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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 1,153 records · Page 64

The Hunt for High-Tc Superconductivity: from Discovery to Breakthrough [Slides]

Summary/Outlook: BCS pairing theory of superconductivity is a prototypical example of a condensed matter physics problem. It has inspired the Weinberg Salam model for Electroweak interactions; So far there is no quantitative theory of superconductivity in strongly correlated materials. The limits on Tc are still unknown; Almost all known superconducting materials were found without theoretical guidance; The next-generation of first-principles approaches is beginning to captures a more holistic picture of correlated materials, giving way to a more quantitative theory of materials.

36 MATERIALS SCIENCE↗

Interpretable Net Load Forecasting Using Smooth Multiperiodic Features

We consider the problem of forecasting net load over a horizon such as one day, using a trailing window of past net load values as well as date and time. We focus on three variations on this problem: point forecasts, marginal quantile forecasts, and generating conditional samples of the future value. We propose a method that relies on linear regression using some custom engineered time-based features to capture multiple periodicities, such as daily, weekly, and seasonal, and their interactions. Our proposed models are readily interpretable, and rely on efficient and reliable convex optimization [1] to fit. We illustrate our method on four years worth of hourly net load data, comparing predictions made with various subsets of the features.

Ogut, Mehmet G↗

From Silos to Synergy: Identifying a Roadmap for Cross-Sector Research to Accelerate the Clean Energy Transition

The U.S. Department of Energy's blueprints for the transportation, buildings, and electricity sectors call for substantial reductions in greenhouse gas (GHG) emissions by 2050. These plans focus on zero-emission vehicles, investments in transit, energy-efficient buildings, and the widespread adoption and deployment of renewable energy technologies like solar photovoltaics (PV), energy storage and energy-efficient appliances. However, these sectors are often studied and modeled in isolation, overlooking how household decisions to adopt clean technologies in one sector influence others. This study, led by an interdisciplinary team at the National Renewable Energy Laboratory (NREL), explores opportunities for cross-sector collaboration to drive more effective and equitable decarbonization. Through discussions with 22 NREL researchers across transportation, building, solar, and grid sectors, the study highlights the need for integrated tools and models that capture interactions between these sectors. Key insights include the need for data standardization and interoperability to enable cross-sector analysis and decision-making. Strengthening utility partnerships is also critical to align energy policies with decarbonization goals and manage the increased demand for renewable energy. The study also emphasizes the importance of equity in the clean energy transition, calling for targeted incentives and support to ensure that low-income and underserved communities benefit from clean technologies like electric vehicles and energy-efficient appliances. To support these efforts, innovative funding mechanisms must be expanded to facilitate interdisciplinary research, such as city-specific decarbonization plans and federal projects like DOE"s Standard Scenarios. By encouraging collaboration and integrating cross-sector insights, this study aims to provide a roadmap to accelerate the clean energy transition and ensure it is both sustainable and inclusive.

14 SOLAR ENERGY↗

Geant4 HEP Examples

Geant4 is a widely used simulation toolkit in high-energy physics (HEP), enabling precise modeling of particle interactions with matter. It plays a crucial role in the development and optimization of detector concepts for future HEP programs. With a structured set of examples ranging from basic to advanced, Geant4 provides a comprehensive set of concrete examples for users at different expertise levels. As a critical tool for the HEP community, Geant4 continues to evolve, adapting to emerging computational paradigms and experimental requirements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Emergent Behaviors and the Limits of Large Language Model Generalization

Over the past couple years, large language models (LLMs) have rapidly grown in size and performance across wide numbers of tasks, leading some to herald them as machine learning models with truly “general” capabilities. We address some of the ways that the language used to describe these models can be both deceptive and a poor framing for making progress towards understanding their capabilities, and also review arguments on to what extent these models can represent and interact with the meaning of language. Emergent behaviors in these highly complex models are unpredictable and research into understanding them is still in early phases, which limits the strength of claims of generality about them. Moreover, while these models demonstrate surprising emergent reasoning capabilities on many tasks, there are still many limitations in generalization that overall high benchmark performance can hide. We review the literature showcasing limitations of LLMs as well as techniques to mitigate or overcome these challenges, while also highlighting how fundamental problems in model evaluation may prevent true claims of generality. We conclude with a practical section on using LLMs on real world problems while appropriately evaluating and validating these tasks to prevent or mitigate the downstream impacts of incorrect results.

