Search NASA⌕ Search

SEARCH · Search NASA

Results for “Space Based”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The origin of the Stokes–Einstein relation in simple dense liquids

Here, we investigate the origin of the universal relation between structural relaxation and diffusion in simple dense liquids, known as the Stokes–Einstein (SE) relation. The fact that this relation, originally derived from a hydrodynamic model of a macroscopic particle in a viscous medium, can describe the microscopic-scale liquid dynamics still eludes understanding. We introduce a new universal measure of structural relaxation in a system of N identical particles based on an explicit decomposition of the configuration space into N! congruent convex polyhedra. This measure makes it possible to quantify the correlation between two distinct particle configurations in terms of their minimal Euclidean distance, optimized with respect to particle permutations. Using this measure alongside a model of independent random walkers under the single-occupancy constraint, we derive a master equation that quantifies the SE relation. It allows us to demonstrate that the universal relation between structural relaxation and diffusion in simple dense liquids is caused by two conditions: (a) the confinement of the dominant density fluctuations to the first coordination shell, manifested by de Gennes narrowing, and (b) Gaussianity of the diffusion process; the former is shown to be violated in low-density fluids, and the latter is known to be violated in supercooled liquids.

Physics - Condensed matter physics↗
DOE OSTI2023

Spatially-resolved dynamic sampling of different phasic magnetic resonances of nanoparticle ensembles in a magnetotactic bacterium Magnetospirillum magnetotacticum

Abstract Nanoscaled magnetic particle ensembles are promising building blocks for realizing magnon based binary logic. Element-specific real-space monitoring of magnetic resonance modes with sampling rates in the GHz regime is imperative for the experimental verification of future complex magnonic devices. Here we present the observation of different phasic magnetic resonance modes using the element-specific technique of time-resolved scanning transmission x-ray microscopy within a chain of dipolarly coupled Fe 3 O 4 nanoparticles (40–50 nm particle size) inside a single cell of a magnetotactic bacterium Magnetospirillum magnetotacticum . The particles are probed with 25 nm resolution at the Fe L 3 x-ray absorption edge in response to a microwave excitation of 4.07 GHz. A plethora of resonance modes is observed within multiple particle segments oscillating in- and out-of-phase, well resembled by micromagnetic simulations.

time-resolved scanning transmission x-ray microsco↗
DOE OSTI2025

Aemulus ν: precision halo mass functions in wνCDM cosmologies

Precise and accurate predictions of the halo mass function for cluster mass scales in wνCDM cosmologies are crucial for extracting robust and unbiased cosmological information from upcoming galaxy cluster surveys. Here, we present a halo mass function emulator for cluster mass scales (≳ 1013 M ⊙/h) up to redshift z = 2 with comprehensive support for the parameter space of wνCDM cosmologies allowed by current data. Based on the Aemulus ν suite of simulations, the emulator marks a significant improvement in the precision of halo mass function predictions by incorporating both massive neutrinos and non-standard dark energy equation of state models. This allows for accurate modeling of the cosmology dependence in large-scale structure and galaxy cluster studies. We show that the emulator, designed using Gaussian Process Regression, has negligible theoretical uncertainties compared to dominant sources of error in future cluster abundance studies. Our emulator is publicly available (https://github.com/DelonShen/aemulusnu_hmf), providing the community with a crucial tool for upcoming cosmological surveys such as LSST and Euclid.

cluster counts↗
DOE OSTI2024

Modeling and ZVS Operation of the Isolated Modular Multilevel DC–DC Converter With a Unified Trapezoidal Wave Modulation

Here, this article introduces a unified trapezoidal wave (UTW) modulation scheme for the isolated modular multilevel dc–dc (IM2dc) converter, which consolidates multiple existing modulation strategies for the IM2dc converter, including the quasi-square wave (QSW) modulation, trapezoidal wave modulation, and sinusoidal wave modulation, into a unified framework. Furthermore, this article introduces the harmonic state-space (HSS) equations to model the IM2dc converter based on the UTW modulation method. The HSS model operates in the frequency domain, enabling it to circumvent the complexities associated with time-domain analysis and seamlessly integrate with the UTW modulation. This article proceeds to analyze the real and reactive power transfer characteristics of the IM2dc converter, as well as the power factor, considering the influence of multiple modulation parameters. Subsequently, it delves into the examination of zero voltage switching (ZVS) conditions for the IM2dc converter based on the UTW modulation and the HSS model. The complete ZVS boundaries of the IM2dc converter, taking various voltage ratios into account, are derived. This article also illustrates the effects of including harmonic orders in the modeling process, modulation parameters, and internal harmonic ripples on the ZVS boundaries. Finally, experimental validation of the analyses is conducted on a down-scaled prototype.

