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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 19 records

Dark Matter Constraints from Small-Scale Cosmic Structure

Small-scale cosmic structure provides a powerful test of the fundamental nature of dark matter (DM). A wide range of DM models impact matter clustering on small scales, including warm, fuzzy, and (self-)interacting DM. In these scenarios, DM physics such as free-streaming, wave interference, and self/Standard Model interactions alter the abundance and internal structure of DM halos. Cosmological and astrophysical probes of nonlinear structure---including dwarf galaxies, strong lensing, the Lyman-$α$ forest, stellar streams, and high-redshift galaxies---are therefore sensitive to these effects. Here, we review DM constraints provided by small-scale structure, focusing on observables that probe scales smaller than $\sim 1~\mathrm{Mpc}$, which define the frontier of current measurements. We summarize how these constraints have been translated to limits on microphysical DM models, and we discuss key modeling uncertainties and observational systematics. Finally, we highlight the growing importance of probe combination and simulation-based inference for this field, and we overview upcoming observational facilities that will sharpen small-scale structure tests of DM physics.

Nadler, Ethan O. [UC, San Diego] (ORCID:0000000211↗

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗

Fast event-based electron counting for small-molecule structure determination by MicroED

Electron counting helped realize the resolution revolution in single-particle cryoEM and is now accelerating the determination of MicroED structures. Its advantages are best demonstrated by new direct electron detectors capable of fast (kilohertz) event-based electron counting (EBEC). This strategy minimizes the inaccuracies introduced by coincidence loss (CL) and promises rapid determination of accurate structures. We used the Direct Electron Apollo camera to leverage EBEC technology for MicroED data collection. Given its ability to count single electrons, the Apollo collects high-quality MicroED data from organic small-molecule crystals illuminated with incident electron beam flux densities as low as 0.01–0.045 e − /Å 2 /s. Under even the lowest flux density (0.01 e − /Å 2 /s) condition, fast EBEC data produced ab initio structures of a salen ligand (268 Da) and biotin (244 Da). Each structure was determined from a 100° wedge of data collected from a single crystal in as few as 50 s, with a delivered fluence of only ∼0.5 e − /Å 2 . Fast EBEC data collected with a fluence of 2.25 or 3.33 e − /Å 2 also facilitated a 1.5 Å structure of thiostrepton (1665 Da). While refinement of these structures appeared unaffected by CL, a CL adjustment applied to EBEC data further improved the distribution of intensities measured from the salen ligand and biotin crystals. However, CL adjustment only marginally improved the refinement of their corresponding structures, signaling the already high counting accuracy of detectors with counting rates in the kilohertz range. Overall, by delivering low-dose structure-worthy data, fast EBEC collection strategies open new possibilities for high-throughput MicroED.

EBEC↗

Small-x structure of oxygen and neon isotopes as seen by the Large Hadron Collider

Results on collisions of O-16 nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. O-16+O-16 collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3+1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on O-16+O-16 and Ne-20+Ne-20 collisions at root s(NN) = 70 GeV and 7 TeV. The choice of Ne-20 is motivated by its strongly elongated geometry, which may respond differently to the effect of the high-energy evolution compared to the more spherical O-16. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Multi-component Dark Matter and small scale structure formation

We consider the evolution of non-thermal dark matter perturbations in models which contain both Weakly Interacting Massive Particles (WIMPs) and axions. Using constraints from existing observations we examine the percentage of WIMPs and axions that may comprise the cosmological dark matter budget in models with an Early Matter Dominated Epoch (EMDE) — where entropy production is important. After carefully tracking the thermal evolution of the various species by solving the Boltzmann equations, we consider the enhancement of perturbations that may have led to early structure formation for axions and WIMPs. We investigate the impact of enhanced perturbations on the parameter space of both species, after imposing existing constraints from indirect detection experiments. Given these constraints we establish the feasibility of axions to form miniclusters in the early universe in EMDEs for a given percentage of allowed WIMPs. We find that EMDEs with low reheat temperatures near the BBN limit are preferred for axion minicluster formation. When the EMDE is caused by string moduli, the WIMP contribution to the relic density is set by the moduli branching to dark matter at the level of ≲ $\mathcal{O}$ (10 −4 ).

