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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

An expanded registry of candidate cis -regulatory elements

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, the ENCODE consortium mapped biochemical signals across hundreds of cell types and tissues and integrated these data to develop a registry containing 0.9 million human and 300,000 mouse candidate cis-regulatory elements (cCREs) annotated with potential functions. Here we have expanded the registry to include 2.37 million human and 967,000 mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays such as STARR-seq, massively parallel reporter assay, CRISPR perturbation and transgenic mouse assays have profiled more than 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer and silencer roles in different cellular contexts. Integrating the registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by the identification of KLF1 as a novel causal gene for red blood cell traits. This expanded registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

Moore, Jill E. [Univ. of Massachusetts, Worchester↗
DOE OSTI2023

Scaling comb-driven resonator-based DWDM silicon photonic links to multi-Tb/s in the multi-FSR regime

The use of chip-based micro-resonator Kerr frequency combs in conjunction with dense wavelength-division multiplexing (DWDM) enables massively parallel intensity-modulated direct-detection data transmission with low energy consumption. Resonator-based modulators and filters used in such systems can limit the number of usable wavelength channels due to practical constraints on the maximum achievable free spectral range (FSR). In this work, we introduce the design of multi-Tb/s comb-driven resonator-based silicon photonic links by leveraging the multi-FSR regime. We demonstrate the viability of the link architecture with yield estimates that are supported by extensive wafer-scale measurements of 704 micro-resonators fabricated in a commercial complementary metal–oxide–semiconductor foundry. We show that a 2.80 Tb/s link is realizable with a ≥6 σ yield (∼99.999%), and that aggregate bandwidths of 3.76 Tb/s and 4.72 Tb/s are possible if yield targets are relaxed (3 σ and 1 σ , respectively). All designs represent a 1.94−3.28× boost to aggregate link bandwidth while maintaining BER≤10 −10 performance, with a theoretical bandwidth of 10.51 Tb/s being possible for sufficiently robust resonators. We use high-speed BER measurements to inform co-optimization of data rate and aggressor spacing ( λ ag ), limiting any additional loss-based power penalties to off-resonance insertion loss (IL) and routing loss. This work demonstrates that, through the multi-FSR regime, there is a clear path toward Kerr comb-driven ultra-broadband, high bandwidth silicon photonic links that can support next-generation data centers and high-performance computers.

James, Aneek (ORCID:0000000262527807)↗
DOE OSTI2022

Finding Electronic Structure Machine Learning Surrogates without Training

A myriad of phenomena in materials science and chemistry rely on quantum-level simulations of the electronic structure in matter. While moving to larger length and time scales has been a pressing issue for decades, such large-scale electronic structure calculations are still challenging despite modern software approaches and advances in high-performance computing. The silver lining in this regard is the use of machine learning to accelerate electronic structure calculations – this line of research has recently gained growing attention. The grand challenge therein is finding a suitable machine-learning model during a process called hyperparameter optimization. This, however, causes a massive computational overhead in addition to that of data generation. We accelerate the construction of machine-learning surrogate models by roughly two orders of magnitude by circumventing excessive training during the hyperparameter optimization phase. We demonstrate our workflow for Kohn-Sham density functional theory, the most popular computational method in materials science and chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Swing of the Pendulum: The Chemodynamics of the Local Stellar Halo Indicate Contributions from Several Radial Merger Events

We find that the chemical abundances and dynamics of APOGEE and GALAH stars in the local stellar halo are inconsistent with a scenario in which the inner halo is primarily composed of debris from a single massive, ancient merger event, as has been proposed to explain the Gaia-Enceladus/Gaia Sausage (GSE) structure. The data contain trends of chemical composition with energy that are opposite to expectations for a single massive, ancient merger event, and multiple chemical evolution paths with distinct dynamics are present. We use a Bayesian Gaussian mixture model regression algorithm to characterize the local stellar halo, and find that the data are fit best by a model with four components. We interpret these components as the Virgo Radial Merger (VRM), Cronus, Nereus, and Thamnos; however, Nereus and Thamnos likely represent more than one accretion event because the chemical abundance distributions of their member stars contain many peaks. Although the Cronus and Thamnos components have different dynamics, their chemical abundances suggest they may be related. We show that the distinct low- and high-α halo populations from Nissen & Schuster are explained by VRM and Cronus stars, as well as some in situ stars. Because the local stellar halo contains multiple substructures, different popular methods of selecting GSE stars will actually select different mixtures of these substructures, which may change the apparent chemodynamic properties of the selected stars. We also find that the Splash stars in the Solar region are shifted to higher v $\phi$ and slightly lower [Fe/H] than previously reported.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The satellite population around luminous red galaxies in the 25 deg2 DESI Legacy Imaging Surveys Early Data Release