42 ENGINEERING↗
DOE OSTI2026

Towards Generalizable and Efficient Circuit Topology Design: A Graph-Transformer-based Surrogate Model with Curriculum Learning

Unlike circuit parameter and sizing optimizations, the automated design of analog circuit topologies poses significant challenges for learning-based approaches. One challenge arises from the combinatorial growth of the topology space with circuit size, which limits the topology optimization efficiency. Moreover, traditional circuit evaluation methods are time-consuming, while the presence of data discontinuity in the topology space makes the accurate prediction of circuit performance exceptionally difficult for unseen topologies. To tackle these challenges, we design a novel Graph-Transformer-based Network (GTN) as the surrogate model for circuit evaluation, offering a substantial acceleration in the speed of circuit topology optimization without sacrificing performance. Our GTN model architecture is designed to embed voltage changes in circuit loops and current flows in connected devices, enabling accurate performance predictions for circuits with unseen topologies. To address the cold start problem when scaling GTN to large-scale circuits, we further introduce a curriculum learning strategy that progressively trains GTN from small-scale to large-scale circuits. This approach enables the model to first learn fundamental physical principles from simpler topologies and gradually adapt to complex configurations, effectively bridging the circuit complexity gap and improving prediction accuracy. Taking the power converter circuit design as an experimental task, our GTN model significantly outperforms an analytical approach and baseline methods directly utilizing graph neural networks. Furthermore, GTN achieves less than 5% relative error and 196× speed-up compared with high-fidelity simulation. Notably, our GTN surrogate model empowers an automatic circuit design framework to discover circuits of comparable quality to those identified through high-fidelity simulation while reducing the time required by up to 98.2%. With curriculum learning, the enhanced GTN achieves a 51% improvement for performance prediction of large-scale circuits compared to the GTN model without this strategy. These advancements establish GTN as a scalable framework for automated analog circuit design across varying circuit complexity levels.

Lu, Haoshu [New Jersey Institute of Technology (NJ↗
DOE OSTI2021

EXPLAINABLE AND TRUSTWORTHY DIAGNOSTICS ACHIEVABLE THROUGH PROCESS-BASED AUTOMATED REASONING

An approach has been developed that incorporates domain knowledge to obtain a more explainable and trustworthy equipment health monitoring diagnosis than might otherwise be obtained from a purely data-driven method. Physics-based models serve to constrain the realizable solution space and render a more trusted diagnosis. An automated reasoning algorithm performs backward chaining to infer a diagnosis that is consistent with logic statements that have been evaluated as true. This diagnosis is made explainable to an operator by providing the forward chaining path that elucidates for inspection and validity testing those truths implied by the diagnosis.

automated reasoning↗
DOE OSTI2020

Computational Modeling To Adapt Neutralizing Antibody

Monoclonal antibodies (mAbs) is the leading therapy for viral infections because it provides immediate protection and can be administered at higher levels than in a natural immune response. Finding mAbs that neutralize a broad spectrum of viral targets has proven difficult because many species and strains exist and blanket targeting is a slow and laborious process to experimentally screen 108 variants. A new method is needed to rapidly redesign mAbs for homologous targets. This project speeds up redesign using structure-based computational design to reduce the mAbs search space to a manageable level and screen mutants at a much higher rate than in experiments. Computation will also provide critical knowledge about the fundamental interactions. The project will adapt S230, a human antibody that neutralizes SARS-CoV, to neutralize SARS-COV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Positrons for Our Future

