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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Grad-Shafranov model for compact quasisymmetric stellarators

A Grad-Shafranov equation (GSE) valid for compact quasisymmetric stellarators is derived by an asymptotic expansion around a vacuum field carried to first order. We obtain an equation for the existence of flux surfaces leading up to the GSE. The flux surface label must simultaneously satisfy the existence equation and the GSE, which generally leads to an overdetermined problem. We show how the overdetermined problem can be resolved within our model for a class of hybrid devices similar to that studied by Henneberg and Plunk [Phys. Rev. Res. 6, L022052 (2024)]. We are also able to solve the existence equation for flux surfaces analytically in the most general case by introducing a special coordinate system. This will enable us to carry out an optimization seeking to minimize the error in our GSE while obeying the flux surface existence equation, which will allow us to find solutions outside the class of hybrid devices. This will allow for a coarse-grained approximate search in the space of quasisymmetric equilibria that should be faster than a conventional stellarator optimization. Nevertheless, it would still be necessary to fine-tune the approximate solutions using conventional tools to obtain a more precise optimized equilibrium.

Nikulsin, N. (ORCID:0000000318611777)↗
DOE OSTI2026

Symmetry-protected topological polarons

Emergent quasiparticles in solids often exhibit unique topological properties as a result of the complex interplay between charge, orbital, spin, and lattice degrees of freedom. Among these quasiparticles, the polaron occupies a special place as the first known manifestation of the interaction between a fermion and a boson field. While polarons have been investigated for almost a century, whether these quasiparticles exhibit topological properties and why remain open questions. Here, we establish the universal symmetry principles governing the topology of polar textures in large polarons. Using a group-theoretic analysis, we identify four distinct classes of polar textures in time-reversal-invariant systems, and we show that they carry integer topological charges. We validate this classification by performing state-of-the-art first-principles calculations of materials representative of each class. For these materials, we compute the fingerprints of polaron topology in Huang diffuse scattering and propose ultrafast electron and X-ray scattering experiments to detect these quasiparticles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗
DOE OSTI2025

The Untold Story of Building the First Megaton Thermonuclear Fusion Device: The Simple Element and IVY Mike

This report is a research and development engineer’s perspective on the fascinating story of the world’s first megaton-class thermonuclear device, IVY Mike (10.4 Mt). Few modern scientific endeavors have matched the complexity and breadth of scientific achievement in such a short amount of time as IVY Mike. This paper will take a look at the design, engineering, fielding, and execution of the world’s first megaton-class physics experiment by Los Alamos Scientific Laboratory and the birth of industrial liquid hydrogen use spawned by the Cold War effort. Although others have written on aspects of this technical history, they have not benefited from access to the original classified documents used by the present author. The present paper must necessarily omit some technical details that remain classified but represents the most comprehensive summary of the engineering and fabrication of the IVY Mike device in the open literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Open-source simulation platform for air source heat pump integrated with thermal energy storage

Here, this article introduces a modular simulation platform for assessing thermal energy storage (TES) integrated with air source heat pumps (ASHP). The Python platform is an open-source library that includes classes for modeling air-air and air-water heat pumps, TES devices, and the heating load of residential buildings. To validate the ASHP model, the study utilized experimental data obtained from a commercial heat pump evaluated at the National Renewable Energy Laboratory (NREL). The results indicate a mean deviation of 0.7% for COP across the operating range, with a maximum relative deviation of 12.6%. In terms of system heating capacity, the model had an average deviation of 4.3% compared to experimental results, with a maximum deviation of 8.2%. Three classes were implemented for modeling distinct types of TES devices: a generic TES based on energy balances, a sensible isothermal water tank, and a stratified water tank. Details of the mathematical models are provided, along with their respective strengths and limitations. An example is provided showcasing the integration of a residential 10 kWh thermal storage unit with an ASHP operating in Denver, CO. The comparison of two different discharge criteria for the TES unit highlights the importance of control strategies in the system performance.

