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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Merger Signatures are Common, but not Universal, in Massive, Recently Quenched Galaxies at z ~ 0.7

We present visual classifications of merger-induced tidal disturbances in 143 M* ~ 10 11 M ⊙ post-starburst galaxies at z ~ 0.7 identified in the $SQuIGG\vec{L}E$ Sample. This sample spectroscopically selects galaxies from the Sloan Digital Sky Survey that have stopped their primary epoch of star formation within the past ~500 Myr. Visual classifications are performed on Hyper Suprime-Cam imaging. We compare to a control sample of mass- and redshift-matched star-forming and quiescent galaxies from the Large Early Galaxy Census and find that post-starburst galaxies are more likely to be classified as disturbed than either category. This corresponds to a factor of $3.6$$^{+2.9}_{-1.3}$ times the disturbance rate of older quiescent galaxies and $2.1$$^{+1.9}_{-.73}$ times the disturbance rate of star-forming galaxies. Assuming tidal features persist for ≲500 Myr, this suggests merging is coincident with quenching in a significant fraction of these post-starbursts. Galaxies with tidal disturbances are younger on average than undisturbed post-starburst galaxies in our sample, suggesting tidal features from a major merger may have faded over time. This may be exacerbated by the fact that, on average, the undisturbed subset is fainter, rendering low-surface-brightness tidal features harder to identify. However, the presence of 10 young (≲150 Myr since quenching) undisturbed galaxies suggests that major mergers are not the only fast physical mechanism that shut down the primary epoch of star formation in massive galaxies at intermediate redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Bayesian Optimization of Catalysis with In-Context Learning

Large language models (LLMs) can perform accurate classification with zero or few examples through in-context learning (ICL), allowing the model to observe query-relevant examples at inference time and eliminating the need for additional weight updates to generalize beyond its original training data. We extend this capability to regression with uncertainty estimation using frozen LLMs (e.g., GPT-4o, Gemini), enabling Bayesian optimization (BO) in natural language without explicit model training or feature engineering. We apply this to materials discovery by representing materials as synthesis and testing procedures for use in natural language prompts. This Bayesian, design-first approach prioritizes optimization toward target material properties before detailed characterization, in contrast to conventional experimental workflows that often emphasize characterization of suboptimal materials. On benchmarks like aqueous solubility and oxidative coupling of methane (OCM), BO-ICL matches or outperforms Gaussian processes. In live experiments on the reverse water–gas shift (RWGS) reaction, BO-ICL identifies multimetallic catalysts that approach equilibrium CO yield within 6 and 10 iterations from a pool of 3,700 and 360,000 candidates, respectively. Our method redefines materials representation and accelerates discovery, with broad applications across catalysis, materials science, and AI.

Calibration↗
DOE OSTI2025

Geometric control of hyperbolic exciton-polariton condensate dimers

Coupled many-body quantum systems exhibit rich emergent physics with diverse stationary and dynamical behaviours. By engineering platforms with tunable and distinct coupling mechanisms, new insights emerge into the collective behaviour of coupled many body systems. Particles can be exchanged via evanescent or ballistic coupling: the former, based on proximity, yields large spectral splitting, while the latter requires strict phase-matching, analogous to phase-coupled harmonic oscillators and has a smaller impact on the energy landscape. We demonstrate an all-optically tunable quantum fluid dimer based on exciton-polariton condensates in a photonic crystal waveguide with hyperbolic (saddle-like) dispersion. Varying the dimer’s angle relative to the grating tunes the coupling from evanescent to ballistic. We directly observe spectral features and mass flow shaped by the saddle dispersion. This work highlights photonic crystals as powerful platforms to explore condensed matter phenomena lying at the interface between delay-coupled nonlinear oscillators and tight binding physics.

