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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Diagnosing electric and magnetic fields in laser-driven coil targets

Laser-driven capacitor coils are widely used to generate intense magnetic fields for various applications in high-energy-density (HED) physics research. Accurate measurement of the magnetic fields is essential but challenging, due to the overlapping contributions from magnetic and electric fields in proton radiography, which is the primary tool diagnosing the field generation around the coils. In this study, we systematically analyze proton radiographs obtained from laser-driven capacitor-coil targets along two orthogonal axes under various electromagnetic field conditions, including magnetic field only, electric field only, and combined electromagnetic fields. By analyzing key features in the radiographs, we distinguish and characterize the respective contributions from magnetic and electric fields. Using detailed simulations validated by experimental benchmarks, methods to isolate and quantify the magnetic field and electric field are given. The methods are successfully applied to determine the electric current and charge distribution in a double coil configuration. Our findings provide insights into improving the diagnostic capability of proton radiography, potentially leading to more accurate measurements of electromagnetic fields and enhancing the utility of laser-driven capacitor coils in HED experiments.

electromagnetic field diagnostics↗
DOE OSTI2025

Electron transport in a tokamak scrape-off layer: impact of toroidal nonuniformities of divertor targets

An analysis of electron dynamics is carried out in the tokamak scrape-off layer (SOL) region. Small non-axisymmetric perturbations of the divertor target sheath potential affect electron drift orbits in the SOL and may lead to non-ambipolar electron radial transport. The resulting rates of electron convection, diffusion, and mobility are calculated analytically, and the analytic results are compared with direct numerical simulations of electron drift orbits. The proposed mechanism of non-ambipolar electron transport may be relevant to the sustainment of the SOL plasma quasi-neutrality in the ‘heuristic’ model of the SOL width (Eich et al 2011 Phys. Rev. Lett. 107 215001).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Comparison of chamber beam geometry robustness to mispointing, imbalance and target offset for direct-drive laser fusion facilities

This study focuses on the optimization of beam chamber geometry designs for future direct-drive laser facilities. It provides a review of leading target chamber geometries, with a particular emphasis on random errors. Through comprehensive solid-sphere illuminations and analysis, we identify an optimized beam geometry design, highlighting its robustness and performance under realistic experimental conditions. Three major sources of random errors are evaluated, closely linked to experimental evaluations at OMEGA. The findings underscore the importance of optimizing the irradiation system alongside beam pattern considerations to enhance the efficiency and reliability of inertial confinement fusion experiments. We conclude that for a desired illumination uniformity of 1% in the presence of system errors, the split icosahedron design is the most robust. However, for a 0.3% uniformity goal, the charged-particle, icosahedron, and t-sphere methods exhibit similar performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Investigating resource-efficient neutron/gamma classification ML models targeting eFPGAs

There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physics communities. A big driver has been the release of the Python package, hls4ml, which has enabled porting models specified and trained using Python ML libraries to register transfer level (RTL) code. So far, the primary end targets have been commercial field-programmable gate arrays (FPGAs) or synthesized custom blocks on application specific integrated circuits (ASICs). However, recent developments in open-source embedded FPGA (eFPGA) frameworks now provide an alternate, more flexible pathway for implementing ML models in hardware. These customized eFPGA fabrics can be integrated as part of an overall chip design. In general, the decision between a fully custom, eFPGA, or commercial FPGA ML implementation will depend on the details of the end-use application. In this work, we explored the parameter space for eFPGA implementations of fully-connected neural network (fcNN) and boosted decision tree (BDT) models using the task of neutron/gamma classification with a specific focus on resource efficiency. We used data collected using an AmBe sealed source incident on Stilbene, which was optically coupled to an OnSemi J-series silicon photomultiplier (SiPM) to generate training and test data for this study. We investigated relevant input features and the effects of bit-resolution and sampling rate as well as trade-offs in hyperparameters for both ML architectures while tracking total resource usage. The performance metric used to track model performance was the calculated neutron efficiency at a gamma leakage of 10 -3 . The results of the study will be used to aid the specification of an eFPGA fabric, which will be integrated as part of a test chip.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Targeted seed EMS mutagenesis reveals a basic helix–loop–helix transcription factor underlying male sterility in sorghum