79 ASTRONOMY AND ASTROPHYSICS↗

Selective deuteration of an RNA:RNA complex for structural analysis using small-angle scattering

The structures of RNA:RNA complexes regulate many biological processes. Despite their importance, protein-free RNA:RNA complexes represent a tiny fraction of experimentally determined structures. Here, we describe a joint small-angle X-ray and neutron scattering (SAXS/SANS) approach to structurally interrogate conformational changes in a model RNA:RNA complex. Using SAXS, we measured the solution structures of the individual RNAs and of the overall RNA:RNA complex. With SANS, we demonstrate, as a proof of principle, that isotope labeling and contrast matching (CM) can be combined to probe the bound state structure of an RNA within a selectively deuterated RNA:RNA complex. Furthermore, we show that experimental scattering data can validate and improve predicted AlphaFold 3 RNA:RNA complex structures to reflect its solution structure. In conclusion, our work demonstrates that in silico modeling, SAXS, and CM-SANS can be used in concert to directly analyze conformational changes within RNAs when in complex, enhancing our understanding of RNA structure in functional assemblies.

HIV-1 dimerization initiation site↗

Aerodynamic and production comparison of wind farms with downwind versus conventional upwind turbines

Ever-increasing turbine scales and their associated logistical challenges have reignited questions about the performance of downwind rotor configurations. A particular potential benefit of downwind rotor configurations is the farm-scale power increase that may be conferred by tilt-driven downward wake entrainment and associated wake recovery. In this work, a comprehensive aerodynamic analysis is carried out to understand the mechanisms for wake entrainment and recovery across a spectrum of velocity and inflow alignment conditions on a small, structured farm in order to understand the impact of downwind rotors on farm production. The results show that the benefits demonstrated previously in the literature for downwind-rotor farms in aligned flows are fragile, and, outside of strong farm/flow alignment conditions, power production benefits for small farms with downwind rotor configurations are significantly if not completely mitigated by misalignment effects. The work indicates that farm-scale benefits for downwind rotors must be realized either from large-scale entrainment benefits, with more exotic farm arrangements that can take advantage of the aerodynamic effects, or from beneficial fatigue impacts from entrainment of less turbulent outer boundary layer flows.

17 WIND ENERGY↗

The Structure-Properties Relationship of Alternative Bismaleimide Variants for Candidacy for Additive Manufacturing

Modernizing the manufacturing of high-performance polymer foams such as amino-poly(oxadiazole) bismaleimide (APO-BMI), a bismaleimide resin with superior thermal and compressive strength that incorporates additive manufacturing (AM) techniques, is crucial for its applications, but the parameters for AM can be challenging based on the physical properties of the associated monomer. For our applications, selective laser sintering (SLS) is typically used. SLS is a 3D printing technique that allows for complex shapes and geometries without structural supports while also providing high resolution material. However, printing thermosets like APO-BMI with SLS is challenging due to the complex melting and curing considerations required when selecting parameters. Additionally, the temperature difference between melting and curing of APO-BMI is over a hundred º C, which makes selecting a sintering window especially difficult. This work explores structural modifications of APO-BMI that may be more amenable for selective laser sintering. The effects of how different structural changes such as substitution pattern, heteroatom identity in the bridge, and bridge length affect the thermal properties of the material were also compared. All APO variants were found to have a smaller temperature window between the melting and curing peaks based on differential scanning calorimetry (DSC) which is advantageous for SLS. Small structural changes significantly altered the melting and curing properties of APO. Additionally, DSC revealed significant polymorphisms in APO-BMI and other APO variants which could be attributed to differences in thermal history and would need to be considered when adapting for SLS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-monotonic size-dependent exciton radiative lifetime in CsPbBr3 nanocrystals