97 MATHEMATICS AND COMPUTING↗

Search for numu Disappearance in the Short-Baseline Neutrino Program Utilizing an Exclusive 1mu1p QE-Like Final State

The Short-Baseline Neutrino (SBN) program at Fermilab is searching for neutrino oscillations over a short baseline as a signature of a sterile neutrino with a mass splitting of about 1eV2. Such oscillations would drive the disappearance of muon neutrinos in the Booster Neutrino Beam between the detectors of the SBN Program. We present progress on an analysis to search for muon neutrino disappearance between the SBND and ICARUS detectors (the SBN Program's near and far detectors, respectively). This analysis leverages the one muon, one proton, quasi-elastic-like final state, which provides the best resolution for reconstructing the neutrino energy. The analysis incorporates a comprehensive set of systematic uncertainties in the neutrino flux, interaction, and detector model. This analysis will soon be completed as part of the first oscillation results at SBN.

Rowe, Nathaniel [U. Chicago (main)]↗

The DUNE Near Detector

DUNE is a next-generation experiment aiming to provide precision measurements of neutrino oscillation parameters. It will detect neutrinos produced in the Long-Baseline Neutrino Facility beamline at Fermilab, using a Near Detector situated near the beam target where the neutrinos originate and a Far Detector located 1300 km away in South Dakota. A comparison of the spectra of neutrinos measured at the Far and the Near Detector will allow for the extraction of oscillation probabilities from which the oscillation parameters can be inferred. The specific role of the Near Detector is to serve as the experiment’s control: it will establish the no oscillation null hypothesis, measure and monitor the beam, constrain systematic uncertainties, and provide essential measurements of the neutrino interactions to improve models. The Near Detector complex will include three primary detector components: a liquid argon time projection chamber, a high-pressure gas time projection chamber and an on-axis beam monitor. The three detectors will serve important individual and overlapping functions, with two of them being also able to move transverse to the beam’s axis via the DUNE-PRISM program. The overall mission of the Near Detector, as well as the three sub-detectors’ unique capabilities and physics programs will be discussed in these proceedings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Biotic countermeasures that rescue Nannochloropsis gaditana from a Bacillus safensis infection

The natural assemblage of a symbiotic bacterial microbiome (bacteriome) with microalgae in marine ecosystems is now being investigated as a means to increase algal productivity for industry. When algae are grown in open pond settings, biological contamination causes an estimated 30% loss of the algal crop. Therefore, new crop protection strategies that do not disrupt the native algal bacteriome are needed to produce reliable, high-yield algal biomass. Bacteriophages offer an unexplored solution to treat bacterial pathogenicity in algal cultures because they can eliminate a single species without affecting the bacteriome. To address this, we identified a highly virulent pathogen of the microalga Nannochloropsis gaditana, the bacterium Bacillus safensis, and demonstrated rescue of the microalgae from the pathogen using phage. 16S rRNA amplicon sequencing showed that phage treatment did not alter the composition of the bacteriome. It is widely suspected that the algal bacteriome could play a protective role against bacterial pathogens. To test this, we compared the susceptibility of a bacteriome-attenuated N. gaditana culture challenged with B. safensis to a N. gaditana culture carrying a growth-promoting bacteriome. We showed that the loss of the bacteriome increased the susceptibility of N. gaditana to the pathogen. Transplanting the microalgal bacteriome to the bacteriome-attenuated culture reconstituted the protective effect of the bacteriome. Finally, the success of phage treatment was dependent on the presence of beneficial bacteriome. This study introduces two synergistic countermeasures against bacterial pathogenicity in algal cultures and a tractable model for studying interactions between microalgae, phages, pathogens, and the algae microbiome.

60 APPLIED LIFE SCIENCES↗

Quantitative Modeling of High-Energy Electron Scattering in Thick Samples Using Monte Carlo Techniques

Cryo-electron microscopy (cryo-EM) is a powerful tool for imaging biological samples but is typically limited by sample thickness, which is restricted to a few hundred nanometers depending on the electron energy. However, there is a growing need for imaging techniques capable of studying biological samples up to 10 µm in thickness while maintaining nanoscale resolution. This need motivates the use of mega-electron-volt scanning transmission electron microscopy (MeV-STEM), which leverages the high penetration power of MeV electrons to generate high-resolution images of thicker samples. In this study, we employ Monte Carlo simulations to model electron–sample interactions and explore the signal decay of imaging electrons through thick specimens. By incorporating material properties, interaction cross-sections for energy loss, and experimental parameters, we investigate the relationship between the incident and transmitted beam intensities. Key factors such as detector collection angle, convergence semi-angle, and the material properties of samples were analyzed. Our results demonstrate that the relationship between incident and transmitted beam intensities follows the Beer–Lambert law over thicknesses ranging from a few microns to several tens of microns, depending on material composition, electron energy, and collection angles. The linear depth of silicon dioxide reaches 3.9 µm at 3 MeV, about 6 times higher than that at 300 keV. Meanwhile, the linear depth of amorphous ice reaches 17.9 µm at 3 MeV, approximately 11.5 times higher than that at 300 keV. These findings are crucial for advancing the study of thick biological and semiconductor samples using MeV-STEM.