25 ENERGY STORAGE↗
DOE OSTI2024

Pulsar timing anomalies: a window into baryon number violation

Here, we investigate the influence of a specific class of slow Baryon Number Violation (BNV)—one that induces quasi-equilibrium evolution — on pulsar spin characteristics. This work reveals how BNV can potentially alter observable parameters, including spin-down rates, the second derivative of spin frequency, and braking indices of pulsars. Moreover, we demonstrate that BNV could lead to anomalies in pulsar timing, along with a wide array of braking indices, both positive and negative. In addition, we examine the possibility of pulsar spin-up due to BNV, which may result in a novel mechanism for the revival of “dead” pulsars. We conclude by assessing the sensitivity required for future pulsar timing efforts to detect such BNV effects, thus highlighting the potential for pulsars to serve as laboratories for testing fundamental physics.

cosmology↗
DOE OSTI2025

Optimal parameterizations for observational constraints on thawing dark energy

Time-varying dark energy is often modeled in observational analyses through generic parameterizations of its equation of state w(z), which typically use two free parameters {w 0 , w a } to span a broad range of behaviors as a function of redshift. However, this broad range of behaviors can only approximately capture the dynamics of any given microphysical theory of dark energy. A complementary approach is to use targeted parameterizations designed to model specific classes of dynamical dark energy with greater precision. Focusing on the class of thawing dark energy, we quantify and compare the precision with which nineteen generic and targeted parameterizations can capture the dynamics of physically motivated thawing quintessence theories. We find that a targeted parameterization derived from a Padé expansion of w is the most reliable of these, producing accurate reconstructions of w(z), the expansion history H(z), and cosmological parameters such as H 0 and Ω m for a broad range of microphysical theories.

dark energy experiments↗
DOE OSTI2024

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗
DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Novel candidate taxa contribute to key metabolic processes in Fennoscandian Shield deep groundwaters

The continental deep biosphere contains a vast reservoir of microorganisms, although a large proportion of its diversity remains both uncultured and undescribed. In this study, the metabolic potential (metagenomes) and activity (metatranscriptomes) of the microbial communities in Fennoscandian Shield deep subsurface groundwaters were characterized with a focus on novel taxa. DNA sequencing generated 1270 de-replicated metagenome-assembled genomes and single-amplified genomes, containing 7 novel classes, 34 orders, and 72 families. The majority of novel taxa were affiliated with Patescibacteria, whereas among novel archaea taxa, Thermoproteota and Nanoarchaeota representatives dominated. Metatranscriptomes revealed that 30 of the 112 novel taxa at the class, order, and family levels were active in at least one investigated groundwater sample, implying that novel taxa represent a partially active but hitherto uncharacterized deep biosphere component. The novel taxa genomes coded for carbon fixation predominantly via the Wood–Ljungdahl pathway, nitrogen fixation, sulfur plus hydrogen oxidation, and fermentative pathways, including acetogenesis. These metabolic processes contributed significantly to the total community’s capacity, with up to 9.9% of fermentation, 6.4% of the Wood–Ljungdahl pathway, 6.8% of sulfur plus 8.6% of hydrogen oxidation, and energy conservation via nitrate (4.4%) and sulfate (6.0%) reduction. Key novel taxa included the UBA9089 phylum, with representatives having a prominent role in carbon fixation, nitrate and sulfate reduction, and organic and inorganic electron donor oxidation. These data provided insights into deep biosphere microbial diversity and their contribution to nutrient and energy cycling in this ecosystem.