Lead halide perovskite nanocrystals have attracted intense interest due to their desirable optical properties, diverse structural features, and size-tunable excitonic structure. Here we show that, under ambient conditions, a non-monotonic trend in radiative lifetime emerges from the interplay of size, lattice symmetry and excitonic structure. Small nanocrystals exhibit long radiative lifetimes due to weakly emissive excitons, but the oscillator strength increases and shortens the lifetime for nanocrystals approaching intermediate confinement. For larger nanocrystals with higher exciton density of states (DOS), the radiative lifetime is lengthened due to depopulation of the bright exciton manifold into thermally accessible dim states. A size-dependent structural symmetry lowering transition from cubic to orthorhombic is observed by XRD and MD simulations, and the non-monotonic radiative lifetime trend emerges only in lower symmetry structures with an increased dim exciton DOS. These findings shed light on the impact of nanocrystal size and structure on radiative lifetime and pave the way for tailored optical materials in various optical applications.

optical materials↗

Mechanism of DNA origami folding elucidated by mesoscopic simulations

Abstract Many experimental and computational efforts have sought to understand DNA origami folding, but the time and length scales of this process pose significant challenges. Here, we present a mesoscopic model that uses a switchable force field to capture the behavior of single- and double-stranded DNA motifs and transitions between them, allowing us to simulate the folding of DNA origami up to several kilobases in size. Brownian dynamics simulations of small structures reveal a hierarchical folding process involving zipping into a partially folded precursor followed by crystallization into the final structure. We elucidate the effects of various design choices on folding order and kinetics. Larger structures are found to exhibit heterogeneous staple incorporation kinetics and frequent trapping in metastable states, as opposed to more accessible structures which exhibit first-order kinetics and virtually defect-free folding. This model opens an avenue to better understand and design DNA nanostructures for improved yield and folding performance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Experimental determination of the magnetic anisotropy in five-coordinated Co( II ) field-induced single molecule magnets

Magnetic anisotropy of the central metal atom is a crucial property of single molecule magnets (SMMs). Small structural changes can alter the magnetic properties, and accurate experimental methods to investigate magnetic anisotropy are therefore critical. Here, we investigate two five-coordinated Co( II ) SMMs, [CoCl 2 Cltpy] (1) and [CoBr 2 Cltpy] (2) (Cltpy = 4′-chloro-2,2′:6′,2′′-terpyridine), through multiple techniques. Ab initio theoretical calculations performed on the two compounds show that both possess axial magnetic anisotropy with the magnetic easy axis pointing towards one of the terminal halogen atoms. Theoretical calculations on SMMs are typically done on isolated molecular species, and to validate this approximation the magnetic anisotropy was further studied through experimental techniques. EPR measurements confirm an axial anisotropy of 1, and magnetic measurements provide experimental Zero-Field Splitting (ZFS) parameters, showing that the values from theoretical calculations are slightly overestimated. The X-ray electron density determined from 20 K single-crystal synchrotron X-ray diffraction data provides estimated d-orbital populations also suggesting axial magnetic anisotropy in both systems, and furthermore suggesting a more pronounced axiality in 1 compared to 2. This is in good agreement with the results obtained from both magnetic measurements and theoretical calculations. The magnetic anisotropy of 1 is quantified experimentally through polarized powder neutron diffraction via the site susceptibility method, confirming an axial magnetic anisotropy of the compound. A slight deviation in the easy axis direction is observed between experimental and theoretical results. This, together with the overestimation of the ZFS parameters from theoretical calculations, shows that experimental investigation of the magnetic anisotropy of SMMs is of high relevance. Magnetic anisotropy of the central metal atom is a crucial property of single molecule magnets (SMMs).

Slavensky, Hannah H. [Aarhus Univ. (Denmark)] (ORC↗

AmeriFlux US-GL2 Granite Island

This is the AmeriFlux version of the carbon flux data for the site US-GL2 Granite Island. Site Description - Granite Island is a small island on Lake Superior approximately 10 miles due north of Marquette, Michigan. It is roughly 6.5 miles from shore and is occupied by a lighthouse, bell tower, Coast Guard light tower, and other small structures. A flux tower to measure H, LE, and meteorological data was installed atop the bell tower in July of 2009 and has been in continuous operation since then (aside from occasional power outages or other sources of data loss). CO2 measurements were added to the flux tower in October of 2010.

