth behaviors in both conventional (unmasked) and masked SPE. Examining conventional SPE of STO, we find that crystallization at the interface is strongly correlated to, and potentially driven by, density fluctuations in the region of the amorphous STO near the crystalline/amorphous interface with a strong facet dependence. In the masked case, we find that the crystalline growth front becomes nonplanar near contact with the mask. We also observe a minimum vertical growth requirement prior to lateral crystallization. Both phenomena depend on the relative bulk and interfacial free energies of the three-phase (crystal/mask/amorphous) system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Band Energy Dependence of Defect Formation in the Topological Semimetal Cd3As2

Cadmium Arsenide (Cd3As2) is a prototypical Dirac semimetal that manifests topological properties in a 3D bulk material. In defect-free Cd3As2, the Fermi level lies at a minimum in the density of states at the Dirac point, but experimentally it forms with excess electron carriers and an elevated EF, thereby masking the topological features. To computationally study the self-doping of Cd3As2, we combine density functional theory (DFT) calculations for defect formation energies with quasi-particle self-consistent GW (QSGW) electronic structure calculations. We demonstrate an innate dependence of the point defect formation energies on carrier concentrations and use the QSGW calculated density of states to extrapolate formation energies to arbitrary electron concentrations. This approach allows the quantitative modeling of thermodynamic defect equilibria in topological semimetals and is used to predict how Cd3As2 growth conditions affect the position of EF relative to the Dirac point.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2021

Tunable, Bacterio-Instructive Scaffolds Made from Functional Graphenic Materials

The balance of bacterial populations in the human body is critical for human health. Researchers have aimed to control bacterial populations using antibiotic substrates. However, antibiotic materials that non-selectively kill bacteria can compromise health by eliminating beneficial bacteria, which leaves the body vulnerable to colonization by harmful pathogens. Due to their chemical tunablity and unique surface properties, graphene oxide (GO)-based materials – termed “functional graphenic materials” (FGMs) – have been previously designed to be antibacterial but have the capacity to actively adhere and instruct probiotics to maintain human health. Numerous studies have demonstrated that negatively and positively charged surfaces influence bacterial adhesion through electrostatic interactions with the negatively charged bacterial surface. We found that tuning the surface charge of FGMs provides an avenue to control bacterial attachment without compromising vitality. Using E. coli as a model organism for gram-negative bacteria, we demonstrate that negatively charged Claisen graphene (CG), a reduced and carboxylated FGM, is bacterio-repellent through electrostatic repulsion with the bacterial surface. Though positively charged poly-L-lysine (PLL) is antibacterial when free in solution by inserting into the bacterial cell wall, here, we found that covalent conjugation of PLL to CG (giving PLLn-G) masks the antimicrobial activity of PLL by restricting polypeptide mobility. This allows the immobilized positive charge of the PLLn-Gs to be leveraged for E. coli adhesion through electrostatic attraction. We identified the magnitude of positive charge of the PLLn-G conjugates, which is modulated by the length of the PLL peptide, as an important parameter to tune the balance between the opposing forces of bacterial adhesion and proliferation. We also tested adhesion of gram-positive B. subtilis to these FGMs and found that the effect of FGM charge is less pronounced. B. subtilis adheres nondiscriminatory to all FGMs, regardless of charge, but adhesion is scarce and localized. Overall, this work demonstrates that FGMs can be tuned to selectively control bacterial response, paving the way for future development of FGM-based biomaterials as bacterio-instructive scaffolds through careful design of FGM surface chemistry.

Eckhart, Karoline E.↗
DOE OSTI2024

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A reference-area-free strain mapping method using precession electron diffraction data

Here, in this work, we developed a method using precession electron diffraction data to map the residual elastic strain at the nano-scale. The diffraction pattern of each pixel was first collected and denoised. Template matching was then applied using the center spot as the mask to identify the positions of the diffraction disks. Statistics of distances between the selected diffracted disks enable the user to make an informed decision on the reference and to generate strain maps. Strain mapping on an unstrained single crystal sapphire shows the standard deviation of strain measurement is 0.5%. With this method, we were able to successfully measure and map the residual elastic strain in VO 2 on sapphire and martensite in a Ni 50.3 Ti 29.7 Hf 20 shape memory alloy. This approach does not require the user to select a “strain-free area” as a reference and can work on datasets even with the crystals oriented away from zone axes. This method is expected to provide a robust and more accessible alternative means of studying the residual strain of various material systems that complements the existing algorithms for strain mapping.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Simulation-Based Inference for Neutrino Interaction Model Tuning

This project demonstrates, for the first time, the application of simulation-based inference (SBI) techniques to tune neutrino–nucleus interaction models. Using a mock dataset based on the MicroBooNE tuning of the GENIE event generator, our approach employs a Neural Posterior Estimator (NPE) with Masked Autoregressive Flows (MAF) to infer the posterior distributions of key GENIE parameters directly from simulated histograms. The workflow provides a scalable and amortized framework for performing likelihood-free inference in high-dimensional parameter spaces, offering a pathway to more efficient and uncertainty-aware model tuning for next-generation neutrino experiments such as DUNE and SBND.

