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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Future grid mix impacts on whole-building life cycle assessment

Building construction and operation are a significant contribution to global greenhouse gas emissions, so understanding and mitigating emissions is crucial for reliable and realistic emissions accounting. Whole-building Life Cycle Assessment (WBLCA) is an emissions accounting method that considers lifetime environmental impacts of a building during its construction, operation, and eventual end-of-life. When performing WBLCAs, emission calculations from the building's operation over the entire building lifespan are typically based on today's energy grid mixes. This method does not consider changes or advancements in the clean energy proportion within the grid mix and can over or under-inflate results, skewing the ratio of embodied vs. operational environmental impacts. While a variety of prediction tools estimate what future grid emissions might be, predictions can vary widely. To predict the clean energy ratio within future grid mixes and the potential impact these changes might have on WBLCA, annual data from several existing U.S. grid models was averaged and probabilistic modeling was used to extend the usable projections of shorter forecasts. Results show that clean energy sources will likely continue to increase over time, although the rate of growth varies by model. On average, by 2085, the clean energy penetration of the grid is projected to reach ~81% and renewable energy is projected to reach ~71%, although no widespread consensus is reached. To understand how the future grid mix impacts lifetime building emissions within a WBLCA context, the team analyzed two 2021 IECC-compliant all-electric residential buildings: one built from traditional materials and construction processes and the other built with carbon sequestering materials and modular assembly, with a portion of energy generated on site. The results indicate that a moderate estimate of future electricity grid mixes shows a reduction of yearly operational emissions for traditional residential buildings of 55% between 2025 and 2085, and a corresponding reduction of 48% of total emissions over a 60 year building lifespan. This study offers a nuanced approach to account for the variability of future grid mix models and provides an average trend-line based on a robust collection of scenarios.

Life Cycle Assessment (LCA)↗
DOE OSTI2025

Techno-economic analysis of synthetic fuel production from existing nuclear power plants across the United States

Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.

Garrouste, Marisol (ORCID:0000000168388644)↗
DOE OSTI2026

Affleck-Dine curvaton

The Standard Model of particle physics does not explain the origin of the universe’s baryon asymmetry or its primordial fluctuations. The Affleck-Dine mechanism is a well motivated scenario for generating the baryon asymmetry through the postinflationary dynamics of a complex scalar field with baryon number. The curvaton mechanism is a popular approach for producing curvature perturbations through the dynamics of a light spectator field that decays after inflation. We demonstrate that the same complex field can viably perform both roles without any modifications to the minimal realization of Affleck-Dine baryogenesis. This scenario can also accommodate appreciable levels of primordial non-Gaussianity, beyond those achievable with only a real-valued curvaton field, and may be observable with future cosmic microwave background experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Observable CMB B -modes from cosmological phase transitions

A B -mode polarization signal in the cosmic microwave background (CMB) is widely regarded as smoking gun evidence for gravitational waves produced during inflation. Here, we demonstrate that tensor perturbations sourced during noninflationary epochs can yield non-negligible B -mode signals, which can in principle complicate the interpretation of future observational data. As a case study, we consider tensor perturbations sourced in the bubble collision stage of a first-order cosmological phase transition occurring in a secluded dark sector. Although phase transitions arise from causal subhorizon physics, they nevertheless exhibit a white noise power spectrum on superhorizon scales. Power is suppressed on the large scales relevant for CMB B -mode polarization, but it is not necessarily negligible. We show that for appropriately chosen phase transition parameters, the maximal B -mode amplitude can compete with inflationary predictions that can be tested with current and future experiments. These scenarios can be differentiated by performing measurements on multiple angular scales, since the phase transition signal predicts peak power on smaller scales.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Detecting dark matter substructures on small scales with fast radio bursts