Georgakilas, Ioannis [IBM Research-Zurich, Rüschli↗
DOE OSTI2022

Connecting radio emission to AGN wind properties with broad absorption line quasars

ABSTRACT Broad absorption line quasars (BALQSOs) show strong signatures of powerful outflows, with the potential to alter the cosmic history of their host galaxies. These signatures are only seen in ∼10 per cent of optically selected quasars, although the fraction significantly increases in IR and radio selected samples. A proven physical explanation for this observed fraction has yet to be found, along with a determination of why this fraction increases at radio wavelengths. We present the largest sample of radio matched BALQSOs using the LOFAR Two-metre Sky Survey Data Release 2 and employ it to investigate radio properties of BALQSOs. Within the DR2 footprint, there are 3537 BALQSOs from Sloan Digital Sky Survey DR12 with continuum signal-to-noise ≥5. We find radio-detections for 1108 BALQSOs, with an important subpopulation of 120 LoBALs, an unprecedented sample size for radio matched BALQSOs given the sky coverage to date. BALQSOs are a radio-quiet population that show an increase of ×1.50 radio-detection fraction compared to non-BALQSOs. LoBALs show an increase of ×2.22 that of non-BALQSO quasars. We show that this detection fraction correlates with wind-strength, reddening, and C iv emission properties of BALQSOs and that these features may be connected, although no single property can fully explain the enhanced radio detection fraction. We create composite spectra for subclasses of BALQSOs based on wind strength and colour, finding differences in the absorption profiles of radio-detected and radio-undetected sources, particularly for LoBALs. Overall, we favour a wind-ISM interaction explanation for the increased radio-detection fraction of BALQSOs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

RNA Splicing Events in Circulation Distinguish Individuals With and Without New-onset Type 1 Diabetes

Context: Alterations in RNA splicing may influence protein isoform diversity that contributes to or reflects the pathophysiology of certain diseases. Whereas specific RNA splicing events in pancreatic islets have been investigated in models of inflammation in vitro, how RNA splicing in the circulation correlates with or is reflective of type 1 diabetes (T1D) disease pathophysiology in humans remains unexplored. Objective: To use machine learning to investigate if alternative RNA splicing events differ between individuals with and without new-onset T1D and to determine if these splicing events provide insight into T1D pathophysiology. Methods: RNA deep sequencing was performed on whole blood samples from 2 independent cohorts: a training cohort consisting of 12 individuals with new-onset T1D and 12 age- and sex-matched nondiabetic controls and a validation cohort of the same size and demographics. Machine learning analysis was used to identify specific isoforms that could distinguish individuals with T1D from controls. Results: Distinct patterns of RNA splicing differentiated participants with T1D from unaffected controls. Notably, certain splicing events, particularly involving retained introns, showed significant association with T1D. Machine learning analysis using these splicing events as features from the training cohort demonstrated high accuracy in distinguishing between T1D subjects and controls in the validation cohort. Gene Ontology pathway enrichment analysis of the retained intron category showed evidence for a systemic viral response in T1D subjects. Conclusion: Alternative RNA splicing events in whole blood are significantly enriched in individuals with new-onset T1D and can effectively distinguish these individuals from unaffected controls. Further, our findings also suggest that RNA splicing profiles offer the potential to provide insights into disease pathogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2024

Energetic Electrons Accelerated and Trapped in a Magnetic Bottle above a Solar Flare Arcade

Where and how flares efficiently accelerate charged particles remains an unresolved question. Recent studies revealed that a “magnetic bottle” structure, which forms near the bottom of a large-scale reconnection current sheet above the flare arcade, is an excellent candidate for confining and accelerating charged particles. However, further understanding its role requires linking the various observational signatures to the underlying coupled plasma and particle processes. Here we present the first study combining multiwavelength observations with data-informed macroscopic magnetohydrodynamics and particle modeling in a realistic eruptive flare geometry. The presence of an above-the-loop-top magnetic bottle structure is strongly supported by the observations, which feature not only a local minimum of magnetic field strength but also abruptly slowing plasma downflows. It also coincides with a compact above-the-loop-top hard X-ray source and an extended microwave source that bestrides the flare arcade. Spatially resolved spectral analysis suggests that nonthermal electrons are highly concentrated in this region. Our model returns synthetic emission signatures that are well matched to the observations. The results suggest that the energetic electrons are strongly trapped in the magnetic bottle region due to turbulence, with only a small fraction managing to escape. The electrons are primarily accelerated by plasma compression and facilitated by a fast-mode termination shock via the Fermi mechanism. Our results provide concrete support for the magnetic bottle as the primary electron acceleration site in eruptive solar flares. They also offer new insights into understanding the previously reported small population of flare-accelerated electrons entering interplanetary space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhancing Regional Seismic Velocity Models With Higher‐Resolution Local Results Using Sparse Dictionary Learning

