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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 199 records · Page 11

Bayesian Inferring Nucleon Gravitational Form Factors via Near-Threshold 𝐽/𝜓 Photoproduction

With Bayesian inference, we investigate the impact of recent near-threshold 𝐽/𝜓 production measurements by the 𝐽/𝜓⁢007 experiment and GlueX Collaboration on the extraction of proton gravitational form factors. We apply the generalized parton distribution framework at the next to leading order and demonstrate a stable expansion for the near-threshold kinematics. We find that the experimental constraints are in good agreement with the state-of-the-art lattice simulations, where negative 𝐶 𝑞 ⁡(𝑡) and 𝐶 𝑔 ⁡(𝑡) are strongly preferred. This highlights a great potential to extract them from future high-precision experiments.

QCD phenomenology↗

Constraining neutrino-nucleon form factors with charged-current scattering at the Electron-Ion Collider

Next-generation neutrino oscillation experiments such as the Deep Underground Neutrino Experiment require percent-level knowledge of neutrino-nucleon interaction cross sections. The nucleon axial form factor 𝐹 𝐴 ⁡(𝑄 2 ), parametrized by the axial mass 𝑀 𝐴 , is the dominant source of uncertainty in the quasielastic channel, and the parity-violating structure function 𝑥⁢𝐹 3 is poorly constrained on free nucleons. We propose using charged-current (CC) electron-proton scattering at the Electron-Ion Collider (EIC) to address both problems simultaneously. The measurement exploits three key features of the EIC: (1) helicity-selective electron bunches provide in situ electromagnetic background rejection; (2) a longitudinally polarized proton target enables extraction of 𝐹 𝐴 ⁡(𝑄 2 ) through the target-spin asymmetry 𝐴 𝑈⁢𝐿 ; and (3) the 𝑦-distribution leverage in CC deep inelastic scattering (DIS) separates 𝐹 2 and 𝑥⁢𝐹 3 on a free proton, without nuclear corrections. Using a Fisher information analysis at $\sqrt{𝑠}$ =141 GeV with 500 fb −1 of integrated luminosity, we project the Cramér-Rao statistical floor of 𝛿⁢𝑀 𝐴 ≈0.03 GeV (3%). Incorporating first-order realistic detector effects, such as zero-degree calorimeter acceptance, 𝑄 2 smearing (5%), and background noise from helicity subtraction, the projected sensitivity is severely background-limited due to the small signal-to-background ratio (𝑆/𝐵 ≈ 3 ×10 −4 ) in the elastic channel. Achieving competitive sensitivity (𝛿⁢𝑀 𝐴 ≈ 0.14 GeV) would require ∼10 −7 background suppression, 3 orders of magnitude beyond current projections. The CC DIS 𝑦 distribution provides subpercent extraction of 𝑥⁢𝐹$^{𝑊^{−}}_{3}$ over 0.05 < 𝑥 < 0.5, representing the most robust electroweak measurement in the near term.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Parameterizations of electron scattering form factors for elastic scattering and electroexcitation of nuclear states in 27 Al and 40 Ca

Here, we report on empirical parameterizations of longitudinal ($\mathscr{R}$ L ) and transverse ($\mathscr{R}$ T ) nuclear elec- tromagnetic form factors for elastic scattering and the excitations of nuclear states in 27 Al and 40 Ca. The parameterizations are needed for the calculations of radiative corrections in measurements of electron scattering cross sections on 27 Al and 40 Ca in the quasi-elastic, resonance and inelastic con- tinuum regions, provide the contribution of nuclear excitations in investigations of the Coulomb Sum Rule, and test theoretical model predictions for excitation of nuclear states in electron and neutrino interactions on nuclear targets at low energies.

elastic scattering reactions↗

Nucleon tensor form factors at large N c

We investigate nucleon tensor form factors in the large- N c limit. In this picture, the nucleon emerges as a state of the N c valence quarks, which were bound by pion mean fields that were created by the presence of the valence quarks self-consistently. We find that the tensor charge ( g T u − d = 0.99 ) and the anomalous tensor magnetic moment ( κ T u + d = 7.61 ) are dominated by valence quarks, while the tensor quadrupole moment ( Q T u − d = − 7.02 ) shows significant sea quark effects. We examine how these quantities vary as the average size of the pion mean field is changed, showing interpolation between nonrelativistic quark and Skyrme limits. We also observe that g T u − d and κ T u + d depend weakly on the pion mass. In contrast, Q T u − d exhibits strong enhancement near the chiral limit. The numerical results are in good agreement with available lattice quantum chromodynamics (QCD) data and provide predictions for unmeasured quantities. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Gravitational Form Factors of the Proton from Lattice QCD

