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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis

We analyze the robustness of the DESI 2024 cosmological inference from the full shape of the galaxy power spectrum to uncertainties in the Halo Occupation Distribution (HOD) model of the galaxy-halo connection and the choice of priors on nuisance parameters. We assess variations in the recovered cosmological parameters across a range of mocks populated with different HOD models and find that shifts are often greater than 20% of the expected statistical uncertainties from the DESI data. We encapsulate the effect of such shifts in terms of a systematic covariance term, C HOD , and an additional diagonal contribution quantifying the impact of our choice of nuisance parameter priors on the ability of the effective field theory (EFT) model to correctly recover the cosmological parameters of the simulations. These two covariance contributions are designed to be added to the usual covariance term, C stat , describing the statistical uncertainty in the power spectrum measurement, in order to fairly represent these sources of systematic uncertainty. This novel approach should be more general and robust to the choice of model or additional external datasets used in cosmological fits than the alternative approach of adding systematic uncertainties to the recovered marginalised parameter posteriors. We compare the approaches within the context of a fixed ΛCDM model and demonstrate that our method gives conservative estimates of the systematic uncertainty that nevertheless have little impact on the final posteriors obtained from DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

WETO Software Stack Best Practices

Wind energy researchers typically share one key characteristic: a passion for increasing wind energy in the global energy mix. The U.S. Department of Energy (DOE) supports this mission in a number of ways including allocating funding directly to various aspects of wind energy research through the Office of Energy Efficiency and Renewable Energy (EERE) via the Wind Energy Technologies Office (WETO). While the traditional output of research is academic publication, software development efforts are increasingly a major focus. Software tools in the research environment allow researchers to describe an idea and quickly increase the scope and scale as they study it further. As a product of research, these tools represent a direct pipeline from researcher to industry practitioners since they are the implementation of ideas described in academic publications. Given this vital role in wind energy research and commercial development, the broad research software portfolio supported by WETO must maintain a minimum level of quality to support the wind energy field in the growing transition to renewable energy. This report outlines a series o f best practices to be adopted by all WETO-supported software projects, as well as expectations that the communities interacting with these projects should have of the developers and tools themselves. Wind energy research software has a unique standing in the field of scientific software. The stakeholders are varied with a subset being: (1) DOE EERE leadership, (2) DOE WETO leadership and program managers, (3) National lab leadership, (4) Associated project principle investigators, (5) Research software engineers, (6) Wind energy researchers in academia (including graduate students, post docs, and national lab staff), (7) Industry researchers and practitioners, (8) Commercial software developers, and (9) The general public interested in wind energy. These software are typically the end-user of other generic software libraries, so the funding cycles are often tied to applied research rather than the development of the software itself. Since the developers are also wind energy researchers, these tools are typically designed in a way that closely resembles the application in which they're used. Additionally, the expertise and incentives for the developers have a high variability, and often neither are aligned with software engineering or computer science. Given the unique environment in which wind energy research software is produced and consumed, it is critical for model owners to understand the context of their software. A framework for developing this understanding is to answer the following questions of a given software project: What is it's purpose? What is its role in the field of wind energy? What is the profile of the expected users? For how long will it be relevant? What is the expected impact? These questions allow model owners to identify the appropriate methods for the design, development, and long term maintenance of their software. Additionally, the answer provide context for future planners to understand why particular decisions were made and discern the consequences of changing course. The information is aggregated from experience within WETO-supported software development groups as well as external organizations and efforts to define the craft of research software engineering. These best practices aim to make the collaborative development process efficient and effective while improving the model understanding across stakeholders. Additionally, the general adoption of a common framework for software quality ensures that the end users of WETO software can trust these tools and accurately understand the risks to workflow integration.

