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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

First identification of resonant states in the {sup 45}V(p, {gamma}){sup 46}Cr reaction and their influence on the production of {sup 44}Ti in Core Collapse Supernovae

The observation of active 44Ti in supernova remnants offers the potential to solve one of the most debated questions in modern astrophysics, the exact underlying explosion mechanism of core collapse supernovae (CCSNe). In particular, a comparison between the predicted synthesized yield of 44Ti and the ejected flux is expected to allow for a determination of the mass cut of the star. Unfortunately, such comparisons are currently severely hindered by large uncertainties in the nuclear reactions governing the production and destruction of 44Ti. On this note, the astrophysical 45Vðp; γÞ46Cr reaction is expected to play a decisive role. We present the first experimental information on resonant states in the 45Vðp; γÞ46Cr reaction. Excitation energies have been measured with high precision for ten previously unknown, low-spin, proton-unbound states in 46Cr, and spin-parity-assignment constraints have been made using observed γ-decay patterns and shell-model calculations. We find that an l ¼ 1 resonance at 714 keV dominates the 45Vðp; γÞ46Cr reaction for the entire temperature range of α-rich freezeout. Moreover, the nominal rate is found to be ∼25–50% of previous estimates for T > 1.2 GK, indicating an increase in 44Ti production in CCSNe of ∼20–35%.

Cousins, C↗
DOE OSTI2025

First Event-by-Event Identification of Cherenkov Radiation from Sub-Mev Particles in Liquid Argon

This Letter reports the event-by-event observation of Cherenkov light from sub-MeV electrons in a high scintillation light-yield liquid argon detector by the coherent CAPTAIN-Mills (CCM) experiment. The CCM200 detector, located at Los Alamos National Laboratory, instruments seven tons (fiducial volume) of liquid argon with 200 eight-inch photomultiplier tubes, 80% of which are coated in a wavelength-shifting material and the remaining 20% are uncoated. In the prompt time region of an event, defined as - 6 ≤ t < 0 ns relative to the event start time t = 0 , the uncoated photomultiplier tubes are primarily sensitive to visible Cherenkov photons. Using gamma rays from a Na 22 source for production of sub-MeV electrons, we isolated prompt Cherenkov light with > 5 σ confidence and developed a selection to obtain a low-background electromagnetic sample. This is the first event-by-event observation of Cherenkov photons from sub-MeV electrons in a high-yield scintillator detector and represents a milestone in low-energy particle detector development.

Aguilar-Arevalo, A. A. [UNAM, Mexico]↗
DOE OSTI2025

Identification of Prompt Proton Emission in $N = Z - 1$ 61 Ga: Isospin Symmetry at the Limit of Nuclear Binding

Excited states in the proton drip line nucleus 61 Ga were populated via the fusion-evaporation reaction 24 Mg ⁢( 40 Ca, 𝑝⁢2⁢𝑛)⁢ 61 Ga. The experimental setup at Argonne National Laboratory comprised a novel combination of the Gammasphere array with two CD-shaped double-sided Si-strip detectors inside the Microball CsI(Tl) charged-particle detection array, as well as the Neutron-Shell liquid scintillators and the Fragment Mass Analyzer. Owing to the setup’s unprecedented in-beam proton spectroscopy and tracking capabilities, a coincidence between a 957.6(5)-keV 𝛾 ray and a 1.876(24)-MeV proton line was observed, which identifies the quasibound proton 𝜋⁢𝑔 9/2 single-particle state in 61 Ga at 𝐸 𝑥 = 2150⁢(34) keV. This probes isospin symmetry at the limit of nuclear binding by providing a unique challenge for the shell-model interpretation of mirror nuclei beyond doubly magic 56 Ni .