36 MATERIALS SCIENCE↗

Architecture for Co-Simulation of Transportation and Distribution Systems with Electric Vehicle Charging at Scale in the San Francisco Bay Area

This work describes the Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI) architecture for the co-simulation of distribution and transportation systems to evaluate EV charging impacts on electric distribution systems of a large metropolitan area and the surrounding rural regions with high fidelity. The current co-simulation is applied to Oakland and Alameda, California, and in future work will be extended to the full San Francisco Bay Area. It uses the HELICS co-simulation framework to enable parallel instances of vetted grid and transportation software programs to interact at every model timestep, allowing high-fidelity simulations at a large scale. This enables not only the impacts of electrified transportation systems across a larger interconnected collection of distribution feeders to be evaluated, but also the feedbacks between the two systems, such as through control systems, to be captured and compared. The findings are that with moderate passenger EV adoption rates, inverter controls combined with some distribution system hardware upgrades can maintain grid voltages within ANSI C.84 range A limits of 0.95 to 1.05 p.u. without smart charging. However, EV charging control may be required for higher levels of charging or to reduce grid upgrades, and this will be explored in future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Structure of Odd-A Ag Isotopes Studied via Algebraic Approaches

The structure of the odd-A silver isotopes Ag 103–115 is discussed within the frame of the interacting boson–fermion model (IBFM). An overview of their key properties is presented, with a particular attention paid to the “ J -1 anomaly”, represented by an abnormal ordering of the lowest 7/2 + and 9/2 + states. By examining previously published data and newly performed calculations, it is demonstrated that the experimentally known level schemes and electromagnetic properties of Ag 103–115 can be reproduced well within IBFM-1 by using a consistent set of model parameters. The contribution of different single-particle orbitals to the structure of the lowest-lying excited nuclear states in Ag 103–115 is discussed. Given that the J-1 anomaly brings down the 7/2 + level from the j −3 multiplet to energies, which can be thermally populated in hot stellar environments, the importance of low-lying excited states in odd-A silver isotopes for astrophysical processes is outlined.

IBFM-1↗

The Early History of the Quark-Gluon Plasma

We present the historical antecedents to the field of relativistic heavy ion physics, beginning with early attempts to model the strong interaction and ending with the endorsement of a relativistic heavy ion collider in the 1983 U.S. Long-Range Plan for Nuclear Science. Particular attention is paid to two major themes: 1) A program to study high density states of nuclear matter emerging from the 1974 Bear Mountain conference and 2) Efforts to understand the predictions of QCD for matter at high densities and/or temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Search for Accelerator-Produced Sub-GeV Dark Matter with the NOvA Near Detector

The NuMI facility at Fermilab produces a high-intensity beam of muon neutrinos and antineutrinos, designed to study neutrino oscillations. This beam may also be a source of dark matter particles produced through a light mediator. We search for dark matter particles with masses between 1 and 200 MeV that interact with Standard Model particles via a vector portal, producing forward-scattered single-electron events in the NOvA near detector. We set limits on the dark-visible coupling based on an exposure of 2.55x10^21 protons of 120 GeV energy on the NuMI target. For the dark matter mass range 10-20 MeV, this analysis sets the tightest constraints on the coupling to date.

Abubakar, S. [Erciyes U.] (ORCID:0000000315112219)↗

Serving in the Public Interest: Samuel Insull and the Public Service Utility Imaginary

This chapter examines the rhetoric of Samuel Insull as an example of how early electricity utility executives framed the idea of granting monopoly territories in terms of the “public interest.” While the public interest has not always maintained sustained attention in public policy research, the concept remains as strong as ever a justification for specific policies and procedures that shape how utilities deliver energy to the public. Insull’s public speeches and other events demonstrate an important instantiation of the coproduction of an energy transition and the reimagining of how the public and energy companies interact. Though this model is by no means perfect, it represents an idea of sociotechnical order that has sustained for over a century, a level of persistent change that is instructive for considering how to shape the ongoing transition to sustainable energy systems.