JLab Users want beams of polarized (and unpolarized) positrons, with beam qualities and modes of operation similar to those provided in the electron beams at CEBAF today [Gra19]. The creation of positrons with a high degree of spin polarization is however very challenging – limited to beta decay, self-polarization in rings, or via e+/e- pair-production, a process requiring a source of polarized gamma rays. At JLab we have a unique source of polarized gamma rays – the bremsstrahlung radiation produced when the spin polarized electron beams of CEBAF interacts with matter – called Polarized Electrons for Polarized Positrons (or PEPPo) [Abb04]. This project sought to extend the PEPPo concept by exploring a possible layout and parameter space for a polarized positron injector at CEBAF based on this approach.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

DOE Support for the North American meeting of the International Society for Microbial Electrochemistry and Technology

The objective of the North American meeting of the International Society for Microbial Electrochemistry and Technology (NA-ISMET 2021, postponed from 2020 due to COVID-19) was to provide a welcoming space for an interdisciplinary group of researchers, primarily based in North America, to discuss their latest discoveries and innovative ideas on both basic science and applied technology in the field of microbial electrochemistry. After two years of limited travel and research interactions due to COVID-19, an in-person meeting was urgently needed to facilitate conversations and collaborations that help move the field forward. NA-ISMET 2021 was co-organized by Moh El-Naggar from the University of Southern California (USC) and Orianna Bretschger from Aquacycl Inc. The meeting took place on November 17 – 19, 2021 at the Michelson Center for Convergent Biosciences of USC. We hosted a total number of 65 registered participants from across the United States and several international participants. Thanks to the generous support from the Department of Energy, Air Force Office of Scientific Research, Office of Naval Research, the Army Research Office, the ISMET organization, and Gamry Instruments Inc., we were able to waive registration fees for all participants and reduce travel cost for several early-career researchers. The scientific program included 28 talks (16 from early-career researchers) and 24 posters that highlighted recent advances in microbial electrochemistry.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Reviewing Flexibility in Industrial Electrification: U.S. Green Ammonia and Steel Industries [Slides]

The renewable energy transition in the power sector involves a paradigm shift for flexibility. Supply flexibility faces new constraints due to the increased share of variable renewable resources. Increased demand flexibility can allow less use of peaking power plants and delay need for additional capacity and transmission. Industrial customers are larger on average than residential and commercial consumers and have typically provided the largest share of demand response in the United States. We consider industrial demand, studying characteristics of flexible industrial loads. We examine the dynamics of change occurring around industrial load flexibility by focusing on two case studies: green ammonia and steel production via electric arc furnaces. Electric arc furnace steel production is an important component of current demand response programs, whereas green ammonia and green fuels offer new paradigms for flexibility. We analyze the structure and functions of the technological innovation systems of load flexibility in those two industries via interviews with twenty-two stakeholders. We conclude that the technological innovation systems are not well-functioning for flexibility in EAF based steelmaking, but are in the green ammonia space. Explicit connections between scope two greenhouse gas emissions reporting and flexibility are lacking, and industry stakeholders do not appear to make a connection between decarbonization and load flexibility.

25 ENERGY STORAGE↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Building a quantum computing architecture using 3D superconducting cavities

Quantum computers promise advantages over classical machines for solving certain complex problems, but building processors that truly deliver this advantage remains a central challenge, particularly due to limited coherence times. Three-dimensional superconducting radio-frequency (SRF) cavities offer an attractive platform due to their exceptionally long lifetimes. However, since these harmonic systems require nonlinear elements, such as transmons, for control, additional losses are often introduced. In this talk, I will present a multimode quantum system based on an elliptical SRF cavity hosting two cavity modes weakly coupled to an ancillary transmon circuit. This architecture is carefully engineered to preserve coherence while enabling efficient control. By optimizing the design to mitigate transmon-induced decoherence, we realize single-photon lifetimes of 20.6 ms and 15.6 ms in the two modes, with pure dephasing times exceeding 40 ms. Using sideband interactions and error-resilient protocols, such as measurement-based correction and post-selection, we demonstrate high-fidelity state control, including preparation of Fock states up to N=20 with fidelities above 95% (to our knowledge, the highest reported to date), as well as high-fidelity two-mode entanglement. These results highlight 3D SRF cavities as a robust foundation for qudit-based quantum information processing, harnessing the large Hilbert space of cavity modes. I will conclude by outlining strategies to further enhance coherence in both cavities and ancilla qubits, and discuss pathways toward scaling this architecture into a larger quantum computing platform.