17 WIND ENERGY↗
DOE OSTI2025

Model-free Rayleigh weight from x-ray Thomson scattering measurements

X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the interpretation of the measured XRTS intensity usually relies on theoretical models and approximations. In this context, a key property is given by the Rayleigh weight that describes the electronic localization around the ions. Here, we show that it is possible to extract the Rayleigh weight directly from the experimental data without the need for any model calculations or simulations. As a practical application, we consider an experimental measurement of strongly compressed Be at the National Ignition Facility [Döppner et al., Nature 618, 270–275 (2023)]. We demonstrate that experimental results for the Rayleigh weight open up new avenues for the interpretation of XRTS experiments by matching the measurement with ab initio simulations such as density functional theory or path integral Monte Carlo. Interestingly, this new procedure leads to significantly lower density compared to previously used chemical models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Toward equitable environmental exposure modeling through convergence of data, open, and citizen sciences: an example of air pollution exposure modeling amidst increasing wildfire smoke

Exposure modeling is critical in environmental epidemiology and human health but may face challenges (e.g., skewed data, unequal error, context-insensitive validation, and computational demands). Modeling decisions reflect the intended use of the models and the values that modelers prioritize. We aimed to provide a conceptual framework and machine learning (ML) modeling protocols that address these issues. With 500m-gridded hourly PM 2.5 and O 3 levels in Illinois before, during, and after the 2023 Canadian wildfire season as a motivating example, we conducted modeling experiments to evaluate modeling methods, guided by three domains we propose based on theories of science: 1) Data Diversity, leveraging open and citizen science data to enhance inclusivity, parsimony, and representativeness; 2) Equitable Accuracy, ensuring fairly distributed uncertainties across subpopulations; and 3) Sustainable Modeling, balancing accuracy with reducing computational demands to promote accessibility for under-resourced researchers. Here, we found that ML with publicly available data can achieve high accuracy. Depending on methods, performance may vary substantially, even with identical input data. Large but skewed data may reduce performance. Misuse of cross-validation protocols can underestimate prediction error; although we observed R 2 s of ∼98 %, the modeled estimates varied significantly, indicating the need for careful model validation. By using new modeling protocols including representativeness-considered training and validation data and a new loss function, we achieved high agreement between estimates and ground-based measurements (e.g., R 2 = ∼90 % for PM 2.5 ; ∼80 % for O 3 ), equally distributed errors across sociodemographic strata and urban–rural divides, and reduction in computation time—from several weeks or months to a few days.

Exposure assessment↗
DOE OSTI2026

L-VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Symptom modelling in head and neck cancer is challenged by the complexity of heterogeneous patient data, leading to an interest in deep learning approaches. Although Long Short-Term Memory Networks (LSTMs) have shown great results in patient risk prediction, their low interpretability requires data modellers to collaborate with clinical experts to validate the results. We present L-VISP, a human–machine solution that uses visual analytics for LSTM modelling in clinical research. L-VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context. We evaluate L-VISP with data modellers and a clinical oncologist and present the takeaways from this multidisciplinary collaboration.

LSTM modeling↗
DOE OSTI2025

Mechanical cosmology: Simulating scalar fluctuations in expanding universes using synthetic mechanical lattices

Inspired by recent advances in observational astrophysics and continued explorations in the field of analog gravity, we discuss the prospect of simulating models of cosmology within the context of synthetic mechanical lattice experiments. We focus on the physics of expanding universe scenarios described by the Friedmann-Lemaître-Robertson-Walker (FLRW) metric. Specifically, quantizing scalar fluctuations in a background FLRW spacetime leads to a quadratic bosonic Hamiltonian with temporally varying pair production terms. Here we present a mapping that provides a one-to-one correspondence between these classes of cosmology models and feedback-coupled mechanical oscillators. As proof of principle, we then perform experiments on a synthetic mechanical lattice composed of such oscillators. We simulate two different FLRW expansion scenarios with universes dominated by vacuum energy and matter and discuss our experimental results. Published by the American Physical Society 2025

Rhyno, Brendan (ORCID:0000000235266998)↗
DOE OSTI2025

A New Framework for Interstellar Medium Emission Line Models: Connecting Multiscale Simulations across Cosmological Volumes

