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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Arctic sea-ice loss drives a strong regional atmospheric response over the North Pacific and North Atlantic on decadal scales

Previous studies have suggested that Arctic sea-ice loss can have a profound influence on atmospheric circulation far away from the Arctic. However, there is little scientific consensus on the features of these remote responses, with the opposite impacts reported. Here we present a multi-model analysis of the decadal climate response to Arctic sea-ice loss using state-of-the-art energy conserving methodologies to isolate the impacts of sea-ice decline. We observe weakening of the Aleutian Low and development of a geopotential ridge in the North Pacific, associated with drier winter conditions over the southwest United States. Over the Atlantic, a negative NAO-like response drives wetter winter conditions across the western Mediterranean. These decadal-scale impacts substantially differ from reported centennial-scale responses to Arctic sea-ice loss simulated using non-energy conserving methodologies. Factors such as the timescale of the response and methodologies used to isolate the impacts of disappearing sea-ice cover should be carefully considered when consolidating scientific understanding on the future impacts of changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Effects of chemical composition and physicochemical properties of poplar biomass on the performance of 3D printed poplar-reinforced PLA materials

Lignocellulosic biomass has been well-acknowledged as a filler for making 3D printed composites. The technical performances of composites were influenced by the characteristics of the components. The correlations between poplar biomass properties and the mechanical and thermal performances of the 3D printed poplar-plastic composites were investigated. The characteristics of poplar were modified by different pretreatment methods, including using hot water, dilute acid, and organic solvent (organosolv), and each treated poplar biomass was applied as a filler in a polylactic acid (PLA) polymer matrix to produce eco-friendly materials. These solvent pretreatments increased the hydrophobicity and surface area of poplar. Organosolv treated poplar showed the highest cellulose content and significantly increased Young's modulus of its biocomposites. Principal component analysis revealed that the specific surface area and water contact angle of biomass contributed to the thermal stability of biocomposites. Additionally, the degree of polymerization of cellulose and xylan content within the biomass correlated with the biocomposites' break stress. Notably, the crystallinity of biocomposites impacted the modulus of these materials. The reported relationships between biomass characteristics and 3D printed composite behaviors provide guidance for optimizing biomass processing in biocomposite applications.

Ji, Anqi [State Univ. of New York (SUNY), Syracuse↗
DOE OSTI2025

GA-NIFS and EIGER: A merging quasar host at z = 7 with an overmassive black hole

The James Webb Space Telescope is revolutionising our ability to understand the host galaxies and local environments of high-z quasars. Here we obtain a comprehensive understanding of the host galaxy of the z = 7.08 quasar J1120+0641 by combining NIRSpec integral field spectroscopy with NIRCam photometry of the host continuum emission. Our emission-line maps reveal that this quasar host is undergoing a merger with a bright companion galaxy. The quasar host and the companion have similar dynamical masses of ∼10 10 M ⊙ , suggesting that this is a major galaxy interaction. Through detailed quasar subtraction and SED fitting using the NIRCam data, we obtained an estimate of the host stellar mass of M ∗ = (3.0 −1.4 +2.5 ) × 10 9 M ⊙ , with M ∗ = (2.7 −0.5 +0.5 ) × 10 9 M ⊙ for the companion galaxy. Using the Hβ Balmer line, we estimated a virial black hole mass of M BH = (1.9 −1.1 +2.9 ) × 109 M ⊙ . Thus, J1120+0641 has an extreme black hole–stellar mass ratio of M BH /M ∗ = 0.63 −0.31 +0.54 , which is ∼3 dex larger than expected by the local scaling relations between black hole and stellar mass. J1120+0641 is powered by an overmassive black hole with the highest reported black hole–stellar mass ratio in a quasar host that is currently undergoing a major merger. These new insights highlight the power of JWST for measuring and understanding these extreme first quasars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