ABSTRACT Luminous red galaxies, or LRGs, are representative of the most massive galaxies and were originally selected in the Sloan Digital Sky Survey as good tracers of large-scale structure. They are dominated by by uniformly old stellar populations, have low star formation rates, early type morphologies, and little cold gas. Despite having old stellar populations and little in situ star formation, studies have shown that they have grown their stellar mass since z = 1, implying that they grow predominantly via the accretion of satellites. Tests of this picture have been limited because of the lack of deep imaging data sets that both covers a large enough area of the sky to contain substantial numbers of LRGs and that also is deep enough to detect faint satellites. We use the 25 deg2 Early Data Release (EDR) of the DESI Legacy Imaging Surveys to characterize the satellite galaxy population of LRGs out to z = 0.65. The DESI Legacy Imaging Surveys are comprised of grz imaging to 2–2.5 mag deeper than SDSS and with better image quality. We use a new statistical background technique to identify excess populations of putative satellite galaxies around 1823 LRGs at 0.2 < z < 0.65. In three redshift and luminosity bins we measure the numbers of satellite galaxies and their r−z colour distribution down to rest-frame g-band luminosity limits at least 3.6 times fainter than L*. In addition, we develop a forward modeling technique and apply it to constrain the mean number of satellites in each of our redshift and luminosity bins. Finally, we use these estimates to determine the amount of stellar mass growth in LRGs down to the local Universe.

Astronomy & Astrophysics↗
DOE OSTI2025

Tracing the Cosmic Evolution of the Cool Circumgalactic Medium of Luminous Red Galaxies with DESI Year 1 Data

We investigate the properties of the cool circumgalactic medium (CGM) of massive galaxies and their cosmic evolution. By using the year 1 dataset of luminous red galaxies (LRGs) and QSOs from the Dark Energy Spectroscopic Instrument survey, we construct a sample of approximately 600,000 galaxy-quasar pairs and measure the radial distribution and kinematics of the cool gas traced by Mg II absorption lines as a function of galaxy properties from redshift 0.4 to redshift 1.2. Our results show that the covering fraction of the cool gas around LRGs increases with redshift, following a trend similar to the global evolution of galaxy star formation rate. At small radii (< 0.3rvir), the covering fraction anti-correlates with stellar mass, suggesting that mass-dependent processes suppress the cool gas content in the inner region. In addition, we measure the gas dispersion by modeling the velocity distribution of absorbers with a narrow and a broad components -- sigma_n ~ 160 and sigma_b ~ 380 km/s -- and quantify their relative contributions. The results show that the broad component becomes more prominent in the outer region, and its relative importance in the central region grows with increasing stellar mass. Finally, we discuss possible origins of the cool gas around massive galaxies, including the contribution of satellite galaxies and the precipitation scenario.

Chang, Yu-Ling [Taiwan, Natl. Taiwan U.] (ORCID:00↗
DOE OSTI2020

New constraints on heavy neutral leptons from Super-Kamiokande data

Abstract Heavy neutral leptons are predicted in many extensions of the Standard Model with massive neutrinos. If kinematically accessible, they can be copiously produced from kaon and pion decays in atmospheric showers, and subsequently decay inside large neutrino detectors. We perform a search for these long-lived particles using Super-Kamiokande multi-GeV neutrino data and derive stringent limits on the mixing with electron, muon and tau neutrinos as a function of the long-lived particle mass. We also present the limits on the branching ratio versus lifetime plane, which are helpful in determining the constraints in non-minimal models where the heavy neutral leptons have new interactions with the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Massive Early-type Galaxies in the HSC-SSP: Flux Fraction of Tidal Features and Merger Rates

Here we present a statistical study on tidal features around massive early-type galaxies (ETGs). Utilizing the imaging data of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), we measure the flux fraction of tidal features (f tidal ) in 2649 ETGs with stellar mass M * > 10 11 M ⊙ and redshift 0.05 < z < 0.15 using automated techniques. The Wide layer of HSC-SSP reaches a depth of ~28.5 mag arcsec –2 in the i band. Under this surface brightness limit, we find that about 28% of these galaxies harbor prominent tidal features with f tidal > 1%, among which the number of ETGs decreases exponentially with f tidal , with a logarithmic slope of ~100. Within the stellar mass range we probe, we note that f tidal increases by a factor of 2 from M * ≈ 10 11 to 10 12 M ⊙ . We also perform a pair count to estimate the merger rate of these massive ETGs. Combining the merger rates with f tidal , we estimate that the typical lifetime of tidal features is ~3 Gyr, consistent with previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Novel strategies for modal-based structural material identification

