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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing Top-Quark–Electron Interactions at Future Colliders

Top quark interactions offer a window into possible new high scale physics and many models of new physics predict that the top quark interactions will deviate significantly from those predicted by the standard model. We present an analysis of the experimental restrictions on anomalous 4-fermion 𝑒 + ⁢𝑒 − $⁢𝑡\bar{⁢𝑡}$ operators that is accurate to next-to-leading order (NLO) in both the electroweak and QCD interactions within the standard model effective field theory framework. At NLO, there is sensitivity to an extended set of anomalous interactions beyond those probed at leading order. A comparison of current limits from electroweak precision observables, along with expected future limits from Drell-Yan and $⁢𝑡\bar{⁢𝑡}$𝑒 +⁢ 𝑒 − production at the high luminosity LHC, from deep inelastic scattering at the EIC, and from projected sensitivities at the future FCC-ee and CEPC machines demonstrates that each of these programs extends the precision understanding of the interactions of top quarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Proton emission in ultraperipheral Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV

The first measurements of proton emission accompanied by neutron emission in the electromagnetic dissociation (EMD) of 208 Pb nuclei in the ALICE experiment at the Large Hadron Collider are presented. The EMD protons and neutrons emitted at very forward rapidities are detected by the proton and neutron zero degree calorimeters of the ALICE experiment. The emission cross sections of zero, one, two, and three protons accompanied by at least one neutron were measured in ultraperipheral 208 Pb − 208 Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02TeV. The 0p and 3p cross sections are described by the RELDIS model within their measurement uncertainties, while the 1p and 2p cross sections are underestimated by the model by 17–25%. According to this model, these 0p, 1p, 2p, and 3p cross sections are associated, respectively, with the production of various isotopes of Pb, Tl, Hg, and Au in the EMD of 208 Pb . The cross sections of the emission of a single proton accompanied by the emission of one, two, or three neutrons in EMD were also measured. The data are significantly overestimated by the RELDIS model, which predicts that the (1p,1n), (1p,2n), and (1p,3n) cross sections are very similar to the cross sections for the production of the thallium isotopes 206,205,204 Tl.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Evidence of Coherent Elastic Neutrino-Nucleus Scattering with COHERENT’s Germanium Array

We report the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) on natural germanium, measured at the Spallation Neutron Source at Oak Ridge National Laboratory. The Ge-Mini detector of the COHERENT collaboration employs large-mass, low-noise, high-purity germanium spectrometers, enabling excellent energy resolution, and an analysis threshold of 1.5 keV electron-equivalent ionization energy. We observe an on-beam excess of 20.6$^{+7.1}_{−6.3}$ counts with a total exposure of 10.22 GWhkg, and we reject the no-CEvNS hypothesis with 3.9⁢𝜎 significance. The result agrees with the predicted standard model of particle physics signal rate within 2⁢𝜎.

Electroweak interaction↗
DOE OSTI2025

Measurement of In-Medium Jet Modification Using Direct Photon + Jet and 𝜋 0 + Jet Correlations in 𝑝 + 𝑝 and Central Au + Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV

The STAR Collaboration presents measurements of the semi-inclusive distribution of charged-particle jets recoiling from energetic direct-photon (𝛾 dir ) and neutral-pion (𝜋 0 ) triggers in 𝑝 + 𝑝 and central Au + Au collisions at $\sqrt{s_{NN}}$ =2 00 GeV over a broad kinematic range, for jet resolution parameters 𝑅 = 0.2 and 0.5. Medium-induced jet yield suppression is observed to be larger for 𝑅 = 0.2 than for 0.5, reflecting the angular range of jet energy redistribution due to quenching. The predictions of model calculations incorporating jet quenching are not fully consistent with the observations. Furthermore, these results provide new insight into the physical origins of jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Sign Problem in Tensor-Network Contraction