JWST’s PEARLS: A z ≃ 6 quasar in a train-wreck galaxy merger system

We present JWST NIRSpec integral field spectroscopy observations of the z = 5.89 quasar NDWFS J1425+3254 from 0.6–5.3 μm, covering the rest-frame ultraviolet and optical at a spectral resolution of R ∼ 100. The quasar has a black hole mass of M BH = (1.4 +3.1 −1.0 ) × 10 9 M ⊙ and an Eddington ratio of L Bol /L Edd = 0.3 +0.6 −0.2 , as implied from the broad Balmer Hα and Hβ lines. The quasar host has significant ongoing obscured star formation, as well as a quasar-driven outflow with velocity 6050 +460 −630 km s −1 and ionised outflow rate of 1650 +130 −1230 M ⊙ yr −1 . This is possibly one of the most extreme outflows in the early Universe. The data also reveal that two companion galaxies are merging with the quasar host. The north-eastern companion galaxy is relatively old and very massive, with a luminosity-weighted stellar age of 65 +9 −4 Myr, stellar mass of (3.6 +0.6 −0.3 #x00D7; 10 11 M ⊙ , and star-formation rate (SFR) of ∼15–30 M ⊙ yr −1 . A bridge of gas connects this companion galaxy and the host, confirming their ongoing interaction. A second merger is occurring between the quasar host and a much younger companion galaxy to the south, with a stellar age of 6.7 ± 1.8 Myr, stellar mass of (1.9 ± 0.4)×10 10 M ⊙ , and SFR of ∼40–65 M ⊙ yr −1 . There is also another galaxy in the field, likely in the foreground at z = 1.135, which could be gravitationally lensing the quasar with a magnification of 1 < μ < 2 and, thus, < 0.75 mag. Overall, the system is a ‘train-wreck’ merger of three galaxies, with star formation and extreme quasar activity that were likely triggered by these ongoing interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

The stellar origins of 96 Zr excesses in presolar graphites from the Murchison meteorite

Context. Zirconium-96 is a stable isotope that can be synthesized under different neutron-rich nucleosynthetic conditions. Astrophysical models predict its production to occur in various stellar environments: from low-to-intermediate-mass asymptotic giant branch (AGB) stars to massive stars and core-collapse supernovae. Aims. Detections of 96Zr excesses, in combination with other isotopic measurements from presolar grains can provide unique constraints on its stellar origin. Presolar grains are microscopic particles found in primitive Solar System materials, which formed in stellar winds and supernova ejecta. The isotopic composition of each grain can provide us a snapshot of the nucleosynthetic processes that took place during the parent star’s lifetime. Methods. In this study, we measured the stable isotopes of C, N, O, Mo, Zr, and Ru in high-density presolar graphite grains from the Murchison meteorite and found four grains that contain positive isotopic anomalies in 96 Zr carried by their internal subgrains. We analyzed multi-element isotopic datasets from each grain to explore the source of the observed 96 Zr excesses. Results. Comparisons with stellar models indicate that two grains likely condensed in an intermediate-mass AGB star with initial metallicity of Z ≤ 0.014. Their 96 Zr/ 94 Zr ratios also match those predicted for born-again AGB stars undergoing a very late thermal pulse and rapidly accreting white dwarfs. After comparing the relative populations of the aforementioned dust-producing stars, we propose rapidly accreting white dwarfs as a new, and more likely, stellar source for one of the presolar grains. The remaining two grains could have originated in the supernova ejecta of massive stars, due to correlated excesses in the p-nuclides, 92, 94 Mo. Thus, grains with 96 Zr anomalies can have a variety of stellar origins, in agreement with theoretical studies. Conclusions. Our study highlights the importance of multi-element analysis in constraining the types of stars where presolar grains have condensed. These data will help improve our understanding of various nucleosynthesis processes in different stellar phases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Density drop at the divertor target in the prototype material plasma exposure eXperiment (Proto-MPEX)