Abstract Forward genetic screens of mutant populations are fundamental for functional genomics studies. However, isolating independent mutant alleles to molecularly identify causal genes is challenging in species recalcitrant to genetic manipulation. Here, we demonstrate that classic seed ethyl methanesulfonate (EMS) mutagenesis coupled with genome sequencing can overcome this limitation in sorghum. We used this method to generate new mutant alleles of sorghum MALE STERILE 8 (MS8) and identified the causal locus for the ms8 phenotype as Sobic.004G270900, which encodes the sorghum ortholog of maize bhlh122, a basic helix–loop–helix (bHLH) transcription factor required for male fertility in maize. Bulked segregant analysis mapped ms8-1 to a region on chromosome 4 containing Sobic.004G270900. Seeds from heterozygous MS8/ms8-1 plants were mutagenized and screened for chimeric inflorescences containing sectors with white, sterile anthers resembling the ms8-1 homozygous phenotype. DNA sequencing of sterile and fertile sectors from a single chimeric inflorescence revealed two mutations in Sobic.004G270900 within the sterile sector, but not the fertile sector. Isolation of this loss-of-function allele (ms8-2) established Sobic.004G270900 as the causative locus for male sterility in the ms8 mutant. We generated additional alleles of MS8 in a different genetic background using CRISPR/Cas9-based gene editing, where deletions in Sobic.004G270900 also resulted in male sterility. Our work identified a gene underlying male sterility in sorghum and provides a novel and straightforward genetic tool for researchers who lack access to advanced transformation facilities to validate gene candidates. Unlike gene editing, no prior knowledge of candidate genes is required for targeted seed EMS mutagenesis to aid identification of causal loci.

Genetics & Heredity↗
DOE OSTI2025

UDP-glucuronic acid decarboxylase in alfalfa: a target to improve ruminal digestibility of stems

Alfalfa (Medicago sativa) has a high nutritional value, but poor digestibility of the stems limits its value as an energy source in ruminant diets. Xylan and lignin negatively affect cell wall digestibility, whereas pectins have high digestibility in the rumen. In plants, UDP-xylose synthase (UXS) catalyses the decarboxylation of UDP-glucuronic acid to form UDP-xylose in an irreversible step that is key for xylan synthesis. Here, we functionally characterized two UXS genes in alfalfa, namely MsaUXS2 and MsaUXS4, and investigated their impact on ruminal digestibility. Both genes are more highly expressed in stems than leaves, and the enzymes have UDP-glucuronic acid decarboxylase activity in vitro. Silencing of MsaUXS2 and MsaUXS4 via RNAi altered plant growth and resulted in a 40% decrease in xylose, a 115% increase in arabinose, and a 60% increase in galacturonic acid in the polysaccharide matrix as well as a 20% decrease in lignin in the cell wall. Together, our results show a major role for UXS2 and UXS4 in xylan synthesis and secondary cell wall deposition in alfalfa. Additionally, in vitro rumen digestibility assays for the silenced lines had on average 30% increased gas production at 24 h, demonstrating the potential of targeting UXS genes to increase stem digestibility.

UDP-xylose synthase↗
DOE OSTI2024

A compact stem-loop DNA aptamer targets a uracil-binding pocket in the SARS-CoV-2 nucleocapsid RNA-binding domain

Abstract SARS-CoV-2 nucleocapsid (N) protein is a structural component of the virus with essential roles in the replication and packaging of the viral RNA genome. The N protein is also an important target of COVID-19 antigen tests and a promising vaccine candidate along with the spike protein. Here, we report a compact stem-loop DNA aptamer that binds tightly to the N-terminal RNA-binding domain of SARS-CoV-2 N protein. Crystallographic analysis shows that a hexanucleotide DNA motif (5′-TCGGAT-3′) of the aptamer fits into a positively charged concave surface of N-NTD and engages essential RNA-binding residues including Tyr109, which mediates a sequence-specific interaction in a uracil-binding pocket. Avid binding of the DNA aptamer allows isolation and sensitive detection of full-length N protein from crude cell lysates, demonstrating its selectivity and utility in biochemical applications. We further designed a chemically modified DNA aptamer and used it as a probe to examine the interaction of N-NTD with various RNA motifs, which revealed a strong preference for uridine-rich sequences. Our studies provide a high-affinity chemical probe for the SARS-CoV-2 N protein RNA-binding domain, which may be useful for diagnostic applications and investigating novel antiviral agents.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Target of 1 Rapamycin kinase is a positive regulator of plant fatty acid 2 and lipid synthesis