We investigate how the computational difficulty of contracting tensor networks depends on the sign structure of the tensor entries. Using results from computational complexity, we observe that the approximate contraction of tensor networks with only positive entries has lower computational complexity as compared to tensor networks with general real or complex entries. This raises the question of how this transition in computational complexity manifests itself in the hardness of different tensor-network-contraction schemes. We pursue this question by studying random tensor networks with varying bias toward positive entries. First, we consider contraction via Monte Carlo sampling and find that the transition from hard to easy occurs when the tensor entries become predominantly positive; this can be understood as a tensor-network manifestation of the well-known negative-sign problem in quantum Monte Carlo. Second, we analyze the commonly used contraction based on boundary tensor networks. The performance of this scheme is governed by the number of correlations in contiguous parts of the tensor network (which by analogy can be thought of as entanglement). Remarkably, we find that the transition from hard to easy—i.e., from a volume-law to a boundary-law scaling of entanglement—already occurs for a slight bias of the tensor entries toward a positive mean, scaling inversely with the bond dimension D , and thus the problem becomes easy the earlier the larger D occurs. This is in contrast both to expectations and to the behavior found in Monte Carlo contraction, where the hardness at fixed bias increases with the bond dimension. To provide insight into this early breakdown of computational hardness and the accompanying entanglement transition, we construct an effective classical statistical-mechanical model that predicts a transition at a bias of the tensor entries of 1 / D , confirming our observations. We conclude by investigating the computational difficulty of computing expectation values of tensor-network wave functions (projected entangled-pair states, PEPSs) and find that in this setting, the complexity of entanglement-based contraction always remains low. We explain this by providing a local transformation that maps PEPS expectation values to a positive-valued tensor network. This not only provides insight into the origin of the observed boundary-law entanglement scaling but also suggests new approaches toward PEPS contraction based on positive decompositions. Published by the American Physical Society 2025

Chen, Jielun (ORCID:0000000178411545)↗
DOE OSTI2026

Search for Light Pseudoscalar Bosons, Pair-Produced in Higgs Boson Decays in the Four-Electron Final State in Proton-Proton Collisions at $\sqrt{s}=13$ TeV

A search for pairs of light neutral pseudoscalar bosons (𝐴) resulting from the decay of a Higgs boson is performed. The search is conducted using LHC proton-proton collision data at $\sqrt{s}=13$ TeV, collected with the CMS detector in 2016–2018 and corresponding to an integrated luminosity of 138 fb −1 . The 𝐴 boson decays into a highly collimated electron-positron pair. A novel multivariate algorithm using tracks and calorimeter information is developed to identify these distinctive signatures, and events are selected with two such merged electron-positron pairs. No significant excess above the standard model background predictions is observed. Upper limits on the branching fraction for 𝐻 → 𝐴⁢𝐴 → 4⁢𝑒 are set at 95% confidence level, for masses between 10 and 100 MeV and proper decay lengths below 100 μ⁢m, reaching branching fraction sensitivities as low as 10 −5 . This is the first search for Higgs boson decays to four electrons via light pseudoscalars at the LHC. It significantly improves the experimental sensitivity to axionlike particles with masses below 100 MeV.

Hayrapetyan, A. [Yerevan Physics Institute]↗
DOE OSTI2025

Neutrino and gamma-ray emissions from NGC 1068

IceCube has recently reported the detection of ∼1–10 TeV neutrinos from the nearby active galaxy, NGC 1068. The lack of TeV-scale emission from this source suggests that these neutrinos are generated in the dense corona that surrounds NGC 1068’s supermassive black hole. In this paper, we present a physical model for this source, including the processes of pair production, pion production, synchrotron, and inverse Compton scattering. We have also performed a new analysis of Fermi-LAT data from the direction of NGC 1068, finding that the gamma-ray emission from this source is very soft but bright at energies below ∼1 GeV . Our model can predict a gamma-ray spectrum that is consistent with Fermi-LAT observations when the magnetic field within the corona of this active galactic nucleus (AGN) is quite high, namely 𝐵 ≳6 kG . To explain the observed neutrino emission, this source must accelerate protons with a total power that is comparable to its intrinsic x-ray luminosity. In this context, we consider two additional nearby active galaxies, NGC 4151 and NGC 3079, which have been identified as promising targets for IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dopant Optimization of Donors in Semiconductor Opening Switches to Eliminate Prepulse

Semiconductor opening switches are solid-state devices capable of delivering nanosecond, hundreds of kilovolts pulses by interrupting kiloamps of current. The interruption of the current occurs in a moderately doped p-region when a high electric field region (HFR) is formed. The HFR occurs because the reverse pumping current cannot be supported by the saturation velocity and majority carrier concentration of the doping level. However, the donor profile also significantly affects the pulse performance. A secondary prepulse occurs if a secondary HFR is formed at the interface of the background n-doping and N+ doping (X n ) . By moving the location of X n deeper into the diode, the effect of the prepulse is reduced. This article investigates the effect of the donor doping profile on the performance metrics of semiconductor opening switches through technology computer-aided design (TCAD) simulations and experimental results. Through a SILVACO TCAD optimization, we designed a P + /p/n - base/n/N + where the intersection of the moderate p-region and intrinsic n-base region (X p ) is at 160 μm and X n is at 220 μm. This profile is fabricated via silicon epitaxy. Experimentally, it is shown that a deep X n (220 μm) compared with a shallow X n (300 μm) reduces the rise time by >5× . In addition, the magnitude of current density during interruption affects the prepulse foot and pulse shape. At lower current densities without the graded donor profile, high peak voltages are not achieved. Comparing the experimental results to the TCAD simulations shows that the model is predictive under high-current densities in the semiconductor opening switch (SOS) regime.