The steady-state linear device “Material Plasma Exposure eXperiment” (MPEX) is currently under construction at Oak Ridge National Laboratory with the goal of enabling Plasma-Material Interaction studies at future fusion reactor relevant plasma conditions. In this work, a newly in-house developed hybrid Particle-In-Cell code-PICOS++ is applied to understand the experimental results obtained from the prototype of MPEX referred to as the “Proto-MPEX” during its helicon-only and helicon with ion cyclotron resonance heating (ICRH) experiments. This study explains the physics of the experimentally observed plasma density-drop at the divertor target in Proto-MPEX device during ICRH. In contrast to previous work on ICRH in MPEX, this study demonstrates that the mirror force plays a central role in the Proto-MPEX plasma transport during ICRH, which has new features not previously explored. Force balance analyses reveal that the temperature anisotropy produced by ICRH leads to a significant increase in the mirror force downstream of the resonance where the magnetic field is diverging. This force accelerates ions toward the target and leads to a drop in plasma density to ensure conservation of particle flux. Simulations with ICRH where the magnetic field divergence downstream of the resonance has been removed, do not produce plasma acceleration nor density drop at the target despite efficient ion heating at the resonance. Moreover, simulation results demonstrate that for a given ICRH power, lowering the source rate produces ions with increased perpendicular energy which interact with the mirror force to produce higher plasma acceleration which increases the strength of the density-drop at the target. The strength of the density drop appears to reach an asymptotic limit at a certain threshold ICRH power. Simulations show that this threshold power increases with increasing particle source rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Detecting the full photoemission cone from laser-based ARPES experiments by leveraging deflector technology

Angle-resolved photoemission spectroscopy (ARPES) provides a direct access to the electronic band structure of solid and molecular systems. The momentum range accessible by this technique depends directly on the photon energy used, and low-photon-energy sources are insufficient to photoemit electrons over the full Brillouin zone of most quantum materials. In addition, while electrons are emitted over a 2π solid angle, conventional hemispherical analyzers only collect a small subset of those electrons. A previous work [Gauthier et al., Rev. Sci. Instrum. 92, 123907 (2021)] demonstrated that electrons emitted over a larger field-of-view can be acquired in one fixed configuration by accelerating them toward the analyzer with a bias voltage. Here, in this study, we extend this work by leveraging the deflector technology of novel ARPES hemispherical analyzers. We demonstrate the ability to detect all 2π photoemitted electrons in a fixed configuration for various materials, such as gold, cuprates, and transition-metal dichalcogenides. This approach is especially advantageous for time-resolved ARPES, as electron dynamics over a large momentum range can be accessed with identical measurement conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Overestimated natural biological nitrogen fixation translates to an exaggerated CO 2 fertilization effect in Earth system models

CO 2 fertilization of the terrestrial biosphere is limited by nitrogen. Biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation but is poorly constrained in Earth system models (ESMs). Here, in this study, we compare terrestrial BNF from an ensemble of ESMs of the 6th Coupled Model Intercomparison Project to a new global synthesis of observations across natural and agricultural biomes. We find that compared to observations, ESMs underestimate agricultural BNF but overestimate natural BNF in the present day by over 50%. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). ESMs with different BNF representations yield a range of BNF responses to CO 2 enrichment. Some ESMs with phenomenological representations of BNF predict a natural BNF increase in response to a doubling of CO 2 that aligns with a meta-analysis of CO 2 enrichment experiments (31% increase) but fail to account for the substantial carbon cost of BNF. In contrast, ESMs with mechanistic representations of BNF account for its carbon cost as well as its regulation by nitrogen limitation but overestimate the BNF response to a doubling of CO 2 (135% increase). Overall, all current BNF representations in ESMs fall short of fully capturing its response to rising atmospheric CO 2 . Finally, we find a positive correlation between modeled present-day natural BNF and the CO 2 fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO 2 fertilization effect of approximately 11% in ESMs.