Candidatus↗
DOE OSTI2025

Year six photometric measurements of known Trans-Neptunian Objects and Centaurs by the Dark Energy Survey

ABSTRACT We identified known Trans-Neptunian Objects (TNOs) and Centaurs in the complete Dark Energy Survey (DES) year six catalogue (DES Y6) through the Sky Body Tracker (SkyBoT) tool. We classified our data set of 144 objects into a widely used 4-class taxonomic system of TNOs. No such previous classification was available in the literature for most of these objects. From absolute magnitudes and average albedos, an estimation of the diameters of all these objects is obtained. Correlations involving colours, orbital parameters, dynamical classes, and sizes are also discussed. In particular, our largest reddest object has a diameter of $390^{+68}_{-53}$ km and our largest cold classical, $255^{+19}_{-17}$ km. Also, a weak correlation between colour and inclination is found within the population of resonant TNOs in addition to weak correlations between colour and phase slope in different bands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Anyonic Membranes and Pontryagin Statistics

Anyons, unique to two spatial dimensions, underlie extraordinary phenomena such as the fractional quantum Hall effect, but their generalization to higher dimensions has remained elusive. The topology of Eilenberg-MacLane spaces constrains the loop statistics to be only bosonic or fermionic in any dimension. In this work, we introduce the novel anyonic statistics for membrane excitations in four dimensions. Analogous to the $\mathbb{Z}_N$-particle exhibiting $\mathbb{Z}_{N\times \gcd(2,N)}$ anyonic statistics in two dimensions, we show that the $\mathbb{Z}_N$-membrane possesses $\mathbb{Z}_{N\times \gcd(3,N)}$ anyonic statistics in four dimensions. Given unitary volume operators that create membrane excitations on the boundary, we propose an explicit 56-step unitary sequence that detects the membrane statistics. We further analyze the boundary theory of $(5{+}1)$D 1-form $\mathbb{Z}_N$ symmetry-protected topological phases and demonstrate that their domain walls realize all possible anyonic membrane statistics. We then show that the $\mathbb{Z}_3$ subgroup persists in all higher dimensions. In addition to the standard fermionic $\mathbb{Z}_2$ membrane statistics arising from Stiefel-Whitney classes, membranes also exhibit $\mathbb{Z}_3$ statistics associated with Pontryagin classes. We explicitly verify that the 56-step process detects the nontrivial $\mathbb{Z}_3$ statistics in 5, 6, and 7 spatial dimensions. Furthermore, in 7 and higher dimensions, the statistics of membrane excitations stabilize to $\mathbb{Z}_{2} \times \mathbb{Z}_{3}$, with the $\mathbb{Z}_3$ sector consistently captured by this process.

Abstract algebra↗
DOE OSTI2025

Incorporating Physical Priors into Weakly Supervised Anomaly Detection

We propose a new machine-learning-based anomaly detection strategy for comparing data with a background-only reference (a form of weak supervision). The sensitivity of previous strategies degrades significantly when the signal is too rare or there are many unhelpful features. Our prior-assisted weak supervision (PAWS) method incorporates information from a class of signal models to significantly enhance the search sensitivity of weakly supervised approaches. As long as the true signal is in the prespecified class, PAWS matches the sensitivity of a dedicated, fully supervised method without specifying the exact parameters ahead of time. On the benchmark LHC Olympics anomaly detection dataset, our mix of semisupervised and weakly supervised learning is able to extend the sensitivity over previous methods by a factor of 10 in cross section. Furthermore, if we add irrelevant (noise) dimensions to the inputs, classical methods degrade by another factor of 10 in cross section while PAWS remains insensitive to noise. This new approach could be applied in a number of scenarios and pushes the frontier of sensitivity between completely model-agnostic approaches and fully model-specific searches.

artificial neural networks↗
DOE OSTI2025

Charge-induced atomic strain as a predictor of structural phase transformation in rare-earth intermetallics