Roy, Tanay [Fermilab]↗
DOE OSTI2022

Physics Informed Reinforcement Learning for Power Grid Control using Augmented Random Search

Wide adoption of deep reinforcement learning need to overcome several challenges in energy system domain, including scalability, learning from limited samples, and high-dimensional continuous state and action spaces. In this paper, we integrated physics-based information from the normal generator operation state formula in the reinforcement learning agent's neural network loss function, and applied an augmented random search agent to optimize the generator control under dynamic contingency. Simulation results demonstrated the reliability performance improvements in training speed, reward convergence, sampling efficiency, scalability, and transferability.

physics informed ML, Physics Informed Neural Netwo↗
DOE OSTI2020

The Wave Energy Converter Design Process: Methods Applied in Industry and Shortcomings of Current Practices

Wave energy is among the many renewable energy technologies being researched and developed to address the increasing demand for low-emissions energy. The unique design challenges for wave energy converter design—integrating complex and uncertain technological, economic, and ecological systems, overcoming the structural challenges of ocean deployment, and dealing with complex system dynamics—have lead to a disjointed progression of research and development. There is no common design practice across the wave energy industry and there is no published synthesis of the practices that are used by developers. In this paper, we summarize the methods being employed in WEC design as well as promising methods that have yet to be applied. We contextualize these methods within an overarching design process. We present results from a survey of WEC developers to identify methods that are common in industry. From the review and survey results, we conclude that the most common methods of WEC design are iterative methods in which design parameters are defined, evaluated, and then changed based on evaluation results. This leaves a significant space for improvement of methods that help designers make better-informed decisions prior to sophisticated evaluation, and methods of using the evaluation results to make better design decisions during iteration. Despite the popularity of optimization methods in academic research, they are less common in industry development. We end this paper with a summary of the areas of WEC design in which the testing and development of new methods is necessary, and where more research is required to fully understand the influence of design decisions on WEC performance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Ferrotorryweiserite, Rh 5 Fe 10 S 16 , a New Mineral Species from the Sisim Placer Zone, Eastern Sayans, Russia, and the Torryweiserite–Ferrotorryweiserite Series

Ferrotorryweiserite, Rh 5 Fe 10 S 16 , occurs as small grains (≤20 µm) among droplet-like inclusions (up to 50 μm in diameter) of platinum-group minerals (PGM), in association with oberthürite or Rh-bearing pentlandite, laurite, and a Pt-Pd-Fe alloy (likely isoferroplatinum and Fe-Pd-enriched platinum), hosted by placer grains of Os-Ir alloy (≤0.5 mm) in the River Ko deposit. The latter is a part of the Sisim placer zone, which is likely derived from ultramafic units of the Lysanskiy layered complex, southern Krasnoyarskiy kray, Russia. The mineral is opaque, gray to brownish gray in reflected light, very weakly bireflectant, not pleochroic to weakly pleochroic (grayish to light brown tints), and weakly anisotropic. The calculated density is 5.93 g·cm –3 . Mean results (and ranges) of four WDS analyses are: Ir 18.68 (15.55–21.96), Rh 18.34 (16.32–20.32), Pt 0.64 (0.19–1.14), Ru 0.03 (0.00–0.13), Os 0.07 (0.02–0.17), Fe 14.14 (13.63–14.64), Ni 13.63 (12.58–14.66), Cu 4.97 (3.42–6.41), Co 0.09 (0.07–0.11), S 29.06 (28.48–29.44), and total 99.66 wt.%. They correspond to the following formula calculated for a total of 31 atoms per formula unit: (Rh 3.16 Ir 1.72 Pt 0.06 Ru 0.01 Os 0.01 ) Σ 4.95 (Fe 4.48 Ni 4.11 Cu 1.38 Co 0.03 ) Σ10.00 S 16.05 . The results of synchrotron micro-Laue diffraction studies indicate that ferrotorryweiserite is trigonal; its probable space group is $R\bar{3}m$ (#166) based on its Ni-analog, torryweiserite. The unit-cell parameters refined from 177 reflections are a = 7.069 (2) Å, c = 34.286 (11) Å, V = 1484 (1) Å 3 , and Z = 3. The c:a ratio is 4.8502. The strongest eight peaks in the X-ray diffraction pattern derived from results of micro-Laue diffraction study [d in Å(hkil)(I)] are 2.7950 ($20\bar{2}5$) (100); 5.7143 (0006) (60); 1.7671 ($22\bar{4}0$) (44.4); 3.0486 ($20\bar{2}1$) (39.4); 5.7650 ($10\bar{1}2$) (38.6); 2.5956 ($20\bar{2}7$) (37.8); 3.0058 ($11\bar{2}6$) (36.5); and 1.5029 ($4\bar{2}\bar{2}12$) (35.3). Ferrotorryweiserite and the associated PGM crystallized from microvolumes of residual melt at late stages of crystallization of grains of Os- and Ir-dominant alloys occurred in lode zones of chromitites of the Lysanskiy layered complex. In a particular case, the residual melt is disposed peripherally around a core containing a disequilibrium association of magnesian olivine (Fo 72.9–75.6 ) and albite (Ab 81.6–86.4 ), with the development of skeletal crystals of titaniferous augite: Wo 40.8–43.2 En 26.5–29.3 Fs 20.3–22.6 Aeg 6.9–9.5 (2.82–3.12 wt.% TiO 2 ). Ferrotorryweiserite represents the Fe-dominant analog of torryweiserite. We also report occurrences of ferrotorryweiserite in the Marathon deposit, Coldwell Complex, Ontario, Canada, and infer the existence of the torryweiserite–ferrotorryweiserite solid solution in other deposits and complexes.