Biological nitrogen fixation↗
DOE OSTI2025

Elephant range and population, strontium isotopes, and genetics combine to give local-scale specificity to ivory hotspot tracking

We use Sr isotopes to increase the precision of DNA-based origin estimates of wildlife products. Population information is used to develop Sr isotope Elephant Polygons that are overlaid onto the region of origin identified by DNA assignment to determine the sources of seized ivory samples. Our approach is cognizant of isotope mixing due to isotope turnover within animals and also of the large home range of elephants or other mobile species. Genetic information from 3 different law enforcement ivory seizures suggests a region of origin confined to Kenya and Tanzania in eastern Africa. We determine characteristic 87 Sr/ 86 Sr ratios for each of 25 different Elephant Polygons within this region using analyses of more the 600 known-origin reference samples. Using both the 87 Sr/ 86 Sr ratios of the seized ivory samples and elephant population estimates from individual Elephant Polygons we find that at least 75 % of the samples likely came from a single Elephant Polygon which includes the Tsavo National Parks in Kenya and the Mkomazi National Park in Tanzania. A few samples may have come from other regions, most likely from Tanzania. This study illustrates the value of combining genetics, isotope geochemistry, and population surveys in wildlife forensics studies.

Africa↗
DOE OSTI2025

High-field side scrape-off layer density profile measurements and implications for high-field side LHCD coupling in DIII-D

The high-field side (HFS) scrape-off layer (SOL) is an often under-diagnosed region of tokamak plasmas. Situated in a region with favorable curvature, the HFS SOL has minimal turbulence-induced radial transport compared to the low-field side. Using profile reflectometry, the HFS SOL density profile is measured with high temporal resolution for a wide range of DIII-D plasma discharges for the first time. The magnetic configuration, particularly the location of the secondary separatrix (SS) largely determines the HFS SOL density profile. Additionally, density perturbations induced by edge-localized modes (ELMs) are observed in the HFS SOL, and the impact of ELMs on the SOL density profile is characterized for a range of magnetic configurations. It is found that ELM-induced HFS SOL perturbations are generally localized to within the SS and ELM-induced changes to the HFS wall density are minimized in near double-null configurations. The characterization of the HFS SOL density profile on DIII-D is crucial for the effective coupling of the planned HFS lower hybrid current drive (LHCD) launcher. Experimental HFS SOL measurements are used as input to full-wave simulations of LHCD coupling. Furthermore, this work simulates the effect of the magnetic configuration on LHCD coupling. It also simulates LHCD coupling in ELMs and high q min discharges. During such discharges, the LHCD coupling is predicted to be resilient to ELM-induced SOL density perturbations.

high-field side↗
DOE OSTI2025

Loosely bound composite dark matter

We investigate loosely bound composite states made of dark matter, where the binding energy for constituent particles is considerably less than the constituent mass. We focus on models of nuclear and molecular dark matter, where constituents are separated by length scales larger than the inverse constituent mass, just like nuclei and atoms in the Standard Model. The cosmology, structure, and interactions at underground experiments are described. We find that loosely bound composites can have a very large cross section for scattering with nuclei that scales with nucleon number like ∼ A 4 . For some couplings, these composites produce extremely soft (≪ keV) individual atomic recoils while depositing a large amount of total recoil energy (≫ keV) in a single passage through a detector, implying an interesting new class of signatures for low threshold direct detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Deep inference of simulated strong lenses in ground-based surveys

The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dark matter. However, leveraging the increased statistical power of such large samples will require further development of automated lens modeling techniques. We show that deep learning and simulation-based inference (SBI) methods produce informative and reliable estimates of parameter posteriors for strong lensing systems in ground-based surveys. We present the examination and comparison of two approaches to lens parameter estimation for strong galaxy-galaxy lenses — Neural Posterior Estimation (NPE) and Bayesian Neural Networks (BNNs). We perform inference on 1-, 5-, and 12-parameter lens models for ground-based imaging data that mimics the Dark Energy Survey (DES). We find that NPE outperforms BNNs, producing posterior distributions that are more accurate, precise, and well-calibrated for most parameters. For the 12-parameter NPE model, the calibration is consistently within <10% of optimal calibration for all parameters, while the BNN is rarely within 20% of optimal calibration for any of the parameters. Similarly, residuals for most of the parameters are smaller (by up to an order of magnitude) with the NPE model than the BNN model. This work takes important steps in the systematic comparison of methods for different levels of model complexity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Silicon pinhole strip defects and their impact on ATLAS Inner Tracker HV current measurement