Tame-Narvaez, KarlaMaria [Fermi National Accelerat↗
DOE OSTI2020

Bat Impact Minimization Technology: An Improved Bat Deterrent for the Full Swept Rotor Area of Any Wind Turbine

The growth in the number of wind turbine generators has led to a significant number of fatal interactions with bat species. The need to reduce the number of bat fatalities while minimizing power losses is the greatest conservation challenge for wind energy development in parts of the country, according to the American Wind Wildlife Institute. Technological solutions that can also allow turbines to operate normally would generate the maximum electricity and avoid financial losses. Bats use echolocation to perceive their surroundings by listening to features of echoes from their high frequency vocal signals reflecting from targets. In this project, Frontier Wind built on previous research demonstrating that ultrasonic noise can mask echolocation and act as a repellent or deterrent to bat flight activity. Whereas the initial study only broadcast ultrasonic transmissions from the center of the turbine, the Strike Free™ system developed for this project extended the ultrasonic coverage to the entire area swept by the turbine blades. Frontier Wind designed the system components and their integration and then tested them in the lab and in the field at Pattern Energy’s Hatchet Ridge Wind Facility near Redding, California. The researchers used an acoustic model to determine the optimal configuration of transmitters along the blades to provide sound transmission coverage across the turbine rotor swept area volume. The custom ultrasonic transmitters were designed specifically for the echolocation frequencies of the four main bat species that have been shown to have died at Hatchet Ridge, although the transmitters can be customized for different frequencies as needed in other geographic locations. The Strike Free™ system shows promise for reducing bat fatalities, and the path to commercialization requires further testing to validate and optimize performance in the field.

17 WIND ENERGY↗
DOE OSTI2022

TEAMER: DAISY Flow-noise Testing (Abstract)

Evaluating impacts of marine energy devices is generally difficult given the dynamic environment where these devices need to be placed. The University of Washington’s (UW) DAISY (The Drifting Acoustic Instrumentation SYstem) is designed to measure radiated noise around marine energy converters operating in energetic waves and currents. In currents, a primary limitation for measurement fidelity at low frequencies (< 100 Hz) is the potential for non-propagating “flow-noise” to mask propagating sound and inflate estimates of the radiated noise from marine energy converters at frequencies that overlap with hearing sensitivities of fish and some marine mammals. While free-drifting measurements help to minimize the relative velocity that produces flow-noise, significant levels were still observed during initial DAISY tests. This motivated the development of a fabric “flow shield” around the hydrophone that disrupts both flow-noise generation mechanisms proposed by the initial tests. First, the flow shield is a source of substantial drag which keeps the hydrophone package moving with the approximate velocity of the surrounding water, compensating for differential wind or current forcing on the surface expression. By minimizing relative velocity around the hydrophone, turbulence shed by the hydrophone is also minimized. Second, the flow shield creates a largely quiescent pocket around the hydrophone, minimizing advection of free stream turbulence over the hydrophone element. Field data collected in these experiments will test effectiveness of these flow shields and provide quantitative data use and deployment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A novel CMB component separation method: hierarchical generalized morphological component analysis

ABSTRACT We present a novel technique for cosmic microwave background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to generalized morphological component analysis (GMCA), we introduce hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on Nside = 256 simulated sky maps that include dust, synchrotron, free–free, and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25{{\ \rm per\ cent}}$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the 0.02–0.03 per cent level at ℓ > 200 (and $\lt 0.26{{\ \rm per\ cent}}$ for all ℓ), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art internal linear combination type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free X-ray wavefronts

A neural-network machine learning model is developed to control a bimorph adaptive mirror to achieve and preserve aberration-free coherent X-ray wavefronts at synchrotron radiation and free electron laser beamlines. The controller is trained on a mirror actuator response directly measured at a beamline with a real-time single-shot wavefront sensor, which uses a coded mask and wavelet-transform analysis. The system has been successfully tested on a bimorph deformable mirror at the 28-ID IDEA beamline of the Advanced Photon Source at Argonne National Laboratory. It achieved a response time of a few seconds and maintained desired wavefront shapes (e.g., a spherical wavefront) with sub-wavelength accuracy at 20 keV of X-ray energy. This result is significantly better than what can be obtained using a linear model of the mirror’s response. The developed system has not been tailored to a specific mirror and can be applied, in principle, to different kinds of bending mechanisms and actuators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Cobalt-Group 13 Complexes Catalyze CO 2 Hydrogenation via a Co(-I)/Co(I) Redox Cycle