The matter power spectrum is only weakly constrained on subgalactic scales, while physics beyond the Standard Model can leave unique imprints, especially on sub-parsec scales. We propose measuring the arrival-time difference of fast radio bursts (FRBs) along two adjacent sightlines as a new probe to dark matter substructures on scales down to ∼ 1 AU . We discuss two observational scenarios in which it may be possible to place interesting constraints on such models through the monitoring of repeating FRB sources: (i) By sending radio receivers to space to form a baseline of tens of AU or more and measuring the temporal variation of the arrival-time difference between receivers. (ii) By measuring the temporal variation of the arrival-time difference between two lensed images of one strongly lensed repeater. In both scenarios, obtaining interesting constraints requires correlating the voltage time series to measure the radio signal arrival time to sub-nanosecond precision. We find that two radio dishes separated by 20 AU may be sensitive to the enhancement of small-scale structures at ∼ 10 - 8 M ⊙ masses in the QCD axion dark matter scenario, or from an early epoch of matter domination with a reheating temperature up to 60 MeV. Other dark matter models, such as those composed of ∼ 10 - 13 M ⊙ primordial black holes produced during inflation, would also be probed by this method. We further show that a strong lensing situation of multiple images provides an equivalent ∼ 2000 AU ( σ v / 10 3 km s - 1 ) ( δ t / 10 yr ) baseline, for a typical velocity of dark matter substructures σ v and an observational time span δ . This is much more sensitive, but with the uncertainty that intervening decoherence from the interstellar medium may degrade the timing precision, and that spatial variation in the FRB emission spot may result in confounding signals. We show that the lensing magnifications of Type Ia supernovae constrain a similar quantity to such FRB timing, with present limits being equivalent to ruling out the same parameter space that would be probed by a 0.14 AU baseline.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Constraints on dark matter from dynamical heating of stars in ultrafaint dwarfs. II. Substructure and the primordial power spectrum

There is a large and growing interest in observations of small-scale structure in dark matter. We propose a new way to probe dark matter structures in the ∼ 10 – 10 8 M ⊙ range. This allows us to constrain the primordial power spectrum over shorter distances scales than possible with direct observations from the CMB. For k in the range ∼ 10 – 1000 Mpc − 1 our constraints on the power spectrum are orders of magnitude stronger than previous bounds. We also set some of the strongest constraints on dark matter isocurvature perturbations. Our method relies on the heating effect such dark matter substructures would have on the distribution of stars in an ultrafaint dwarf galaxy. Many models of inflation produce enhanced power at these short distance scales and can thus be constrained by our observation. Further, many dark matter models such as axion dark matter, self-interacting dark matter and dissipative dark matter, produce dense structures which could be constrained this way. Published by the American Physical Society 2024

Graham, Peter W. (ORCID:0000000216001601)↗
DOE OSTI2024

Coulomb confinement in the Hamiltonian limit

The Gribov-Zwanziger scenario attributes the phenomenon of confinement to the instantaneous interaction term in the QCD Hamiltonian in the Coulomb gauge. For a static quark-antiquark pair, it leads to a potential energy that increases linearly with the distance between them. Lattice studies of the SU(2) Yang-Mills theory determined the corresponding (Coulomb) string tension for sources in the fundamental representation, 𝜎 𝐶 , to be about 3 times larger than the Wilson loop string tension, 𝜎 𝐹 . It is far above the Zwanziger variational bound, 𝜎 𝐶 ≥ 𝜎 𝐹 . We argue that the value often reported in the literature is artificially inflated. We examine the lattice definition of the instantaneous potential, find the source of the string tension’s enhancement, and perform its improved determination in SU(2) lattice gauge theory. We report our conservative estimate for the value of the Coulomb string tension as 𝜎 𝐶 /𝜎 𝐹 = 2.0 ± 0.4 and discuss its phenomenological implications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Systematic study of projection biases in the weak lensing analysis of cosmic shear and the combination of galaxy clustering and galaxy-galaxy lensing