Hrabar, Yuliia [Lund Univ. (Sweden)] (ORCID:000000↗
DOE OSTI2025

Flow matching beyond kinematics: Generating jets with particle identification and trajectory displacement information

We introduce the first generative model trained on the etlass dataset. Our model generates jets at the constituent level, and it is a permutation-equivariant continuous normalizing flow (CNF) trained with the flow matching technique. It is conditioned on the jet type, so that a single model can be used to generate the ten different jet types of etlass. For the first time, we also introduce a generative model that goes beyond the kinematic features of jet constituents. The etlass dataset includes more features, such as particle-ID and track impact parameter, and we demonstrate that our CNF can accurately model all of these additional features as well. Our generative model for etlass expands on the versatility of existing jet generation techniques, enhancing their potential utility in high-energy physics research, and offering a more comprehensive understanding of the generated jets. Published by the American Physical Society 2025

Birk, Joschka (ORCID:0000000219310127)↗
DOE OSTI2026

Identification and denoising of radio signals from cosmic-ray air showers using convolutional neural networks

Radio pulses generated by cosmic-ray air showers can be used to reconstruct key properties like the energy and depth of the electromagnetic component of cosmic-ray air showers. Radio detection threshold, influenced by natural and anthropogenic radio background, can be reduced through various techniques. In this work, we demonstrate that convolutional neural networks (CNNs) are an effective way to lower the threshold. We developed two CNNs: a classifier to distinguish radio signal waveforms from background noise and a denoiser to clean contaminated radio signals. Following the training and testing phases, we applied the networks to air-shower data triggered by scintillation detectors of the prototype station for the enhancement of IceTop, IceCube’s surface array at the South Pole. Over a four-month period, we identified 554 cosmic-ray events in coincidence with IceTop, approximately five times more compared to a reference method based on a cut on the signal-to-noise ratio. Comparisons with IceTop measurements of the same air showers confirmed that the CNNs reliably identified cosmic-ray radio pulses and outperformed the reference method. Additionally, we find that CNNs reduce the false-positive rate of air-shower candidates and effectively denoise radio waveforms, thereby improving the accuracy of the power and arrival time reconstruction of radio pulses.

Abbasi, R↗
DOE OSTI2025

Coincident learning for beam-based rf station fault identification using phase information at the SLAC linac coherent light source

Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase data to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.

Accelerator Physics (physics.acc-ph)↗
DOE OSTI2024

Mixture-of-Experts for Multi-Domain Defect Identification in Non-Destructive Inspection

Composite materials are widely used in aircraft structures because of their superior mechanical properties. However, their complex failure modes require sophisticated inspection methods to ensure structural integrity. Ultrasonic testing (UT) is a common non-destructive inspection (NDI) technique for aircraft composites that can detect internal and external defects with high resolution and accuracy. Despite their effectiveness, traditional UT methods rely on the manual interpretation of ultrasonic signals, which is time-consuming, labor-intensive, and subjective. Furthermore, processing such large-scale data, particularly across materials of varying thicknesses, significantly increases the computational demands of deep learning model optimization. To overcome these challenges, we propose an efficient sparse mixture-of-experts (MoE) model with a multi-level loss function and introduce four novel training objectives to improve computational efficiency and accuracy in identifying surface defects in composite aircraft materials. Here, we evaluated our approach on material with multiple thicknesses or domains comprising various defects. Our experimental results demonstrate higher accuracy and F1-Score, with only 10% training epochs compared to baseline MoE.

composite materials↗
DOE OSTI2025

Crack Identification and Characterization in Deformed Nb3Sn Rutherford Cable Stacks Using Machine Learning

An investigation of instance segmentation of cracks in Nb3Sn 4-stack 40-strand Rutherford cables using machine learning is presented. Three samples were uniaxially and biaxially loaded before metallographic inspections were performed. The Mask R-CNN model was used in the Detectron2 framework with pre-trained weights but fine-tuned to detect and segment cracks. The model detected cracks with bounding box and mask average precisions (AP) of 42.8 and 27.9, respectively, and was used for instance segmentation of all cracks in the three samples. More cracks were found in the sample pre-loaded along the z-axis (i.e., along the cable length). Pre-loading along the x-axis (i.e., on the cables edges) reduced the number of cracks and changed the crack orientation distribution, away from being highly aligned with the y-axis (i.e., normal to the cables broad faces), i.e., the direction with the highest applied load. Fine-tuning of the Segment Anything Model (SAM) was also studied but performed poorly without human-provided prompts. However, the zero-shot capability of SAM showed high promises to accelerate the image annotation process for applications beyond this study.