Lenters, John [University of Michigan Biological S↗

Machine Learning Inference of Random Medium Properties

Earth materials are heterogeneous across a range of spatial scales, but the resolvability of small structures is limited by sparse data coverage, noise, bandlimitedness, and other difficulties. In practice, heterogeneities below a certain size cannot be recovered from seismic data except through statistical medium descriptions, which even then can be difficult to uniquely determine. To improve the characterization of such heterogeneities, we develop a novel supervised machine learning (ML) model that provides insight about the recoverability of statistical medium properties from elastic waveform data and succeeds despite cycle-skipping and other challenges well known from elastic waveform inversion. We demonstrate the approach using random media generated by superimposing self-affine random variations on homogeneous and layered background structures. After training on sparsely-recorded, high-frequency waveforms from hundreds of different random medium realizations, we show the ability of our ML model to recover correlation lengths and other statistical properties of interest to near-surface and crustal seismology, among other fields. For frequency passbands and spatial offsets encountered in seismology, Gaussian correlation lengths and the amplitude of the random variations relative to the background model are recovered even in challenging scenarios involving unknown medium parameters, complex crustal structures, and low signal-to-noise ratio. In comparison, von Kármán correlation lengths, which are related to larger-wavelength variations of the medium than Gaussian correlation lengths, are not as well recovered. These results provide one of the first and most systematic investigations of the recoverability of statistical properties of heterogeneities below the resolution limit of deterministic seismic tomography, and suggest practical ML strategies for high-frequency waveform seismology.

58 GEOSCIENCES↗

Modeling Flow and Particle Deposition in a Spent Nuclear Fuel Assembly

CFD (Computational Fluid Dynamic) simulation of aerosol-laden natural convective flow and particle deposition in a spent fuel storage canister with 37 assemblies is currently computationally prohibitive. PWR (Pressurized Water Reactor) assemblies have up to 289 pins or tubes with several spacer grids to align the pins. Spacer grids with mixing vanes induce swirling during operation to increase heat transfer. Each spacer grid contains hundreds of small structures such as retaining clips, channel walls, and openings. The largest canisters store 37 PWR assemblies thus, there are numerous pins, tubes, and spacer grids for which the flow region between and around these structures needs to be determined along with the movement and deposition of aerosol particles. Because of the complicated geometry, modeling the intricate flow even for just one assembly is currently impractical. Nonetheless, we are developing techniques for a practical model to assess the natural aerosol particle deposition process in a canister in the event that a release occurs from one or more fuel pins. In the previous work it was demonstrated that CFD can model the flow through a PWR spacer grid with mixing vanes, including particle deposition, in a reasonable amount of time on a personal computer. In this work, the analysis is extended to include the bypass region between an assembly and the canister basket walls. It is shown that the flow velocity in the bypass region is about three times that of the interstitial region between the pins. The lengths before and after the spacer grid are also extended to determine when the flow becomes fully developed. In addition, the approach of computationally “stitching together” segments of an assembly is demonstrated with the plan to ultimately model a full assembly. The fraction of particles that are deposited in a segment with a spacer grid is determined as a function of particle size and flow velocity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ab initio property predictions of quinary solid solutions using small binary cells

The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. Here in this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.

36 MATERIALS SCIENCE↗

Symmetric-asymmetric collision comparison: Disentangling nuclear structure and subnucleonic structure effects for small system flow

Previous flow measurements in small collision systems were mostly based on highly asymmetric collisions (p+Pb, p+Au, d+Au, 3 He+Au), where both nuclear structure and subnucleonic fluctuations are important. Comparing these asymmetric systems with the newly available symmetric 16 O+ 16 O collisions at RHIC and LHC provides a unique opportunity to disentangle these two contributions. Using Glauber models incorporating both nucleon and quark-level substructure, we analyze multiplicity distributions and initial-state estimators: eccentricities ε n for anisotropic flow ν n and inverse transverse size d ⟂ for radial flow. We find that subnucleonic fluctuations impact O+O collisions differently from asymmetric systems, creating specific patterns in flow observables that enable disentangling the competing contributions. Such experimental comparisons will reduce uncertainties in the initial conditions and improve our understanding of the properties of the QGP-like medium produced in small systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