This paper presents the results of a systematic study of projection biases in the weak lensing analysis of cosmic shear and the combination of galaxy clustering and galaxy-galaxy lensing using data collected during the first year of running the Dark Energy Survey experiment. The study uses Lambda cold dark matter ( Λ CDM ) as the cosmological model and two-point correlation functions for the weak lensing (WL) analysis. The results in this paper show that, independent of the WL analysis, projection biases of more than 1 σ exist and are a function of the position of the true values of the parameters h , n s , Ω b , and Ω ν h 2 with respect to their prior probabilities. For cosmic shear, and the combination of galaxy clustering and galaxy-galaxy lensing, this study shows that the coverage probability of the 68.27% credible intervals ranges from as high as 93% to as low as 16% and that these credible intervals are inflated, on average, by 29% for cosmic shear and 20% for the combination of galaxy clustering and galaxy-galaxy lensing. The results of the study also show that, in six out of nine tested cases, the reduction in error bars obtained by transforming credible intervals into confidence intervals is equivalent to an increase in the amount of data by a factor of 3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Warm and fuzzy dark matter: Free streaming of wave dark matter

Wave or fuzzy dark matter that is produced with relativistic wave numbers exhibits free-streaming effects analogous to warm or hot particle dark matter with relativistic momenta. Axions produced after inflation provide such a warm or mildly relativistic candidate, where the enhanced suppression and observational bounds are only moderately stronger than that from wave propagation of initially cold axions. More generally, the free-streaming damping also impacts isocurvature fluctuations from generation in causally disconnected patches. As coherent spatial fluctuations free stream away they leave incoherent and transient superpositions in their wakes. These multiple wave momentum streams are the wave analog of particle phase space fluctuations or directional collisionless damping of massive neutrinos or hot dark matter. The observable impact on both adiabatic and isocurvature fluctuations of fuzzy dark matter can differ from their cold dark matter counterparts due to free streaming depending on how warm or hot is their momentum distribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Refining localtype primordial non-Gaussianity: Sharpened bϕ constraints through bias expansion

Local-type primordial non-Gaussianity (PNG), predicted by many nonminimal models of inflation, creates a scale-dependent contribution to the power spectrum of large-scale structure tracers. Its amplitude is characterized by the product bϕfNLloc, where bϕ is an astrophysical parameter dependent on the properties of the tracer. However, bϕ exhibits significant secondary dependence on halo concentration and other astrophysical properties, which may bias and weaken the constraints on fNLloc. In this work, we demonstrate that incorporating knowledge of the relation between Lagrangian bias parameters and bϕ can significantly enhance PNG constraints. We employ the hybrid effective field theory approach at the field level and a linear regression model to seek a connection between the bias parameters and bϕ for halo and galaxy samples, constructed using the abacussummit simulation suite and mimicking the luminous red galaxies and quasistellar objects of the Dark Energy Spectroscopic Instrument survey. For the fixed-mass halo samples, our full bias model reduces the uncertainty by more than 70%, with most of that improvement coming from b∇, which we find to be an excellent proxy for concentration. For the galaxy samples, our model reduces the uncertainty on bϕ by 80% for all tracers. By adopting Lagrangian-bias informed priors on the parameter bϕ, future analyses can thus constrain fNLloc with less bias and smaller errors.

Hadzhiyska, Boryana↗
DOE OSTI2024

Simulated structure and thermodynamics of decagonal Al-Co-Cu quasicrystals

Atomic structures of Al-Co-Cu decagonal quasicrystals (dQCs) are investigated using empirical oscillating pair potentials (EOPP) in molecular dynamic (MD) simulations that we enhance by Monte Carlo (MC) swapping of chemical species and replica exchange. Predicted structures exhibit planar decagonal tiling patterns and are periodic along the perpendicular direction. We then recalculate the energies of promising structures using first-principles density functional theory (DFT), along with energies of competing phases. We find that our τ -inflated sequence of QC approximants (QCAs) are energetically unstable at low temperature by at least 3 meV/atom. Extending our study to finite temperatures by calculating harmonic vibrational entropy, as well as anharmonic contributions that include chemical species swaps and tile flips, our results suggest that the quasicrystal phase is entropically stabilized at temperatures in the range 600-800 K and above. It decomposes into ordinary (though complex) crystal phases at low temperatures, including a partially disordered B2-type phase. We discuss the influence of density and composition on QC phase stability; we compare the structural differences between Co-rich and Cu-rich quasicrystals; and we analyze the role of entropy in stabilizing the quasicrystal, concluding with a discussion of the possible existence of “high entropy” quasicrystals. Published by the American Physical Society 2024