Croteau, Jean-Francois↗
DOE OSTI2024

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗
DOE OSTI2024

Identification of glycosyltransferases mediating 2‐ O ‐arabinopyranosyl and 2‐ O ‐galactosyl substitutions of glucuronosyl side chains of xylan

SUMMARY Xylan is one of the major hemicelluloses in plant cell walls and its xylosyl backbone is often decorated at O ‐2 with glucuronic acid (GlcA) and/or methylglucuronic acid (MeGlcA) residues. The GlcA/MeGlcA side chains may be further substituted with 2‐ O ‐arabinopyranose (Ara p ) or 2‐ O ‐galactopyranose (Gal) residues in some plant species, but the enzymes responsible for these substitutions remain unknown. During our endeavor to investigate the enzymatic activities of Arabidopsis MUR3‐clade members of the GT47 glycosyltransferase family, we found that one of them was able to transfer Ara p from UDP‐Ara p onto O ‐2 of GlcA side chains of xylan, and thus it was named xylan 2‐ O ‐arabinopyranosyltransferase 1 (AtXAPT1). The function of AtXAPT1 was verified in planta by its T‐DNA knockout mutation showing a loss of the Ara p substitution on xylan GlcA side chains. Further biochemical characterization of XAPT close homologs from other plant species demonstrated that while the poplar ones had the same catalytic activity as AtXAPT1, those from Eucalyptus , lemon‐scented gum, sea apple, 'Ohi'a lehua, duckweed and purple yam were capable of catalyzing both 2‐ O ‐Ara p and 2‐ O ‐Gal substitutions of xylan GlcA side chains albeit with differential activities. Sequential reactions with XAPTs and glucuronoxylan methyltransferase 3 (GXM3) showed that XAPTs acted poorly on MeGlcA side chains, whereas GXM3 could efficiently methylate arabinosylated or galactosylated GlcA side chains of xylan. Furthermore, molecular docking and site‐directed mutagenesis analyses of Eucalyptus XAPT1 revealed critical roles of several amino acid residues at the putative active site in its activity. Together, these findings establish that XAPTs residing in the MUR3 clade of family GT47 are responsible for 2‐ O ‐arabinopyranosylation and 2‐ O ‐galactosylation of GlcA side chains of xylan.

Zhong, Ruiqin↗
DOE OSTI2025

A Design for Remanufacturing Framework Incorporating Identification, Evaluation, and Validation: A Case Study of Hydraulic Manifold

In recent years, academic researchers and engineers in the industry have widely recognized the necessity of integrating remanufacturing considerations into product design iterations to advance sustainability objectives. Acknowledging the importance of design for remanufacturing (DfRem), efforts were made to develop tools and guidelines that could be implemented in practice. However, such methods largely rely upon experiential insights and qualitative assessments, leaving a gap in the ability to quantitatively assess the economic and environmental impacts of design choices. To bridge this gap, we investigate existing efforts and present a framework for DfRem that integrates established design and remanufacturing practices into a cohesive workflow with quantitative assessments. To demonstrate its efficacy for making practical design changes for remanufacturing, we apply the framework to a hydraulic manifold in a transmission system for heavy-duty tractors. Through this industry-relevant case study, we focus on showcasing the practical utility of our framework. Based on the identified design modifications from remanufacturability analysis, we estimate the reductions in life cycle costs, energy consumption, and emissions. Afterward, the modifications are tested using physical experiments with plans for integration into future iterations of the hydraulic manifold design and production. Here, we anticipate this framework can illustrate the process of remanufacturing that ensures improvements in sustainability while maintaining performance and reliability standards.

design for X↗
DOE OSTI2025

Identification of contamination in the pulse-compression chamber of the OMEGA EP Laser System originating from clean room garments

The contamination of optical components with microscopic particles strongly impacts their ability to handle high-power or high-intensity laser pulses via an array of mechanisms. This work explores the nature and origin of a subset of contamination particles found inside the pulse-compression chamber of the OMEGA EP Laser System. Using Raman microscopy accompanied by other analytical methods, it was shown that sodium nitrate constitutes a significant fraction of the particles that possess diameters on the order of a few micrometers. Further investigation aiming to reveal the origin of these particles suggests that these sodium nitrate particles are deposited via shedding from the reusable clean room garments worn in the Laser Bay and compression chamber. Raman microscopy also revealed various plastic particles such as polystyrene, polyethylene, and poly(diallyl isophthalate).