The James Webb Space Telescope (JWST) and Atacama Large Millimeter/submillimeter Array have detected emission lines from the ionized interstellar medium (ISM) in some of the first galaxies at z ≳ 6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context. In order to meet this challenge, we introduce a novel subgrid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from H II regions within each simulated FIRE galaxy are modeled using the semianalytic HIIL INES code. A machine learning approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the H II regions around each simulated stellar particle. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower-resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the IllustrisTNG simulations at z = 6. The resulting predictions for the [O II ], [O III ], and Balmer line luminosities as a function of star formation rate agree well with current observations. Our predictions differ, however, from related works in the literature, which lack detailed subgrid ISM models. This highlights the importance of our multiscale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys.

(ISM:) H II regions↗
DOE OSTI2024

Combination of searches for Higgs boson decays into a photon and a massless dark photon using pp collisions at $\sqrt{\textrm{s}}$ = 13 TeV with the ATLAS detector

A combination of searches for Higgs boson decays into a visible photon and a massless dark photon (H → γγd) is presented using 139 fb –1 of proton-proton collision data at a centre-of-mass energy of $\sqrt{\textrm{s}}$ = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider. The observed (expected) 95% confidence level upper limit on the Standard Model Higgs boson decay branching ratio is determined to be B(H → γγ d ) < 1.3% (1.5)%. The search is also sensitive to higher-mass Higgs bosons decaying into the same final state. The observed (expected) 95% confidence level limit on the cross-section times branching ratio ranges from 16 fb (20 fb) for m H = 400 GeV to 1.0 fb (1.5 fb) for m H = 3 TeV. Results are also interpreted in the context of a minimal simplified model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

t -channel dark matter models – a whitepaper

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t -channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t -channel dark matter models at colliders and in cosmology.

Arina, Chiara [Universite Catholique de Louvain, L↗
DOE OSTI2026

QCalEval: Benchmarking Vision-Language Models for Quantum Calibration Plot Understanding

Quantum computing calibration depends on interpreting experimental data, and calibration plots provide the most universal human-readable representation for this task, yet no systematic evaluation exists of how well vision-language models (VLMs) interpret them. We introduce QCalEval, the first VLM benchmark for quantum calibration plots: 243 samples across 87 scenario types from 22 experiment families, spanning superconducting qubits and neutral atoms, evaluated on six question types in both zero-shot and in-context learning settings. The best general-purpose zero-shot model reaches a mean score of 72.3, and many open-weight models degrade under multi-image in-context learning, whereas frontier closed models improve substantially. A supervised fine-tuning ablation at the 9-billion-parameter scale shows that SFT improves zero-shot performance but cannot close the multimodal in-context learning gap. As a reference case study, we release NVIDIA Ising Calibration 1, an open-weight model based on Qwen3.5-35B-A3B that reaches 74.7 zero-shot average score.

Cao, Shuxiang↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Superadditivity at large charge

The weak gravity conjecture has been invoked to conjecture that the dimensions of charged operators in a CFT should obey a superadditivity relation (sometimes referred to as convexity). In this paper, we study superadditivity of the operator spectrum in theories expanded about the semi-classical saddle point that dominates correlators of large charge operators. We explore this in two contexts. The first is a model with two scalar fields that carry different charges, at a non-trivial Wilson-Fisher fixed point. A careful analysis of the semi-classics for this two field model demonstrates that ‘quantum’ violations of superadditivity (those not forbidden by the conjecture) persist in the large charge regime. We then turn to study the general properties of CFTs at large charge as bottom-up EFTs. By a trial and error procedure we come up with a seemingly consistent family of examples violating the conjecture. In so doing the presence of a genuine dilaton field appears necessary. On the one hand our result demonstrates that the superadditivity conjecture cannot be proven purely on the basis of a bottom-up analysis. On the other hand, the need for a dilaton, with the corresponding infinite fine tuning, indicates the conjecture-violating EFTs are unlikely to be UV completable.