Huang, Yang (ORCID:0009000045917347)↗
DOE OSTI2025

Fluctuations in Hill’s equation parameters and application to cosmic reheating

Cosmic inflation provides a compelling framework for explaining several observed features of our Universe, but its viability depends on an efficient reheating phase that converts the inflaton’s energy into Standard Model particles. This conversion often proceeds through nonperturbative mechanisms such as parametric resonance, which is described by Hill’s equation. In this work, we investigate how stochastic fluctuations in the parameters of Hill’s equation can influence particle production during reheating. We show that such fluctuations can arise from couplings to light scalar fields and can significantly alter the stability bands in the resonance structure, thereby enhancing the growth of fluctuations and broadening the region of efficient energy transfer. Using random matrix theory and stochastic differential equations, we decompose the particle growth rate into deterministic and noise-induced components and demonstrate analytically and numerically that even modest noise leads to substantial particle production in otherwise stable regimes. Furthermore, these results suggest that stochastic effects can robustly enhance the efficacy of reheating across a wide swath of parameter space, with implications for early Universe cosmology, UV completions involving multiple scalar fields, and the resolution of the cosmological moduli problem.

Cosmology↗
DOE OSTI2026

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2026

The Impact of Time-Aware Design Choices in ICS Anomaly Detection

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and na¨ıve imputation— prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensordecomposition– based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States

Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.

greenhouse gas emissions↗
DOE OSTI2025

Cold freeze out of superheavy dark matter and Hubble tension

We present a unified framework, the "X miracle", in which dark matter consists of superheavy, nonthermal X particles whose relic abundance is determined not by the conventional weak-scale, semi-relativistic ("hot") freeze-out of WIMPs, but by annihilation or decay occurring within the smallest and earliest gravitationally bound objects. Unlike thermal WIMPs, which decouple at velocities of order 0.3c with relic abundance ρ∞ set by weak-scale interactions, X particles are produced nonthermally with an initial overabun dance ρ ini >> ρ ∞ . They become nonrelativistic extremely early, redshift to ultra-cold velocities, allowing collapse into compact bound structures characterized by a novel quantum gravitational scale, r X = 4$\hbar$ 2 $/Gm^3_X$ = 10 −13 m $\hbar$$/m_Xc$, much larger than the Compton wavelength. The framework predicts a particle mass of 10 12 GeV and an enhanced cross section of 10 −21 m 3 /s. Overlapping particle wavefunctions in these compact structures drive annihilation or decay into additional radiation, leading to a "cold" freeze-out that converts most of ρ ini into radiation while leaving a relic density ρ ∞ . Solutions to the Boltzmann equation indicate that an extreme ("big") depletion, with only one particle in a billion surviving, yields an additional radiation contribution $ΔN_{eff}$ ≈ 0.4, which could help alleviate the Hubble tension. For particles of 10 12 GeV, the scenario predicts a dark coupling constant α X = 0.09 that is responsible for an instanton-induced decay process, consistent with current UHECR bounds. Early collapse at 10 −6 s may release binding energy as high-frequency (100kHz) gravitational waves or ultralight GUT-scale axions (10 −9 eV). Superheavy sterile neutrinos provide a natural particle realization, linking dark matter to neutrino mass and baryogenesis. If gravitationally produced, this framework favors high-scale inflation and effi cient reheating. The "X miracle" thus demonstrates that dark matter need not be weak-scale: gravitational dynamics can control freeze-out and evolution, producing multi-messenger observational signatures in UHECRs, axions, gravitational waves, and small-scale structures.

Xu, Zhijie Jay [Pacific Northwest National Laborat↗