Abstract We use sparse dictionary learning to develop transformations between seismic velocity models of different resolution and spatial extent. Starting with data in the common region of both models, the method can enhance a regional lower‐resolution model to match the style and resolution of local higher‐resolution results while preserving its regional coverage. The method is demonstrated by applying it to two‐dimensional V S and three‐dimensional V P and V S regional and local velocity models in southern California. The enhanced reconstructed regional results exhibit clear visual improvements, especially in the reconstructed V P / V S ratios, and better correlations with geological features. Moreover, the reconstructed regional V P , V S models outperform the original ones in comparison of simulated earthquake waveforms to observations. The improved fitting to observed waveforms extends beyond the domain of the overlapping region. The developed dictionary learning approach provides physically interpretable results and offers a powerful tool for additional applications of data enhancement in earth sciences.

Geochemistry & Geophysics↗
DOE OSTI2020

Hardware-in-the-loop Testing of Signal Temporal Logic Frequency Control in a Microgrid

This paper presents a hardware-in-the-loop (HITL) testing and lessons learned for a signal temporal logic (STL) frequency control in a microgrid setting. In contrast to most, if not all, traditional control mechanisms, the STL control allows for including temporal constraints in the control formulation to handle sophisticated specifications from grid codes and protection relays. This feature provides richer descriptions of control specifications to address both magnitude and time simultaneously, hence a valuable tool for power system operation and control. An ultra-low voltage (24V) HITL microgrid platform consisting of two type-3 wind turbine generators and one diesel generator is used to test the proposed STL frequency control. In experimental case studies, we demonstrate that the HITL frequency responses closely match the simulated ones and strictly satisfy the designed STL control specifications.

Ferrari Maglia, Max↗
DOE OSTI2024

Leveraging MARVEL and SPHERE to Demonstrate NEAMS Thermal Hydraulics Codes

The Single Primary Heat Extraction and Removal Emulator (SPHERE) and Microreactor Applications Research Validation and Evaluation (MARVEL) were utilized to demonstrate thermal hydraulics codes of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. A recent long-duration test of a sodium heat pipe conducted at the SPHERE facility was utilized for the validation of the heat pipe code Sockeye. The first 10 hours of operation featured a startup of the heat pipe from room temperature; this portion was modeled with Sockeye and compared to the experimental data. Measurements included several thermocouple measurements across the length of the heat pipe surface. Two of Sockeye’s heat pipe models were applied to experiment, as well as several models of the cooling at the condenser end of the heat pipe. Sockeye results gave a decent match to the experimental data, with notable discrepancy in the condenser section, where experimental data indicated a significant inactive length of the heat pipe. The MARVEL microreactor was modeled through a coupled simulation of System Analysis Module (SAM) and SubChannel Module (SCM). This multiscale coupled simulation was performed as an exercise to demonstrate the compatibility and applicability of these codes for thermal-hydraulic analysis of microreactors. The coupling between the SCM and SAM codes for multiscale modeling of MARVEL, was achieved through a domain overlapping approach. In this example a transient SAM simulation provided boundary conditions to SCM, and SCM provided pressure drop to SAM.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Pushing the Limits: Maximizing Energy Density in Silicon Sulfide Solid‐State Batteries

Here, for the first time, we demonstrate a silicon solid-state battery (SSB) architecture that achieves >400 Wh kg −1 , approaching the theoretical limit for silicon-based SSBs. This configuration features a 99.9 wt% micro-Si, a thin sulfide solid electrolyte (SSE), and a high-loading NMC811. Key to these results is strategically selecting and evaluating the processing techniques, whether wet or dry, for the negative electrode, positive electrode and thin sheet-type SSE. Excessive lithium incorporation into the silicon host, beyond the Li 3.75 +Si phase to form a LiSi composite, is essential to match the high capacity of the positive electrode. This SSB achieves over 1000 cycles for a 2 mAh cm −2 with ≈80% capacity retention and 94% capacity retention for 3 mAh cm −2 over 500 cycles at 25 °C. Post analysis identifies the primary capacity decay mechanisms as oxidation at the NMC/SSE interface and structural disruptions within NMC. Meanwhile, the Si electrode maintains a robust solid-electrolyte interphase layer, minimizing capacity decay. This study highlights the necessity for improved NMC coatings, lattice oxygen stabilization, and a durable positive electrode-electrolyte interface to improve the long-term stability of SSBs. Strategies leading to a single-layer pouch cell SSB exceeding 400 Wh kg −1 are developed.