In eukaryotes, Target of Rapamycin (TOR), a conserved protein sensor kinase, integrates a diverse set of environmental cues, including growth factor signals, energy availability, and nutritional status, to direct cell growth. In plants, TOR is activated by light and sugars and regulates a wide range of cellular processes, including protein synthesis and metabolism. Fatty acid synthesis is key to membrane biogenesis that in turn, is required for cell growth. To elucidate the primary regulatory role(s) of TOR in lipid metabolism, we followed fatty acid and lipid changes in plants with altered TOR protein levels or activity for short durations, using Nicotiana benthamiana leaves, Arabidopsis seedlings and Brassica napus cell suspension cultures. Transient expression of TOR significantly elevated the levels of total fatty acids in Nicotiana benthamiana leaves, while treatment of Arabidopsis seedlings with Torin 2, a TOR specific inhibitor, for one day, caused significant reductions in fatty acids and membrane lipids. Similarly, incubating oil-producing Brassica napus suspension culture cells with Torin 2 for eight hours led to significant decreases in the levels of TFA and TAG. Taken together the results from three independent systems presented here establishes that TOR positively regulates lipid synthesis in plants, consistent with its role in animals. Furthermore, RNA-seq analysis of Torin 2-treated Arabidopsis seedlings showed that TOR promotes the upregulation of a number of genes involved in de novo fatty acid synthesis while downregulating genes involved in lipid turnover, which we propose as a mechanistic explanation for its promotion of lipid synthesis and accumulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue ‘The evolution of plant metabolism’.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2026

Small-𝑥 Factorization in the Target Fragmentation Region

We consider the differential cross-section for single-inclusive jet production with transverse momentum 𝑃 ⊥ in deep inelastic scattering at small Bjorken 𝑥 Bj , mediated by a virtual photon with virtuality 𝑄 2 . Unlike most studies at small 𝑥, which focus on particle production in the current fragmentation region, we investigate the kinematic regime where the jet is produced in the target fragmentation hemisphere of the Breit frame, and with 𝑃 ⊥ ≪ 𝑄. For a longitudinally polarized photon, we demonstrate that this cross section is not power suppressed in 𝑃 ⊥ /𝑄 and we derive a factorized expression in terms of extended quark and gluon jet fracture functions. Our formula, valid at next-to-leading order in 𝛼 𝑠 at small 𝑥, is akin to the Altarelli-Martinelli identity for the longitudinal DIS structure function. Numerical estimates show that the extended quark jet fracture function is the most sensitive to saturation effects in large nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

New thermal-relic targets for sub-GeV dark matter direct detection

Dark matter direct detection experiments involving electron recoils are beginning to test highly predictive, thermal-relic milestones for sub-GeV dark matter models. Due to the Lee-Weinberg bound, thermal dark matter candidates in this mass range necessarily require comparably light mediator particles to achieve a suitably large annihilation cross section. Here we present new thermal-relic milestones for sub-GeV dark matter candidates that couple to vector mediators. In these models, the mediators are massive gauge bosons of anomaly-free Abelian extensions to the Standard Model, including the dark photon, gauged L i - L j , B - L , and B - 3 L i models, where B is the baryon number, L is the lepton number, and i , j index the lepton families. Since the same interactions that govern cosmological production also govern electron scattering, the targets we present are firmly predictive and allow for these models to be robustly discovered or falsified. Furthermore, since the mediators we study exhaust the minimal anomaly-free U(1) extensions to the Standard Model, our results offer a complete list of predictive milestones for sub-GeV dark matter coupled to vector mediators.

Han, Xu [Chicago U.] (ORCID:0009000821607836)↗
DOE OSTI2025

Dihadron azimuthal correlations in deep-inelastic scattering off nuclear targets

We measured the nuclear dependence of the di-pion azimuthal correlation function in deepinelastic scattering (DIS) using the CEBAF Large Acceptance Spectrometer (CLAS) and a 5 GeV electron beam. As the nuclear-target size increases, transitioning from deuterium to carbon, iron, and lead, the correlation function broadens monotonically. Its shape exhibits a significant dependence on kinematics, including the transverse momentum of the pions and the difference in their rapidity. None of the various Monte-Carlo event generators we evaluated could fully replicate the observed correlation functions and nuclear effects throughout the entire phase space. As the first study of its kind in DIS experiments, this research provides an important baseline for enhancing our understanding of the interplay between the nuclear medium and the hadronization process in these reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Atomic binding corrections for high-energy fixed target experiments