nanosecond pulse power↗
DOE OSTI2025

Intraspecific Diversity in Thermal Performance Determines Phytoplankton Ecological Niche

ABSTRACT Temperature has a primary influence on phytoplankton physiology and ecology. We grew 12 strains of Gephyrocapsa huxleyi isolated from different‐temperature regions for ~45 generations (2 months) and characterised acclimated thermal response curves across a temperature range. Even with similar temperature optima and overlapping cell size, strain growth rates varied between 0.45 and 1 day −1 . Thermal niche widths varied from 16.7°C to 24.8°C, suggesting that strains use distinct thermal response mechanisms. We investigated the implications of this thermal intraspecific diversity using an ocean ecosystem simulation resolving phytoplankton thermal phenotypes. Model analogues of thermal ‘generalists’ and ‘specialists’ resulted in a distinctive global biogeography of thermal niche widths with a nonlinear latitudinal pattern. We leveraged model output to predict ranges of the 12 lab‐reared strains and demonstrated how this approach could broadly refine geographic range predictions. Our combination of observations and modelled biogeography highlights the capacity of diverse groups to survive temperature shifts.

Krinos, Arianna I. [Department of Biology Woods Ho↗
DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗
DOE OSTI2025

Extending High-Level Synthesis with AI/ML Methods

Artificial Intelligence (AI) and Machine Learning (ML) methods provide significant opportunities of improving quality of results when performing high-level synthesis (HLS). For example, they can be used to model and predict metrics of the final design (e.g., area, considering aspects such as interconnect overhead for different device technologies), facilitating exploration when searching for the best design trade-offs. They can also enable identifying hidden correlations across the various phases of the synthesis and the various optimizations performed, identifying the most effective pipelines. Finally, in more general terms, bio-inspired heuristic algorithms can improve the design space exploration for the synthesis process in terms of time and quality of the result. This paper discusses opportunities and challenges to augment HLS with AI/ML using as example flow the SODA Synthesizer, an open-source hardware generation toolchain which includes SODA-OPT, a hardware/software partitioning and pre-optimization tool developed with the MLIR framework, and PandA-Bambu, a state-of-the art HLS tool. SODA interfaces with OpenROAD to provide a complete end-to-end toolchain.

artificial intelligence↗
DOE OSTI2025

Nitrogen limitation causes a seismic shift in redox state and phosphorylation of proteins implicated in carbon flux and lipidome remodeling in Rhodotorula toruloides

Background: Oleaginous yeast are prodigious producers of oleochemicals, offering alternative and secure sources for applications in foodstuff, skincare, biofuels, and bioplastics. Nitrogen starvation is the primary strategy used to induce oil accumulation in oleaginous yeast as part of a global stress response. While research has demonstrated that post-translational modifications (PTMs), including phosphorylation and protein cysteine thiol oxidation (redox PTMs), are involved in signaling pathways that regulate stress responses in metazoa and algae, their role in oleaginous yeast remain understudied and unexplored. Results: Towards linking the yeast oleaginous phenotype to protein function, we integrated lipidomics, redox proteomics, and phosphoproteomics to investigate Rhodotorula toruloides under nitrogen-rich and starved conditions over time. Our lipidomics results unearthed interactions involving sphingolipids and cardiolipins with ER stress and mitophagy. Our redox and phosphoproteomics data highlighted the roles of the AMPK, TOR, and calcium signaling pathways in regulation of lipogenesis, autophagy, and oxidative stress response. As a first, we also demonstrated that lipogenic enzymes including fatty acid synthase are modified as a consequence of shifts in cellular redox states due to nutrient availability. Conclusions: We conclude that lipid accumulation is largely a consequence of carbon rerouting and autophagy governed by changes to PTMs, and not increases in the abundance of enzymes involved in central carbon metabolism and fatty acid biosynthesis. Our systems-level approach sets the stage for acquiring multidimensional data sets for protein structural modeling and predicting the functional relevance of PTMs using Artificial Intelligence/Machine Learning (AI/ML). Coupled to those bioinformatics approaches, the putative PTM switches that we delineate will enable advanced metabolic engineering strategies to decouple lipid accumulation from nitrogen limitation.