We present a descriptor based on charge-induced atomic strain in crystalline lattices for predicting structural phase transformations in rare-earth intermetallic compounds containing lanthanides and transition metals. The charge-induced local atomic strain was obtained from structural optimization of experimentally known crystalline phases using state of the art density-functional theory methods. The predictive power of the descriptor was evaluated on 𝑅⁢𝐸 2 ⁢In (𝑅𝐸 = rare earth) compounds, a class known for diverse phase transformations. We show that incorporating quantum-mechanical effects—such as local charge distribution, bonding, symmetry, and electronic structure—enhances the robustness of the descriptor. To gain further insight, we analyzed phononic and electronic behavior in Y 2 ⁢In and demonstrated that experimental phase transformations are captured only when atomic strain effects are included. The descriptor was further used to predict structural phase changes in (Y⁢b 1–𝑥 ⁢E⁢r 𝑥 ) 2 ⁢In and G⁡d 2 ⁡(I⁢n 1–𝑥⁢ A⁢l 𝑥 ), with predictions confirmed by x-ray powder diffraction. Here, while the current study is focused on lanthanide-based intermetallics, the underlying principles of the descriptor suggest potential applicability to other closely related classes of rare-earth intermetallics.

Density functional theory↗
DOE OSTI2026

Nonequilibrium universality of the nonreciprocally coupled 𝑂⁡(𝑛 1 ) × 𝑂⁡(𝑛 2 ) model

Nonequilibrium dynamics play an important role in all contexts of physics, both classical and quantum as well as living and nonliving, so it is crucial to develop a foundational understanding of nonequilibrium phase transitions. In this work we investigate an important class of nonequilibrium dynamics in the form of nonreciprocal interactions. In particular we study how nonreciprocal coupling between two 𝑂⁡(𝑛𝑖) order parameters (with 𝑖 = 1,2) affects the universality at a multicritical point, extending the analysis of J. T. Young et al. [Phys. Rev. X 10, 011039 (2020)], which considered the case 𝑛 1 = 𝑛 2 = 1, i.e., a ℤ 2 × ℤ 2 model. We show that nonequilibrium fixed points (NEFPs) emerge for a broad range of 𝑛 1 ,𝑛 2 and exhibit intrinsically nonequilibrium critical phenomena, namely a violation of fluctuation-dissipation relations at all scales and underdamped oscillations near criticality in contrast to the overdamped relaxational dynamics of the corresponding equilibrium models. Furthermore, the NEFPs exhibit an emergent discrete scale invariance in certain physically relevant regimes of 𝑛 1 ,𝑛 2 , but not others, depending on whether the critical exponent 𝜈 is real or complex. The boundary between these two regions is described by an exceptional point in the renormalization group (RG) flow, leading to distinctive features in correlation functions and the phase diagram. Another contrast with the previous work is the number and stability of the NEFPs as well as the underlying topology of the RG flow. Lastly, we investigate an extreme form of nonreciprocity where one order parameter is independent of the other order parameter but not vice versa. Unlike the ℤ 2 × ℤ 2 model, which becomes nonperturbative in this case, we identify a distinct nonequilibrium universality class whose dependent field similarly violates fluctuation-dissipation relations but does not exhibit discrete scale invariance or underdamped oscillations near criticality.

Critical phenomena↗
DOE OSTI2026

Primordial black hole dark matter: A quantitative parameter sensitivity comparison across formation mechanisms and particle candidates