25 ENERGY STORAGE↗
DOE OSTI2020

A simple vacuum suitcase for enabling plasma facing component characterization in fusion devices

We have demonstrated a vacuum suitcase to transport samples in vacuo to a surface analysis station for characterization of tokamak plasma facing components (PFCs). This technique enables surface analysis at powerful, dedicated stations that are not encumbered by design constraints imposed on them by a tokamak. The vacuum suitcase is an alternative solution to characterizing PFCs using diagnostics that are designed and built around a tokamak. The vacuum suitcase, called the Sample Exposure Probe (SEP), features mobile ultra-high vacuum pumping. Active pumping under high vacuum enables sample transfer between the Lithium Tokamak eXperiment-β (LTX-β) and a high resolution X-ray Photoelectron Spectroscopy (XPS) system that is situated close by. A thermocouple inserted in the back of the sample head measures heat flux from the plasma during exposure, and together with a button heater, allows the sample to match the LTX-β PFCs in high temperature operations. As vacuum conditions are better during transfer and analysis than in the tokamak, less contamination is introduced to the samples. XPS scans on a dedicated analysis station enable peak identification due to higher resolution and signal to noise ratio. A similar probe could be implemented for other fusion devices. As a result, the SEP is the first vacuum suitcase implementation for fusion applications that incorporates active pumping.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Downwind control of oceanic air by land: the land wake and its sensitivity to CO 2

Oceans are well-known to be directly altered by global climate forcings such as greenhouse gas changes, but how oceans are indirectly influenced by land and its response to such forcings remains less explored. Here, we assess the present-day and projected future state of a little-explored feature of the climate system—a 'land wake' in relative humidity downwind of the east coast of North America, consisting of low-humidity continental air extending roughly 1000 km over the Atlantic ocean. The wake exists throughout the year, but is supported by high continental temperatures in summer and low continental moisture in winter. The wake is well represented in an ensemble of global climate models (GCMs), qualitatively matching reanalysis data. Under increasing atmospheric CO 2 , the land wake intensifies in GCM simulations through two pathways: the radiative effects of CO 2 on surface temperatures, and the biogeochemical effect of CO 2 on terrestrial vegetation. Vegetation responses to increased CO 2 alter the summer wake from Florida to Newfoundland, and both the radiative and biogeochemical effects of CO 2 drive reductions in coastal cloud cover. These changes illustrate the potential of rapidly changing terrestrial climate to influence coastal regions and the ocean environment downwind of continents through both light conditions and the energy balance of the surface ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Hamiltonian Truncation Effective Theory

Hamiltonian truncation is a non-perturbative numerical method for calculating observables of a quantum field theory. The starting point for this method is to truncate the interacting Hamiltonian to a finite-dimensional space of states spanned by the eigenvectors of the free Hamiltonian H_0 H 0 with eigenvalues below some energy cutoff E_\text{max} E max . In this work, we show how to treat Hamiltonian truncation systematically using effective field theory methodology. We define the finite-dimensional effective Hamiltonian by integrating out the states above E_\text{max} E max . The effective Hamiltonian can be computed by matching a transition amplitude to the full theory, and gives corrections order by order as an expansion in powers of 1/E_\text{max} 1 / E max . The effective Hamiltonian is non-local, with the non-locality controlled in an expansion in powers of H_0/E_\text{max} H 0 / E max . The effective Hamiltonian is also non-Hermitian, and we discuss whether this is a necessary feature or an artifact of our definition. We apply our formalism to 2D \lambda\phi^4 λ ϕ 4 theory, and compute the the leading 1/E_\text{max}^2 1 / E max 2 corrections to the effective Hamiltonian. We show that these corrections nontrivially satisfy the crucial property of separation of scales. Numerical diagonalization of the effective Hamiltonian gives residual errors of order 1/E_\text{max}^3 1 / E max 3 , as expected by our power counting. We also present the power counting for 3D \lambda \phi^4 λ ϕ 4 theory and perform calculations that demonstrate the separation of scales in this theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) of zwitterionic organic HCl salts