effective field theories↗
DOE OSTI2025

Chemical Interface Damping Revealed by Single-Particle Absorption Spectroscopy

Plasmon-induced interfacial charge separation is a promising way to efficiently extract energetic carriers through direct plasmon decay. This mechanism of charge transfer has been investigated by single-particle scattering spectroscopy, which measures the homogeneous plasmon line width. The line width is broadened by charge transfer, generally known as chemical interface damping. However, conflicting reports exist regarding the effect of chemical interface damping on the corresponding single-particle absorption spectrum, which is needed to accurately determine absolute light conversion efficiencies. This work aims to resolve this question by directly correlating absorption and scattering spectra of individual gold nanorods in the presence and absence of a charge-accepting interface. We find that for TiO 2 coated nanorods, the absorption line width is indeed broadened due to chemical interface damping but is overall narrower than the scattering line width. Here, chemical interface damping is furthermore found to increase with larger resonance energies. The observed differences in line widths between absorption and scattering are elucidated within the context of an analytically tractable model describing the lowest energy optically bright and higher-order optically dark plasmon modes of the nanorod, including bulk, radiative, and chemical interface damping effects. Taken together, these results establish that single-particle absorption spectroscopy is capable of revealing interfacial charge injection by direct plasmon decay.

absorption↗
DOE OSTI2024

Improving Aerosol Radiative Forcing and Climate in E3SM: Impacts of New Cloud Microphysics and Improved Wet Removal Treatments

Abstract Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m −2 , while the ZM_plus increases it by 0.27 W m −2 , resulting from excessive direct (0.31 W m −2 ) and indirect forcing (−1.79 W m −2 ). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m −2 ) and indirect aerosol forcing (−1.52 W m −2 ). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m −2 and −1.31 W m −2 , respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Axisymmetric hybrid Vlasov equilibria with applications to tokamak plasmas

We derive axisymmetric equilibrium equations in the context of the hybrid Vlasov model with kinetic ions and massless fluid electrons, assuming isothermal electrons and deformed Maxwellian distribution functions for the kinetic ions. The equilibrium system comprises a Grad–Shafranov partial differential equation and an integral equation. These equations can be utilized to calculate the equilibrium magnetic field and ion distribution function, respectively, for given particle density or given ion and electron toroidal current density profiles. The resulting solutions describe states characterized by toroidal plasma rotation and toroidal electric current density. Additionally, due to the presence of fluid electrons, these equilibria also exhibit a poloidal current density component. This is in contrast to the fully kinetic Vlasov model, where axisymmetric Jeans equilibria can only accommodate toroidal currents and flows, given the absence of a third integral of the microscopic motion.

Physics↗
DOE OSTI2024

Magnetic interactions and excitations in SrMnSb 2

The magnetic interactions in the antiferromagnetic (AFM) Dirac semimetal candidate SrMnSb 2 are investigated using ab initio linear response theory and inelastic neutron scattering (INS). Our calculations reveal that the first two nearest in-plane couplings (J 1 and J 2 ) are both AFM in nature, indicating a significant degree of spin frustration, which aligns with experimental observations. The orbital resolution of exchange interactions shows that J 1 and J 2 are dominated by direct and superexchange, respectively. In a broader context, a rigid-band model suggests that electron doping fills the minority spin channel and results in a decrease in the AFM coupling strength for both J 1 and J 2 . To better compare with INS measurements, we calculate the spin-wave spectra within a linear spin-wave theory, utilizing the computed exchange parameters. Although the calculated spin-wave spectra somewhat overestimate the magnon bandwidth, they exhibit overall good agreement with measurements from INS experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗
DOE OSTI2024

Reactive-transport modeling of fracture flow to quantify the changes in flow pathways from matrix thermal contraction and mineral precipitation and dissolution; influence of grid resolution

A series of reactive-transport models of Enhanced Geothermal Systems (EGS) were constructed using the reactive transport code PFLOTRAN to examine the effect of matrix thermal contraction and mineral dissolution/precipitation on fracture flow in the context of grid cell size and model complexity. It was found that for thermal drawdown at production well, the impact of fracture zone grid cell size is negligible.

Gatz-Miller, Hannah Sarah↗