In preparation for the High-Luminsity LHC (HL-LHC) [1], the ATLAS detector will undergo major detector upgrades, including the replacement of the current Inner Detector with the new all-silicon Inner Tracker (ITk) [2]. The ITk consists of a pixel detector close to the beamline surrounded by a large-area strip detector. During detector production, the electrical properties of silicon sensors and readout electronics must be characterized through a series of quality control (QC) and quality assurance tests. These tests ensure any defect is captured at the earliest possible stage. One such defect, callled a pinhole, occurs when the strip implant and the metal readout electrode are shorted through the intermediary dielectric layer. Notably, the introduction of pinholes during module assembly and pinhole effects on completed modules, especially on leakage current measurement circuitry, have never been studied. In this paper, we investigate the effect of such connections on the sensor leakage current measurements of completed modules and introduce new ways to locate pinholed strips. Here, with minor modifications to testing procedures, such defects are shown not to impede module testing or performance.

FOS: Physical sciences↗
DOE OSTI2025

Exploring the energy landscape of RBMs: reciprocal space insights into bosons, hierarchical learning and symmetry breaking

Deep generative models have become ubiquitous due to their ability to learn and sample from complex distributions. Despite the proliferation of various frameworks, the relationships among these models remain largely unexplored, a gap that hinders the development of a unified theory of AI learning. In this work, we address two central challenges: clarifying the connections between different deep generative models and deepening our understanding of their learning mechanisms. We focus on Restricted Boltzmann Machines (RBMs), a class of generative models known for their universal approximation capabilities for discrete distributions. By introducing a reciprocal space formulation for RBMs, we reveal a connection between these models, diffusion processes, and systems of coupled bosons. Our analysis shows that at initialization, the RBM operates at a saddle point, where the local curvature is determined by the singular values of the weight matrix, whose distribution follows the Marc̆enko-Pastur law and exhibits rotational symmetry. During training, this rotational symmetry is broken due to hierarchical learning, where different degrees of freedom progressively capture features at multiple levels of abstraction. This leads to a symmetry breaking in the energy landscape, reminiscent of Landau’s theory. This symmetry breaking in the energy landscape is characterized by the singular values and the weight matrix eigenvector matrix. We derive the corresponding free energy in a mean-field approximation. We show that in the limit of infinite size RBM, the reciprocal variables are Gaussian distributed. Our findings indicate that in this regime, there will be some modes for which the diffusion process will not converge to the Boltzmann distribution. To illustrate our results, we trained replicas of RBMs with different hidden layer sizes using the MNIST dataset. Our findings not only bridge the gap between disparate generative frameworks but also shed light on the fundamental processes underpinning learning in deep generative models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Resolving turbulent magnetohydrodynamics: a hybrid operator-diffusion framework

We present a hybrid machine learning framework that combines physics-informed neural operators (PINOs) with score-based generative diffusion models to simulate the full spatio-temporal evolution of two-dimensional, incompressible, resistive magnetohydrodynamic turbulence across a broad range of Reynolds numbers (Re). The framework leverages the equation-constrained generalization capabilities of PINOs to predict coherent, low-frequency dynamics, while a conditional diffusion model stochastically corrects high-frequency residuals, enabling accurate modeling of fully developed turbulence. Trained on a comprehensive ensemble of high-fidelity simulations with Re ϵ {100, 250, 500, 750, 1000, 3000, 10000}, the approach achieves state-of-the-art accuracy in regimes previously inaccessible to deterministic surrogates. At Re = 1000 and 3000, the model faithfully reconstructs the full spectral energy distributions of both velocity and magnetic fields late into the simulation, capturing non-Gaussian statistics, intermittent structures, and cross-field correlations with high fidelity. At extreme turbulence levels (Re = 10 000), it remains the first surrogate capable of recovering the high-wavenumber evolution of the magnetic field, preserving large-scale morphology and enabling statistically meaningful predictions.

Diffusion-Integrated Neural Operators↗
DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗
DOE OSTI2024

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