The gravitational form factors (GFFs) of a hadron encode fundamental aspects of its structure, including its shape and size as defined from, e.g., its energy density. This Letter presents a determination of the flavor decomposition of the GFFs of the proton from lattice QCD, in the kinematic region 0 ≤−𝑡 ≤2 GeV 2 . The decomposition into up-, down-, strange-quark, and gluon contributions provides first-principles constraints on the role of each constituent in generating key proton structure observables, such as its mechanical radius, mass radius, and 𝐷 term.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-The-Meter Solar

The ever-growing integration of distributed energy resources (DERs), especially behind-the-meter (BTM) solar generations, poses imperative operational challenges to system operators such as regional transmission organizations (RTOs). It is important for RTOs to effectively and accurately extract actual load profiles at the transmission level for a single node with significant BTM solar injection. This paper first illustrates the necessity of disaggregating the daily actual load profile of a single node. Furthermore, by segmenting nodes with selected timeseries features, nodes with significant BTM solar generation are identified. Lastly, a bi-level framework is proposed, comprising reference node disaggregation and DeepFM nodal disaggregation, aimed at disaggregating the nodal load profiles from which system operators require more information. By adopting a hybrid Deep Factorization Machine (DeepFM) model, the model achieve accurate results by extracting both linear and nonlinear relations between nodes in the same region and the zonal load and nodal load profile. To overcome the lack of ground truth, this paper segments the load profile into daytime, nighttime, and zero-crossing points and utilizes the latter two for evaluation purposes. The proposed disaggregation procedure is validated using real world, minute-level, normalized, and anonymized nodal data in the PJM service territory.

42 ENGINEERING↗

Real-Time, Adaptive Radiological Anomaly Detection and Isotope Identification Using Non-Negative Matrix Factorization

Spectroscopic anomaly detection and isotope identification algorithms are integral components in nuclear nonproliferation applications such as search operations. The task is especially challenging in the case of mobile detector systems because the observed gamma-ray background changes more than for a static detector system, and a pretrained background model can easily find itself out of domain. The result is that algorithms may exceed their intended false alarm rate or sacrifice detection sensitivity to maintain the desired false alarm rate. Non-negative matrix factorization (NMF) is a powerful tool for spectral anomaly detection and identification, but, like many similar algorithms that rely on data-driven background models, in its conventional implementation, it is unable to update in real time to account for environmental changes that affect the background spectroscopic signature. Here, we have developed a novel NMF-based algorithm that periodically updates its background model to accommodate changing environmental conditions. The adaptive NMF algorithm involves fewer assumptions about its environment, making it more generalizable than existing NMF-based methods while maintaining or exceeding detection performance on simulated and real-world datasets.

Anomaly detection↗

Using DNA affinity purification sequencing (DAP-seq) to identify in vitro binding sites of potential Novosphingobium aromaticivorans DSM12444 transcription factors

Genome-wide binding sites of 44 putative transcription factors (TFs) from Novosphingobium aromaticivorans DSM12444 were analyzed using DNA affinity purification sequencing. We report that 32 of these TFs have at least one area of enrichment. These data will help better understand aromatic metabolism and other features of N. aromaticivorans biology.

DAP-seq↗

Randomized Algorithms for Symmetric Nonnegative Matrix Factorization

Symmetric Nonnegative Matrix Factorization (SymNMF) is a technique in data analysis and machine learning that approximates a matrix with a product of a nonnegative, low-rank matrix and it transpose. To design faster and more scalable algorithms for SymNMF we develop two randomized algorithms for its computation. The first method uses randomized matrix sketching to compute an initial low-rank approximation to the input matrix and proceeds to uses this as a low-rank input to rapidly compute a SymNMF. The second methods uses randomized leverage score sampling to approximately solve constrained least squares problems. Many successful methods for SymNMF rely on (approximately) solving sequences of constrained least squares problems. Here, we prove theoretically that leverage score sampling can approximately solve constrained least squares problems to e-accuracy. Finally we demonstrate both methods work in practice by applying them to graph clustering tasks on large real world data sets. These experiments show that our methods approximately maintain solution quality and achieve significant speed ups for both large dense and large sparse problems.