Tidwell, Abraham SD↗

Confinement transition to gravitational waves in the one-flavor $SU(4)$ Hyper Stealth Dark Matter theory

The thermodynamics of the $SU(4)$ gauge theory with a single flavor of fundamental quarks is analyzed on the lattice with dynamical fermion simulations, which is the low-energy sector of a realistic, strongly-interacting dark matter model -- the Hyper Stealth Dark Matter. The gravitational wave spectrum from the first-order confinement transition in the early universe is further calculated, where the effect of the dark sea quarks, which decrease the interface tension in the effective potential of the Polyakov loop, is shown numerically to lower the gravitational wave amplitude.

Ayyar, V. [Boston U.]↗

A Physics-Informed Reinforcement Learning Framework for Economic-Thermal Co-Optimization of Crypto Mining Data Centers: Preprint

The rapid expansion of cryptocurrency mining has created a new class of high-density data centers characterized by extreme thermal flux and high sensitivity to volatile economic markets. Traditional thermal management strategies, typically reliant on rule-based control, maintain static setpoints that fail to account for fluctuating electricity prices and cryptocurrency values - factors critical to mining profitability. To address this, we present a physics-informed reinforcement learning (PIRL) framework for economic-thermal co-optimization in crypto mining data centers. This framework consists of a proximal policy optimization (PPO) agent, a virtual testbed powered by high-fidelity physics-based models, and an interactive frontend dashboard. The PPO agent is trained using the virtual testbed and strict hardware safety limits. This physics-informed approach allows the agent to learn a stochastic policy that dynamically balances mining revenue against operational costs by co-optimizing HVAC cooling setpoints and IT computational hashrate. The simulation results demonstrate that the integrated framework achieved an 8.62% increase in net operational profit compared to traditional baseline strategies while strictly adhering to safety-critical temperature constraints (coolant supply temperature < 32 degrees C). This work provides a scalable template for the deployment of reinforcement learning in mission critical facilities where economic volatility and physical safety must be managed simultaneously.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

JAX-CanVeg: A Differentiable Land Surface Model

Land surface models consider the exchange of water, energy, and carbon along the soil-canopy-atmosphere continuum, which is challenging to model due to their complex interdependency and associated challenges in representing and parameterizing them. Differentiable modeling provides a new opportunity to capture these complex interactions by seamlessly hybridizing process-based models with deep neural networks (DNNs), benefiting both worlds, that is, the physical interpretation of process-based models and the learning power of DNNs. Here, we developed a differentiable land model, JAX-CanVeg. The new model builds on the legacy CanVeg by incorporating advanced functionalities through JAX in the graphic processing unit support, automatic differentiation, and integration with DNNs. We demonstrated JAX-CanVeg's hybrid modeling capability by applying the model at four flux tower sites with varying aridity. To this end, we developed a hybrid version of the Ball-Berry equation that emulates the water stress impact on stomatal closure to explore the capability of the hybrid model in (a) improving the simulations of latent heat fluxes (LE) and net ecosystem exchange (NEE), (b) improving the optimization trade-off when learning observations of both LE and NEE, and (c) benefiting a multi-layer canopy model setup. Our results show that the proposed hybrid model improved the simulations of LE and NEE at all sites, with an improved optimization trade-off over the process-based model. Additionally, the multi-layer canopy set benefited hybrid modeling at some sites. Anchored in differentiable modeling, our study provides a new avenue for modeling land-atmosphere interactions by leveraging the benefits of both data-driven learning and process-based modeling.

54 ENVIRONMENTAL SCIENCES↗

Freeze-in dark matter from secret neutrino interactions

We investigate a simplified freeze-in dark-matter model in which the dark matter only interacts with the standard-model neutrinos via a light scalar. The extremely small coupling for the freeze-in mechanism is naturally realized in several neutrino-portal scenarios with the secret neutrino interactions. We study possible evolution history of the hidden sector: the dark sector would undergo pure freeze-in production if the interactions between the dark-sector particles are negligible, while thermal equilibrium within the dark sector could occur if the reannihilation of the dark matter and the scalar mediator is rapid enough. We investigate the relic abundance in the freeze-in and dark freeze-out regimes, calculate evolution of the dark temperature, and study its phenomenological aspects on BBN and CMB constraints, the indirect-detection signature, as well as the potential to solve the small scale structure problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