Raman spectroscopy↗
DOE OSTI2025

Identification of key steps in the evolution of anaerobic methanotrophy in Candidatus Methanovorans (ANME-3) archaea

Despite their large environmental impact and multiple independent emergences, the processes leading to the evolution of anaerobic methanotrophic archaea (ANME) remain unclear. This work uses comparative metagenomics of a recently evolved but understudied ANME group, “Candidatus Methanovorans” (ANME-3), to identify evolutionary processes and innovations at work in ANME, which may be obscured in earlier evolved lineages. We identified horizontal transfer of hdrA homologs and convergent evolution in carbon and energy metabolic genes as potential early steps in Methanovorans evolution. We also identified the erosion of genes required for methylotrophic methanogenesis along with horizontal acquisition of multiheme cytochromes and other loci uniquely associated with ANME. The assembly and comparative analysis of multiple Methanovorans genomes offers important functional context for understanding the niche-defining metabolic differences between methane-oxidizing ANME and their methanogen relatives. Furthermore, this work illustrates the multiple evolutionary modes at play in the transition to a globally important metabolic niche.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification of short-range ordering motifs in semiconductors

Chemical short-range ordering is expected to be a key factor for tuning the electronic structure of semiconductors. However, experimental evidence of short-range ordering is still lacking due to the challenge of characterizing atomic-scale ordering motifs. Here, we determined the presence of short-range order in a ternary GeSiSn semiconductor system using advanced energy-filtered four-dimensional scanning transmission electron microscopy and large-scale atomistic models generated by a machine learning neuroevolution potential of first-principles accuracy. This approach revealed preferred ordering of different atomic species with the dominant occurrence of Si–Ge–Sn triplets. Our findings not only confirmed the presence of short-range order but also directly revealed the actual atomic structure, demonstrating the potential for informed atomic order–based band engineering as a third degree of freedom beyond composition and strain tuning.

Vogl, Lilian M. [University of California Berkeley↗
DOE OSTI2025

Multi-technique characterization of iron reduction by an Antarctic Shewanella : an analog system for putative Martian biosignature identification

ABSTRACT Microbes from terrestrial extreme environments enable testing of biosignature production in conditions relevant to astrobiological targets. Mars, which was likely more conducive to life during early warmer and wetter epochs, has inspired missions that search for signs of early life in the surficial rock record, including mineral or organic biosignatures. Microbial iron reduction is a common and ancient metabolism that may have also operated on other rocky celestial bodies. To investigate biosignature production during iron reduction, aShewanellasp. (strain BF02_Schw) isolated from a subglacial discharge known as Blood Falls, Antarctica, was incubated with the electron acceptor ferrihydrite (Fh). Biosignatures associated with Fh reduction were identified using a suite of techniques currently utilized or proposed for Mars missions, including X-ray diffraction and infrared, Mössbauer, and Raman spectroscopy. The biotic origin of features was validated by transcriptional changes observed between treatments with and without Fh and comparison to killed controls. In live treatments, Fh was reduced to magnetite and goethite, both detected in Martian lacustrine basins. Several soluble and volatile metabolites were also detected, including riboflavin and dimethyl sulfide (DMS), which could be astrobiological indicators of active microbial processes. While none of the identified biosignatures individually would serve as definitive proof of life (past or present), detecting concomitant features associated with known terrestrial biotic processes would provide compelling rationale for more targeted life detection missions. Terrestrial extremophiles can support the exploration of astrobiologically relevant microbial processes, validation of life detection instrumentation, and potentially the discovery of new biomarkers. IMPORTANCE Culture-based experiments with terrestrial extremophiles can elucidate biosignatures that may be analogous to those produced under extraterrestrial conditions, and thus inform sampling and technology strategies for future missions. Here, we demonstrate the production of several biosignatures under iron-reducing conditions byShewanellasp. BF02_Schw, originally isolated from an Antarctic analog feature. These biosignatures could be detectable using flight-ready instrumentation. Growth experiments with terrestrial extremophiles can identify biosignatures measurable by current methodologies and inform the development and optimization of techniques for detecting extant or extinct life on other worlds.

Biotechnology & Applied Microbiology↗