Primordial black holes (PBHs) in the asteroid-mass window ( 10 17 – 10 22 g ) can account for all of the dark matter without violating any observational constraint, yet are routinely dismissed as fine-tuned. I put that dismissal to the test by applying three complementary sensitivity measures uniformly across a broad landscape: three noninflationary PBH production mechanisms, six classes of inflationary PBH models, and seven particle dark matter benchmarks, all evaluated against the same observable target. Three distinct naturalness universality classes emerge, determined entirely by the analytic structure of the abundance map rather than by the nature of the dark matter candidate. Biased-domain-wall PBHs, in their least model-dependent (free- V b ) form, have the same low sensitivity, Δ = 4.5 , as off-resonance weakly interacting massive particles and freeze-in particles ( Δ = 2 ), a sensitivity that, because it is constant over the entire parameter space of the construction, also coincides trivially with its own Wilson-normalized average within that parameter space (Section Definition and conventions), an equivalence that concerns only the space over which Δ is computed and is not a naturalness statement about the construction as a whole; a further reduction to Δ = 2 is possible only under the additional, independently motivated but not required, assumption that the domain-wall bias is generated by Planck-suppressed operators; early matter-domination PBHs occupy an intermediate tier alongside coannihilating weakly interacting massive particles (WIMPs), unified by a structural identity in which the sensitivity measure equals the logarithm of the ratio of the formation scale to the matter–radiation equality scale; first-order phase transition PBHs, once the more accurate super-exponential collapse probability is used in place of the single-exponential approximation, instead belong to the same highly sensitive tier as resonant WIMP annihilation and single-field inflationary collapse, for a structurally distinct reason; single-field ultraslow-roll inflationary collapse is severely tuned for a distinct reason: a double exponential in which the power spectrum amplitude is itself exponentially sensitive to the inflaton potential coefficients, on top of the exponential collapse sensitivity of the abundance map. My main conclusion is that the claim that PBH dark matter is generically fine-tuned conflates the worst case with a landscape spanning every naturalness tier. The Barbieri-Giudice sensitivity computed here and the Wilson-normalized measure of Iovino and Riotto answer distinct and mutually consistent questions about the same construction, a distinction I clarify within the two-layer decomposition.

Profumo, Stefano [University of California, Santa ↗
DOE OSTI2025

Coarsening dynamics of Ising-nematic order in a frustrated Heisenberg antiferromagnet

We study the phase ordering dynamics of the classical antiferromagnetic 𝐽 1 −𝐽 2 (nearest-neighbor and next-nearest-neighbor couplings) Heisenberg model on the square lattice in the strong frustration regime (𝐽 2 /𝐽 1 > 1/2). While thermal fluctuations preclude any long-range magnetic order at finite temperatures, the system exhibits a long-range spin-driven nematic phase at low temperatures. The transition into the nematic phase is further shown to belong to the two-dimensional Ising universality class based on the critical exponents near the phase transition. Our large-scale stochastic Landau-Lifshitz-Gilbert simulations find a two-stage phase ordering when the system is quenched from a high-temperature paramagnetic state into the nematic phase. In the early stage, collinear alignments of spins lead to a locally saturated Ising-nematic order. Once domains of well-defined Ising order are developed, the late-stage relaxation is dominated by curvature-driven domain coarsening, as described by the Allen-Cahn equation. The characteristic size of Ising-nematic domains scales as the square root of time, similar to the kinetic Ising model described by the time-dependent Ginzburg-Landau theory. Our results confirm that the late-stage ordering kinetics of the spin-driven nematic, which is a vestigial order of the frustrated Heisenberg model, belongs to the dynamical universality class of a nonconserved Ising order. Interestingly, the system shows no violation of the superuniversality hypothesis under weak bond disorder. The dynamic scaling invariance is preserved in the presence of weak bond disorder. Here, we also discuss possible applications of our results to materials for which vestigial Ising-nematic order is realized.

Antiferromagnets↗
DOE OSTI2025

Weak localization as a probe of intervalley coherence in graphene multilayers

Spontaneous intervalley coherence is suspected in several different graphene multilayer systems, but is difficult to confirm because of a paucity of convenient experimental signatures. Here we suggest that magneto-conductance features associated with quantum corrections to Drude conductivity can serve as a smoking gun for intervalley coherence that does not break time-reversal symmetry. In this class of ordered multilayer quantum transport corrections can produce weak localization or weak antilocalization, depending on whether the valley order belongs to the orthogonal or symplectic symmetry class. Our analysis motivates low-temperature weak-field magnetoresistance measurements in graphene multilayers in which time-reversal invariant intervalley coherent order is conjectured.

36 MATERIALS SCIENCE↗