58 GEOSCIENCES↗
DOE OSTI2025

CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves

We compare multiple foreground-cleaning pipelines for estimating the tensor-to-scalar ratio, r, using simulated maps of the planned CMB-S4 experiment within the context of the South Pole Deep Patch. To evaluate robustness, we analyze bias and uncertainty on r across various foreground suites using map-based simulations. The foreground-cleaning methods include: a parametric maximum likelihood approach applied to auto- and cross-power spectra between frequency maps; a map-based parametric maximum-likelihood method; and a harmonic-space internal linear combination using frequency maps. We summarize the conceptual basis of each method to highlight their similarities and differences. To better probe the impact of foreground residuals, we implement an iterative internal delensing step, leveraging a map-based pipeline to generate a lensing B-mode template from the large aperture telescope frequency maps. Our results show that the performance of the three approaches is comparable for simple and intermediate-complexity foregrounds, with σ(r) ranging from 3–5 ×10 −4 . However, biases at the 1σ–2σ level appear when analyzing more complex forms of foreground emission. By extending the baseline pipelines to marginalize over foreground residuals, we demonstrate that contamination can be reduced to within statistical uncertainties, albeit with a pipeline-dependent impact on σ(r), which translates to a detection significance between 2σ and 4σ for an input value of r = 0.003. These findings suggest varying levels of maturity among the tested pipelines, with the auto- and cross-spectra-based approach demonstrating the best stability and overall performance. Moreover, given the extremely low noise levels, mutual validation of independent foreground-cleaning pipelines is essential to ensure the robustness of any potential detection.

astronomy data analysis↗
DOE OSTI2020

Flashing ratchets

Provided herein are flashing ratchets that produce transport based on the oscillating application of regularly-spaced, asymmetric potentials. In particular, devices are provided that transport electrons without the requirement of an overall source-drain bias favoring electron transport.

42 ENGINEERING↗
DOE OSTI2022

Medium voltage planar DC bus distributed capacitor array

An inverter with a modular bus assembly is described. In various embodiments, the modular bus assembly includes a laminated motherboard and a plurality of capacitor daughtercards. The laminated motherboard can be configured to interface a plurality of phase-leg modules and a plurality of capacitor daughtercards through a plurality of terminals and connectors located on a bottom side or a top side of the laminated motherboard. The laminated motherboard includes a layer stack with a plurality of conductor layers. Each of the plurality of conductor layers is implemented with a net spacing from a neighboring plated through hole (PTH) based at least in part on differences in potential to be applied to each of the plurality of conductor layers as compared to a potential to be applied to the PTH. Embedded shield polygons can be implemented on the laminated motherboard to mitigate surface discharge at surface terminal (PTH/SMT) triple junctions.

Ravi, Lakshmi↗