Lipid Signalling↗
DOE OSTI2026

The two radiative states of the Arctic atmosphere and their impacts on the surface energy budget of sea ice

The surface energy budget (SEB) is a central regulator of Arctic climate and sea ice evolution, yet its processes remain poorly constrained due to sparse observations and complex, coupled surface-atmosphere interactions. This study leverages year-long measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) to provide the most comprehensive assessment to date of the central Arctic SEB and its modulation by atmospheric variability. Ship- and ice-based observations from October 2019 to September 2020 were used to directly measure or tightly constrain each term of the SEB, leading to exceptional energetic closure with the seasonal snow and ice mass balance. The analysis reveals strong seasonal transitions in atmosphere-surface energy transfer that are modulated by the atmospheric state and constrained by the ability of the surface temperature to respond. Classification of the atmosphere into its two dominant radiative states—the semi-transparent (ST) and opaque (OP)—highlights the central role of synoptic-scale variability in clouds. The ST atmospheric state dominated the long winter ice growth season, with limited cloudiness supporting persistent surface radiative cooling and ice growth. The OP state, associated with liquid-containing or thick ice clouds, became dominant in spring, with the combination of increased solar heating and cloud surface longwave warming driving ice and snow melt. Eddy covariance versus bulk approaches for deriving surface turbulent heat fluxes provide vastly different perspectives on the role of turbulence in modulating the SEB. These results establish a high-quality benchmark dataset for Arctic SEB studies and demonstrate how the balance of atmospheric radiative states exerts a first-order control on the annual evolution of the sea ice. The findings have broad implications for advancing observing technologies, understanding Arctic amplification, improving climate models, and predicting future sea ice change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

1970 Home Interview Survey

This study was conducted by Twin Cities Metropolitan Council—Saint Paul, and the database was used to develop mathematical models to predict future regional travel patterns and ultimately develop appropriate regional transportation policies, plans, and programs. The surveys in 1970 did not specifically include walking or bicycling as options in the travel diary; instead, these trips are included in a broad “other” category.

1Hz data↗
DOE OSTI2026

1970 Home Interview Survey

The 1970 Home Interview Survey was conducted by Twin Cities Metropolitan Council, Saint Paul. This database was used to develop mathematical models to predict future regional travel patterns, which were used to develop appropriate regional transportation policies, plans, and programs. The 1970 survey did not specifically include walking or bicycling as options in the travel diary; instead, these trips are included in a broad “other” category.

1Hz data↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2025

Literature Review Investigating Historical Plutonium Solubility in SRS Tank Waste

The Savannah River Site (SRS) has designed the Accelerated Basin De-inventory (ABD) program to accelerate the de-inventory of L-Basin and accelerate the Spent Nuclear Fuel (SNF) disposition mission. Similarly, the H-Canyon facility at SRS is reestablishing the 6.3D electrolytic dissolver for dissolving unirradiated stainless-steel (SS) clad Fast Critical Assembly (FCA) fuel. In both discard types (ABD and FCA), plutonium is present and its complex solubility when composited to Concentration, Storage, and Transfer Facility (CSTF) sludge is being investigated as it may have downstream impacts to the liquid waste (LW) organization. This literature review aims to highlight and compile the existing literature on plutonium solubility in waste streams relevant to ABD and FCA discards, as well as discuss some considerations in analyzing solubility data of plutonium. This review serves to help define the analysis methods for future experiments involving plutonium (and other actinides) and in designing appropriate testing conditions surrounding these studies. This review is broken up into five parts and will discuss: (i) The possible effects of testing hold time and temperature on plutonium solubility, (ii) the influence of neutralization rate and particle size of freshly precipitated discards, (iii) the coprecipitation of plutonium with iron and uranium, (iv) predictive solubility modeling and the influence of supernate anions on solubility, and (v) the speciation of plutonium in solutionas a result of supernate anions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Development of a Two-Dimensional CASTLE Transmission-Line Model for all Levels of Saturn

This report describes a two-dimensional model of Saturn based on the CASTLE transmission line code. Building on previous modeling efforts, 2D circuit models based on the “chain-link fence” geometry are constructed for pre-ReCap Saturn and post-ReCap Saturn. The 2D model results are in better agreement with data from Shot 4550 measurements of load currents and doses then the previous 1D model. Lower doses (9%) predicted by the new model can be compensated by increasing the load A-K gap.

43 PARTICLE ACCELERATORS↗