The Co(-I) dihydrogen complexes, [(η 2 -H 2 )CoML]-, where ML is the group 13 metalloligand, N(o-(NCH 2 PiPr 2 )C 6 H 4 ) 3 M, and M is Al, Ga, or In, were previously reported ( J. Am. Chem. Soc. 2017, 139, 6570-6573). In this work, the related Co(-I) end-on dinitrogen adducts, [(N 2 )CoML]-, were isolated and investigated as precatalysts for CO 2 hydrogenation. The Co–Ga catalyst was highly active, achieving 19,200 formate turnovers with an initial turnover frequency of 27,000 h –1 under 34 atm of 1:1 CO 2 /H 2 and using Verkade’s proazaphosphatrane as a base at ambient temperature. The Co–Al catalyst was moderately active, while the Co–In complex was inactive. Hence, tuning the group 13 ion greatly influences the catalytic activity at the Co site. To elucidate the role of the group 13 support, experimental and theoretical mechanistic studies of the Co–Ga and Co–Al catalysts were conducted. The Co(-I) H 2 species are potent hydride donors with estimated thermodynamic hydricities (ΔG° H– ) of 32.0(1) and 37.4(1) kcal/mol in CH 3 CN for M = Al and Ga, respectively. By acting as masked Co(I) dihydrides, the Co(-I) H 2 species operate via an unusual Co(-I)/Co(I) redox cycle. After hydride transfer to CO 2 , the resulting intermediate is the Co(I) hydride complex, HCoML, which was independently synthesized and structurally characterized for M = Al and Ga. The Gibbs free energy for H 2 binding, ΔG° bind (1 atm), to generate (η 2 -H 2 )HCoML was slightly more favorable for HCoGaL (-4.2(1) kcal/mol) than for HCoAlL (-2.7(1) kcal/mol). In the subsequent step, the deprotonation reaction to regenerate the initial catalyst was much more favorable for (η 2 -H 2 )HCoGaL (pK a of 31.4, CH 3 CN) than for (η 2 -H 2 )HCoAlL (pK a of 34.3). Finally, the straightforward substitution of Al with Ga perturbs the energy profile of the catalytic reaction (|ΔΔG° H– | = 5.4 kcal/mol, |ΔΔG° bind | = 1.5 kcal/mol, and |ΔΔG° K a | = 4.0 kcal/mol) and thus provides a thermodynamic rationale for the higher catalytic efficiency of Co–Ga over Co–Al.

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

Dark energy survey year 3 results: likelihood-free, simulation-based w CDM inference with neural compression of weak-lensing map statistics

We present simulation-based cosmological wcold dark matter (wCDM) inference using dark energy survey year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky pkdgrav3 dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock dark energy survey lensing data sets. For wCDM inference, for which we allow –1 < w < –$\frac{1}{3}$⁠, our most constraining result uses power spectra combined with map-level (CNN) inference. Using gravitational lensing data only, this map-level combination gives Ω m = 0.283$^{+0.020}_{–0.027}$⁠, S 8 = 0.804$^{+0.025}_{–0.017⁠}$, and w < –0.80 (with a 68 per cent credible interval); compared to the power spectrum inference, this is more than a factor of two improvement in dark energy parameter (Ω⁠ DE , w⁠) precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Editorial overview: Unlocking the secrets of nongenetic plasticity, one cell at a time

Cellular noise, the non-genetic variability observed among isogenic cells, arises from factors such as growth conditions, aging, and stochastic gene expression, influencing cell stress-response, metabolism, morphology, and size. Here, such plasticity, while critical for adaptation, often goes unnoticed with traditional population-averaging biotechnologies that inevitably mask cell-specific variations and prompting the question, "What else might we be missing". However, recent breakthroughs in optical imaging, microfluidics, and omics, are beginning to uncover the complexity of cellular plasticity. This special is-sue highlights some of these breakthroughs, with key contributions including innovations in multimodal chemical imaging, label-free microscopy, spatial and temporal omics, and droplet-based microfluidics. Collectively, these cutting-edge tools provide unprecedent-ed insights into non-genetic cell-to-cell variability, enhancing our understanding of cellu-lar plasticity and its implications for health, energy, and ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

At-wavelength characterization of X-ray wavefronts in Bragg diffraction from crystals

The advent of next-generation synchrotron radiation sources and X-ray free-electron lasers calls for high-quality Bragg-diffraction crystal optics to preserve the X-ray beam coherence and wavefront. This requirement brings new challenges in characterizing crystals in Bragg diffraction in terms of Bragg-plane height errors and wavefront phase distortions. Here, a quantitative methodology to characterize crystal optics using a state-of-the-art at-wavelength wavefront sensing technique and statistical analysis is proposed. The method was tested at the 1-BM-B optics testing beamline at the Advanced Photon Source for measuring silicon and diamond crystals in a self-referencing single-crystal mode and an absolute double-crystal mode. The phase error sensitivity of the technique is demonstrated to be at the λ/100 level required by most applications, such as the characterization of diamond crystals for cavity-based X-ray free-electron lasers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery

Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.

42 ENGINEERING↗
DOE OSTI2024

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