In this work, we benchmark quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) for determining the crystal structures of two zwitterionic organic HCl salts, L-ornithine HCl ( Orn ) and L-histidine HCl·H 2 O ( Hist ). These salts present an interesting challenge for QNMRX-CSP, as gas-phase geometry optimizations used to generate starting structures for the organic zwitterionic fragments fail to capture their correct solid-state geometries. To overcome this limitation, geometry optimizations using the COSMO water-solvation model are employed to generate initial structural models. Using this approach, QNMRX-CSP yields structural models of the two zwitterionic organic HCl salts that closely match experimentally determined crystal structures. In addition, the application of QNMRX-CSP to Hist represents a further step toward the de novo structural determination of solvated organic HCl salts, as Hist is the first benchmark system of this type to include a water molecule as a component of its crystal structure. This work is significant for its potential application to the structural determination of active pharmaceutical ingredients, which often feature complex organic components and solvated solid forms.

Fleischer, Carl H. [Florida State Univ., Tallahass↗
DOE OSTI2021

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks

Microscopic images from multiple modalities can produce plentiful experimental information. In practice, biological or physical constraints under a given observation period may prevent researchers from acquiring enough microscopic scanning. Recent studies demonstrate that image synthesis is one of the popular approaches to release such constraints. Nonetheless, most existing synthesis approaches only translate images from the source domain to the target domain without solid geometric associations. To embrace this challenge, we propose an innovative model architecture, BANIS, to synthesize diversified microscopic images from multi-source domains with distinct geometric features. The experimental outcomes indicate that BANIS successfully synthesizes favorable image pairs on C. elegans microscopy embryonic images. To the best of our knowledge, BANIS is the first application to synthesize microscopic images that associate distinct spatial geometric features from multi-source domains.

Wang, Dali↗
DOE OSTI2025

Pathway Selectivity in 2D Electronic‐Vibrational Spectroscopy with Quantum Light

Abstract Pathway selectivity in quantum spectroscopy with entangled photons is a powerful spectroscopic tool. Phase‐matched signals involving classical light contain contributions from multiple material pathways, whereas quantum spectroscopy may allow the selection of individual pathways. 2D electronic‐vibrational spectroscopy (2DEVS) is a four‐wave mixing technique which employs visible and infrared entangled photons. It is showed how the three contributing pathways—ground state bleach, excited state absorption, and excited state emission—can be separated by photon‐number‐resolved coincidence measurements. Entangled photons thus reveal spectral features not visible in the classical signal, with an enhanced spectral resolution.

Jadoun, Deependra [Department of Chemistry Univers↗
DOE OSTI2025

Emulation of quantum correlations by classical dynamics in a spin-$\frac{1}{2}$ Heisenberg chain

We simulate the dynamical spin structure factor (DSSF) 𝒮⁡(𝑞,𝜔) of the spin-1/2 Heisenberg antiferromagnetic chain using classical simulations. By employing Landau-Lifshitz Dynamics, we emulate quantum correlations through temperature-dependent corrections, including rescaling of magnetic dipoles and renormalization of exchange interactions. Here, our results closely match Quantum Monte-Carlo calculations for 𝑘 B⁢ 𝑇/𝐽≳1, extending the applicability of classical dynamics to the challenging case of gapless excitations. At higher temperatures, our simulations comply with general predictions for uncorrelated paramagnetic fluctuations in the infinite temperature limit. Entanglement witnesses derived from the quantum-equivalent DSSF act as sensitive diagnostics for the quantum-to-classical crossover. Their reliability stems from their dependence on spectral features alone, enabling classical dynamics to emulate quantum thresholds without genuine entanglement. This framework also reproduces transverse spin correlations in finite magnetic fields, in agreement with quantum simulations. Together, our results establish quantum-corrected classical dynamics as a scalable and predictive tool for interpreting scattering experiments and exploring quantum correlations in strongly correlated spin systems.

Inelastic neutron scattering↗