Here, we present modal-based methods for model calibration in structural dynamics, and address several key challenges in the solution of gradient-based optimization problems with eigenvalues and eigenvectors, including the solution of singular Helmholtz problems encountered in sensitivity calculations, non-differentiable objective functions caused by mode swapping during optimization, and cases with repeated eigenvalues. Unlike previous literature that relied on direct solution of the eigenvector adjoint equations, we present a parallel iterative domain decomposition strategy (Adjoint Computation via Modal Superposition with Truncation Augmentation) for the solution of the singular Helmholtz problems. For problems with repeated eigenvalues we present a novel Mode Separation via Projection algorithm, and in order to address mode swapping between inverse iterations we present a novel Injective mode ordering metric. We present the implementation of these methods in a massively parallel finite element framework with the ability to use measured modal data to extract unknown structural model parameters from large complex problems. A series of increasingly complex numerical examples are presented that demonstrate the implementation and performance of the methods in a massively parallel finite element framework [7], [5], using gradient-based optimization techniques in the Rapid Optimization Library (ROL) [21].

36 MATERIALS SCIENCE↗
DOE OSTI2020

CMB distance priors revisited: effects of dark energy dynamics, spatial curvature, primordial power spectrum, and neutrino parameters

As a physical and sufficient compression of the full CMB data, the CMB distance priors, or shift parameters, have been widely used and provide a convenient way to include CMB data when obtaining cosmological constraints. In this paper, we revisit this data vector and examine its stability under different cosmological models. We find that the CMB distance priors are an accurate substitute for the full CMB data when probing dark energy dynamics. This is true when the primordial power spectrum model is directly generalized from the power spectrum of the model used in the derivation of the distance priors from the CMB data. We discover a difference when a non-flat model with the untilted primordial inflation power spectrum is used to measure the distance priors. This power spectrum is a radical change from the more conventional tilted primordial power spectrum and violates fundamental assumptions for the reliability of the CMB shift parameters. We also investigate the performance of CMB distance priors when the sum of neutrino masses Σm ν and the effective number of relativistic species N eff are allowed to vary. Our findings are consistent with earlier results: the neutrino parameters can change the measurement of the sound horizon from CMB data, and thus the CMB distance priors. We find that when the neutrino model is allowed to vary, the cold dark matter density ω c and N eff need to be included in the set of parameters that summarize CMB data, in order to reproduce the constraints from the full CMB data. As a result, we present an updated and expanded set of CMB distance priors which can reproduce constraints from the full CMB data within 1σ, and are applicable to models with massive neutrinos, as well as non-standard cosmologies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Does the Z boson have a lighter cousin?

In the quenched electroweak theory on the lattice I construct a set of physical states which overlap the physical photon and Z boson states. This is done by employing eigenstates of the covariant lattice Laplacian, in addition to the Higgs and lattice link variables, to construct gauge invariant vector boson creation operators. Diagonalizing the transfer matrix in the subspace of Hilbert space spanned by this set yields a massless photon and massive Z particle, as expected. But in the numerical data there is evidence for more vector bosons in the spectrum, albeit with considerable uncertainty in their masses, with the lowest finite mass particle in the range of 3–4 GeV. Published by the American Physical Society 2025

Greensite, Jeff (ORCID:0000000317209436)↗
DOE OSTI2024

A JWST Survey of the Supernova Remnant Cassiopeia A

We present initial results from a James Webb Space Telescope (JWST) survey of the youngest Galactic core-collapse supernova remnant, Cassiopeia A (Cas A), made up of NIRCam and MIRI imaging mosaics that map emission from the main shell, interior, and surrounding circumstellar/interstellar material (CSM/ISM). We also present four exploratory positions of MIRI Medium Resolution Spectrograph integral field unit spectroscopy that sample ejecta, CSM, and associated dust from representative shocked and unshocked regions. Surprising discoveries include (1) a weblike network of unshocked ejecta filaments resolved to ~0.01 pc scales exhibiting an overall morphology consistent with turbulent mixing of cool, low-entropy matter from the progenitor's oxygen layer with hot, high-entropy matter heated by neutrino interactions and radioactivity; (2) a thick sheet of dust-dominated emission from shocked CSM seen in projection toward the remnant's interior pockmarked with small (~1'') round holes formed by ≲0$^"_•$1 knots of high-velocity ejecta that have pierced through the CSM and driven expanding tangential shocks; and (3) dozens of light echoes with angular sizes between ~0$^"_•$1 and 1' reflecting previously unseen fine-scale structure in the ISM. NIRCam observations place new upper limits on infrared emission (≲20 nJy at 3 μm) from the neutron star in Cas A's center and tightly constrain scenarios involving a possible fallback disk. These JWST survey data and initial findings help address unresolved questions about massive star explosions that have broad implications for the formation and evolution of stellar populations, the metal and dust enrichment of galaxies, and the origin of compact remnant objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Data-Driven Framework for Power System Event Type Identification via Safe Semi-Supervised Techniques