High-energy beams incident on a fixed target may scatter against atomic electrons. To a first approximation, one can treat these electrons as free and at rest. For precision experiments, however, it is important to be able to estimate the size of, and when necessary calculate, subleading corrections. We discuss atomic binding corrections to relativistic lepton-electron scattering. We analyze hydrogen in detail, before generalizing our analysis to multi-electron atoms. Using the virial theorem, and many-body sum rules, we find that the corrections can be reduced to measured binding energies, and the expectation value of a single one-body operator. We comment on the phenomenological impact for neutrino flux normalization and an extraction of hadronic vacuum polarization from elastic muon electron scattering at MUonE.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Experimental targets for dark photon dark matter

Ultralight dark photon dark matter features distinctive cosmological and astrophysical signatures and is also supported by a burgeoning direct-detection program searching for its kinetic mixing with the ordinary photon over a wide mass range. Dark photons, however, cannot necessarily constitute the dark matter in all of this parameter space. In minimal models where the dark photon mass arises from a dark Higgs mechanism, early-Universe dynamics can easily breach the regime of validity of the low-energy effective theory for a massive vector field. In the process, the dark sector can collapse into a cosmic string network, precluding dark photons as viable dark matter. We establish the general conditions under which dark photon production avoids significant backreaction on the dark Higgs and identify regions of parameter space that naturally circumvent these constraints. After surveying implications for known dark photon production mechanisms, we propose novel models that set well-motivated experimental targets across much of the accessible parameter space. We also discuss complementary cosmological and astrophysical signatures that can probe the dark sector physics responsible for dark photon production.

Dark matter↗
DOE OSTI2025

Enhanced Isomer Population via Direct Irradiation of Solid-Density Targets Using a Compact Laser-Plasma Accelerator

Excitation of long-lived states in bromine nuclei using a tabletop laser-plasma accelerator providing pulsed (<100 fs) electron beams provided a sensitive probe of γ strength and level densities in the nuclear quasicontinuum and may indicate angular momentum coupling through electron-nuclear interactions. Solid-density active $LaBr_{3}$ targets absorb real and virtual photons up to 35 ± 2.5 MeV and deexcite through γ cascade into different states. Here, a factor of 4.354 ± 0.932 enhancement of the $^{80}Br^{m}/^{80}Br^{g}$ isomeric ratio was observed following electron irradiation, as compared to bremsstrahlung. Additional angular momentum transfer could possibly occur through nuclear-plasma or electron-nuclear interactions enabled by the ultrashort electron beam. Further investigation of these mechanisms could have far-reaching impact including decreased storage of long-term nuclear waste and an improved understanding of heavy element formation in astrophysical settings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Laser-driven ion and electron acceleration from near-critical density gas targets: Towards high-repetition rate operation in the 1 PW, sub-100 fs laser interaction regime

Ion acceleration from gaseous targets driven by relativistic-intensity lasers was demonstrated as early as the late 1990s, yet most of the experiments conducted to date have involved picosecond-duration, Nd:glass lasers operating at low repetition rate. Here, we present measurements on the interaction of ultraintense ( ≈ 10 20 W cm − 2 , 1 PW ) , ultrashort ( ≈ 70 fs ) Ti:Sa laser pulses with near-critical ( ≈ 10 20 cm − 3 ) helium gas jets, a debris-free targetry with the potential for future compatibility with high ( ≈ 1 Hz ) repetition rate operation. We provide evidence of α particles being forward accelerated up to ≈ 2.7 − MeV energy with a total flux of ≈ 10 11 sr − 1 as integrated over > 0.1 − MeV energies and detected within a 0.5 − mrad solid angle. We also report on on-axis emission of relativistic electrons with an exponentially decaying spectrum characterized by a ≈ 10 − MeV slope, i.e., five times larger than the standard ponderomotive scaling. The total charge of these electrons with energy above 2 MeV is estimated to be of ≈ 1 nC , corresponding to ≈ 0.1 % of the laser drive energy. In addition, we observe the formation of a plasma channel, extending longitudinally across the gas density maximum and expanding radially with time. These results are well captured by large-scale particle-in-cell simulations, which reveal that the detected fast ions most likely originate from reflection off the rapidly expanding channel walls. The latter process is predicted to yield ion energies in the MeV range, which compare well with the measurements. Finally, direct laser acceleration is shown to be the dominant mechanism behind the observed electron energization. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement

This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 ⁢O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