97 MATHEMATICS AND COMPUTING↗

Human Factors Considerations for Anticipated Uses of Autonomy in Advanced Reactor Technologies

The objective of this report is examine anticipated advanced reactor designs that incorporate high levels of autonomy in operation of advanced reactor systems or facilities, and to begin identifying the human factors engineering (HFE) considerations relevant to those designs. The insights gained will help identify areas where U.S. Nuclear Regulatory Commission (NRC) may need to develop or update review guidance to adequately address HFE considerations essential for safe operation. The adequacy of existing guidance, along with recommendations for updates or new guidance, may be addressed in future reports. We use the term “landscape analysis” to describe the review, analysis, and characterization of publicly available information on the anticipated future state of the industry regarding particular technologies or operational concepts. This landscape analysis considers the potential range of advanced reactor automation concepts that may be used for monitoring and controlling nuclear systems and facilities, including the potential for highly automated, near autonomous, or fully autonomous operation of advanced nuclear reactors.

99 - GENERAL AND MISCELLANEOUS↗

Effect of Thermodynamic and Environmental Factors on Crystallization of DNA‐Origami Superlattices

The directed self‐assembly of nanoscale materials into ordered superlattices presents a powerful strategy for creating next‐generation materials with programmable mechanical, optical, and photonic properties. Deoxyribonucleic acid (DNA) origami has emerged as a versatile scaffold for encoding nanoscale geometry and guiding the crystallization of complex 3D architectures. However, a systematic understanding of the parameters that govern the efficiency and quality of superlattice formation remains limited. In this study, we utilize octahedral DNA nanoscale frames as a model system to investigate the relative influence of key factors, including buffer composition, ionic strength, frame concentration, and thermal annealing protocols, on the size, order, and reproducibility of the resulting superlattices. Our findings provide a quantitative framework to rationally optimize DNA‐based assembly pathways. Structural characterization via small‐angle x‐ray scattering (SAXS), scanning electron microscopy (SEM), and optical microscopy validates the quality and fidelity of the assembled lattices. Moreover, by templating these DNA frameworks into inorganic replicas, we establish general design principles that extend beyond biomolecular systems, providing a foundation for the synthesis of programmable materials in broader nanofabrication contexts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Factors Influencing Gas Evolution from High‐Nickel Layered Oxide Cathodes in Lithium‐Based Batteries

Abstract Gas evolution from high‐nickel layered oxide cathodes (>90% Ni) remains a major issue for their practical application. Gaseous species, such as CO 2 , O 2 , and CO, that are evolved at high states of charge (SOC) worsen the overall safety of batteries, as pressure build‐up within the cell may lead to cell rupture. Since these gasses are produced during cathode degradation, tracking the formation of gasses is also important in diagnosing cathode failure. Online electrochemical mass spectrometry (OEMS) is a powerful in situ technique to study gas evolution from the cathode during high‐voltage charge. However, the differences in the OEMS experimental setups between different groups make it challenging to compare results between groups. In this perspective, the various factors that influence gas evolution based on the OEMS results collected in this group are presented. The focus is on the conditions that lead to gas release, with a particular emphasis on reactive oxygen formation and subsequent chemical reactions with the electrolyte. Promising strategies, such as electrolytes, compositional tuning, and surface coatings that are effective at suppressing gas evolution from the cathode are highlighted. Critical insights into mitigating cathode degradation and gas evolution are provided to guide the development of safer, high‐energy batteries.

Chemistry↗

De Novo Design of High‐Affinity Miniprotein Binders Targeting Francisella Tularensis Virulence Factor

Abstract Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella‐like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well‐defined binding pockets and structural information on native interactions has hindered structure‐guided ligand discovery against Flpp3. Here, we used a combination of physics‐based and deep‐learning methods to design high‐affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24–110 nM. For the second site, an initial binder showed a dissociation constant ( K D ) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub‐nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X‐ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (Cα root‐mean‐square deviation (RMSD): 0.9 Å). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

Gokce‐Alpkilic, Gizem [Molecular Engineering and S↗

Movement Models to Predict Low‐Altitude Flight of Soaring Birds Using Look‐Ahead Environmental Factors

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤ 200 m above ground level), which puts them at risk of collision with wind turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles (Aquila chrysaetos) as a function of ecological covariates at the current location as well as those within an eagle's line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of change of heading and the orographic updraft conditions within an eagle's line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

17 WIND ENERGY↗

Streptococcus pneumoniae HtrA is a dynamic and monomeric virulence factor capable of forming larger oligomeric complexes

Abstract High‐temperature requirement A (HtrA) proteases are a conserved family of serine proteases central to protein quality control and bacterial virulence. While Gram‐negative and human HtrAs are structurally well studied, Gram‐positive homologs remain essentially uncharacterized. Here, we present the first integrated structural and mechanistic analysis of a Gram‐positive HtrA, from Streptococcus pneumoniae , a virulence factor essential for adhesion and infection in vivo. Proteomic profiling of an htrA knockout and cleavage assays demonstrate that S. pneumoniae HtrA is required for protein quality control, with the PDZ domain mediating substrate recognition. Biochemically, S. pneumoniae HtrA exists exclusively as a monomer in solution, a striking divergence from canonical trimeric HtrAs that we show is shared with other Gram‐positive homologs. NMR analyses reveal that the monomer dynamically samples open and closed conformations, while cryo‐EM of a catalytic mutant identifies a hexamer stabilized by a unique LoopA–PDZ interaction. Together, these findings define S. pneumoniae HtrA as a dynamic monomer with interdomain coupling between its protease and PDZ domains, establishing Gram‐positive HtrAs as a mechanistically divergent subgroup within the HtrA family.