Herein this paper investigates the use of phasor measurement unit (PMU) data with deep learning techniques to construct real-time event identification models for transmission networks. Increasing penetration of distributed energy resources represents a great opportunity to achieve decarbonization, as well as challenges in systematic situational awareness. When high-resolution PMU data and sufficient manually recorded event labels are available, the power event identification problem is defined as a statistical classification problem that can be solved by numerous cutting-edge classifiers. However, in real grids, collecting tremendous high-quality event labels is quite expensive. Utilities frequently have a large number of event records without in-depth details (i.e., unlabeled events). To bridge this gap, we propose a novel semi-supervised learning-based method to improve the performance of event classifiers trained with a limited number of labeled events by exploiting the information from massive unlabeled events. In other words, compared to existing data-driven methods, our method requires only a small portion of labeled data to achieve a similar level of accuracy. Meanwhile, this work discusses and addresses the performance degradation caused by class distribution mismatch between the training set and the real applications. Based on the proposed safe learning mechanism, our model does not directly use all unlabeled events during model training, but selectively uses them through a comprehensive evaluation procedure. Numerical studies on a sizable PMU dataset have been used to validate the performance of the proposed method.

42 ENGINEERING↗
DOE OSTI2025

Elucidating texture and grain morphology contributions to the micromechanical response of additively manufactured Inconel 625

Microstructural variation of additively manufactured (AM) metal components in comparison to wrought counterparts makes certification for critical applications a challenge. Microscale simulations leveraging modern computational tools may be used to supplement testing of AM microstructures, thus accelerating certification by reducing the number of experiments needed. However, as micromechanical response is closely tied to critical properties like fatigue-life and fracture, utilization of these simulations with macroscale experimental data alone is insufficient. One means to attain microscale experimental data is in situ diffraction data collected from synchrotron X-ray sources. In this work, such data were collected during in situ compression of AM Inconel 625 superalloy. Interpretation of experimental results was assisted by massive (8M element) complementary micromechanical simulations performed on sets of virtual microstructures generated using cellular automata. Together, micromechanical data from diffraction experiments and simulations were used to probe the effects of textured “track” microstructures generated during laser powder bed fusion and directional strength-to-stiffness on micromechanical response. Though fiber-averaged directional strength-to-stiffness ratios were expected to dominate given the high elastic anisotropy of the material, the combination of small variations in texture and specific grain configurations unique to AM microstructures lead to significant variability in micromechanical response after yield. The findings emphasize the importance of high-fidelity microstructural representation that captures key texture components and AM-specific morphology for property prediction of AM metals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CommAwareNet: Towards Communication‐Aware Smart Facilities: Designing an Energy‐Efficient High‐Data‐Rate and Reliable Hybrid THz/VLC Comm. Arch. Reinforced with Intelligent Surfaces for Future Network

This project will develop foundations for energy-efficient, high-data-rate, and reliable communication links for next-generation advanced wireless technologies. The Internet of Everything is emerging as a major technology that can establish a massively connected network among both human-type users and machine-type devices. Particularly, massive machine-type communication is becoming the dominant communication paradigm for numerous emerging areas, including data center networking and wireless backhaul, healthcare (e-health), manufacturing (industry 4.0), utilities, transportation (connected cars and public safety), and virtual or augmented reality for human-machine interaction applications. The rising demand for high data rates, especially in indoor scenarios and densely populated outdoor environments, will eventually overload conventional RF-based technologies. This project aims to conduct fundamental research to design, optimize, and validate a communication-aware, energy-efficient, and reliable network (CommAwareNet) architecture for future smart facilities and environments that require unprecedented high throughput needs for massive numbers of the machine- and human-type users. The scientific and technical merit of this work lies in the research required to bring the proposed transformative CommAwareNet solution into fully functional and practical architecture.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Phoenix: A Scalable Streaming Hypergraph Analysis Framework

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.

Kurte, Kuldeep↗
DOE OSTI2021

Detecting topological phase transitions in cadmium arsenide films via the transverse magnetoresistance

Topological protection against localization causes electrical transport phenomena in disordered topological materials to differ from those in topologically trivial systems. For example, a transition between a regime of weak localization to one of weak antilocalization can occur in systems such as topological insulators and topological semimetals when an external potential is applied across the system. Here, we report on the transverse magnetoresistance of thin films of cadmium arsenide, a topological non-trivial material, as we tune the electronic states and the Fermi level. We show that the appearance of weak localization and weak antilocalization sensitively reflects the relative contributions of multiple transport channels involving both gapless (massless) and gapped (massive) Dirac fermion states present in these films. Furthermore, the data is consistent with expectations of the different topological states of these films. Weak (anti-) localization phenomena can therefore serve as a probe of the types of Dirac fermions present in topological semimetals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