Lee, Eunjeong [Department of Biochemistry and Mole↗

Identification of a key water molecule involved in the macrophage migration inhibitory factor‐catalyzed tautomerization of para ‐hydroxyphenylpyruvate using neutron crystallography

Abstract Neutron crystallography was used to determine a 2.5‐Å resolution all‐atom structure of macrophage migration inhibitory factor (MIF) interacting with 3‐(4‐hydroxyphenyl)‐pyruvate (HPP). MIF is a pro‐inflammatory, pro‐tumorigenic protein that may be an attractive therapeutic target. MIF catalyzes the interconversion of the keto and enol forms of HPP by a tautomerase reaction. Although HPP is evidently not a physiological substrate of MIF, many compounds that inhibit this activity in enzymatic assays have been found also to inhibit physiological activities of MIF. Therefore, the MIF‐catalyzed HPP tautomerization reaction is used in initial screening of compounds in the search for inhibitors of MIF physiological activity. The neutron diffraction‐derived crystal structure reveals the position of a water molecule involved in the tautomerization reaction, and also confirms the charged state of lysine‐32 in the active site. The structure confirms the previously proposed catalytic mechanism of MIF, with the N‐terminal Pro‐1 abstracting a proton to generate an HPP enolate intermediate which is subsequently protonated. The structure reported herein reveals that this proton is supplied by a neighboring water molecule. Along with the neutron structure, a room‐temperature synchrotron x‐ray crystal structure reveals a covalent adduct between HPP and MIF. While this adduct is a result of radiation‐induced chemistry, its formation confirms the catalytic role of the active site residue because a covalent complex could only form if the reactive carbon of the substrate is correctly positioned by the enzyme.

Schröder, Gabriela C. [Department of Molecular and↗

Bottom quark energy loss and hadronization with B + and ${\textrm{B}}_{\textrm{s}}^0$ nuclear modification factors using pp and PbPb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

The production cross sections of $ {\textrm{B}}_{\textrm{s}}^0 $ and B$^{+}$ mesons are reported in proton-proton (pp) collisions recorded by the CMS experiment at the CERN LHC with a center-of-mass energy of 5.02 TeV. The data sample corresponds to an integrated luminosity of 302 pb$^{−1}$. The cross sections are based on measurements of the $ {\textrm{B}}_{\textrm{s}}^0 $→ J/ψ(μ$^{+}$μ$^{−}$)ϕ(1020)(K$^{+}$K$^{−}$) and B$^{+}$→ J/ψ(μ$^{+}$μ$^{−}$)K$^{+}$ decay channels. Results are presented in the transverse momentum (p$_{T}$) range 7–50 GeV/c and the rapidity interval |y| < 2.4 for the B mesons. The measured p$_{T}$-differential cross sections of B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ in pp collisions are well described by fixed-order plus next-to-leading logarithm perturbative quantum chromodynamics calculations. Using previous PbPb collision measurements at the same nucleon-nucleon center-of-mass energy, the nuclear modification factors, R$_{AA}$, of the B mesons are determined. For p$_{T}$> 10 GeV/c, both mesons are found to be suppressed in PbPb collisions (with R$_{AA}$ values significantly below unity), with less suppression observed for the $ {\textrm{B}}_{\textrm{s}}^0 $ mesons. In this p$_{T}$ range, the R$_{AA}$ values for the B$^{+}$ mesons are consistent with those for inclusive charged hadrons and D$^{0}$ mesons. Below 10 GeV/c, both B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ are found to be less suppressed than either inclusive charged hadrons or D$^{0}$ mesons, with the $ {\textrm{B}}_{\textrm{s}}^0 $R$_{AA}$ value consistent with unity. The R$_{AA}$ values found for the B$^{+}$ and $ {\textrm{B}}_{\textrm{s}}^0 $ are compared to theoretical calculations, providing constraints on the mechanism of bottom quark energy loss and hadronization in the quark-gluon plasma, the hot and dense matter created in ultrarelativistic heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