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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 145 records · Page 8

Dispersing nano- and micro-sized portlandite particulates via electrosteric exclusion at short screening lengths

In spite of their high surface charge (zeta potential ζ = +34 mV), aqueous suspensions of portlandite (calcium hydroxide: Ca(OH) 2 ) exhibit a strong tendency to aggregate, and thereby present unstable suspensions. While a variety of commercial dispersants seek to modify the suspension stability and rheology (e.g., yield stress, viscosity), it remains unclear how the performance of electrostatically and/or electrosterically based additives is affected in aqueous environments having either a high ionic strength and/or a pH close to the particle's isoelectric point (IEP). We show that the high native ionic strength (pH ≈ 12.6, IEP: pH ≈ 13) of saturated portlandite suspensions strongly screens electrostatic forces (Debye length: κ -1 = 1.2 nm). As a result, coulombic repulsion alone is insufficient to mitigate particle aggregation and affect rheology. However, a longer-range geometrical particle–particle exclusion that arises from electrosteric hindrance caused by the introduction of comb polyelectrolyte dispersants is very effective at altering the rheological properties and fractal structuring of suspensions. As a result, comb-like dispersants that stretch into the solvent reduce the suspension's yield stress by 5× at similar levels of adsorption as compared to linear dispersants, thus enhancing the critical solid loading (i.e., at which jamming occurs) by 1.4×. Significantly, the behavior of diverse dispersants is found to be inherently related to the thickness of the adsorbed polymer layer on particle surfaces. These outcomes inform the design of dispersants for concentrated suspensions that present strong charge screening behavior.

36 MATERIALS SCIENCE↗

Gas-phase oxidation and nanoparticle formation in multi-element laser ablation plumes

The evolution from gas-phase oxidation to nanoparticle and agglomerate formation was studied in nanosecond laser-produced plasmas of a multi-principal element alloy target in air. Here gas-phase oxidation of plasma species was monitored in situ via optical emission spectroscopy, while a custom-built single particle mass spectrometer was used to measure size and compositions of agglomerated nanoparticles formed in laser ablation plumes. Ex situ analysis employing transmission electron microscopy was used to study nanoparticle morphology, crystal structure, and element distribution at the nanoscale. Emission spectra indicate that gas-phase oxidation of elements in the alloy target are formed at varying times during plume evolution, and mass spectrometry results indicate fractal agglomerates contain all principal alloying elements and their oxides. Finally, electron microscopy characterization illustrates that these agglomerates consist of multiple material types: sub-10 nm diameter amorphous, multi-element nanoparticles, ≈10–30 nm diameter Ti-rich crystalline oxide nanoparticles, and ejected base material. Results highlight that the multi-component target composition impacts molecular formation in the gas phase and the morphology, composition, and structure of nanoparticles and agglomerates formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphodynamics of dendrite growth in alumina based all solid-state sodium metal batteries

All solid-state batteries (ASSBs) with ceramic electrolytes and alkali metal anodes are a potential future energy storage technology for vehicle electrification and smart grids. However, uncontrollable dendrite growth toward ultimate short circuiting in solid electrolytes (SEs) has become a serious concern in the design of long-cycle, safe ASSBs, and the underlying mechanism has remained unclear. Here through multiscale imaging and morphodynamic tracking we show that Na dendrites grow in β''-Al 2 O 3 SEs through an alternating sequence of Na deposition and crack propagation. Atomic-scale imaging evidenced that electrochemical cycling causes massive delamination cracking along the Na + conduction planes, accompanied by the closure of neighboring conduction channels. In situ SEM observations revealed a dynamic interplay between Na deposition and crack propagation: Na deposition accumulates mechanical stress that induces cracking; cracking releases the local stress, which promotes further Na deposition. Thus, Na deposition and cracking alternatingly proceed until short circuits take place. A multiscale phase-field model is developed to recapitulate the morphodynamics of Na dendrite growth, predicting the tree-like fractal morphology of the growing dendrites. Importantly, our findings suggest that decoupling between Na deposition and cracking represents an important route to mitigate uncontrollable dendrite growth in ASSBs.

25 ENERGY STORAGE↗

Morphology and reactivity of size-selected titanium oxide nanoclusters on Au(111)

The morphology and reactivity of mass-selected titania clusters, Ti 3 O 6 and Ti 3 O 5 , deposited onto Au(111) were studied by scanning tunneling microscopy (STM) and temperature programmed desorption (TPD). Despite differing by only one oxygen atom, the stoichiometric Ti 3 O 6 and the sub-stoichiometric (“reduced”) Ti 3 O 5 clusters exhibit very different structures and preferred binding sites. The Ti 3 O 6 clusters preferentially bind at step edges and form small assemblies (2-4 clusters) on Au terraces, while the “reduced” Ti 3 O 5 clusters form much larger fractal-like assemblies that can extend across step boundaries. Annealing the Ti 3 O 5,6 /Au(111) systems to higher temperatures causes changes in the size-distributions of cluster assemblies but does not lead to the formation of TiO x nanoislands for temperatures ≤ 700 K. Reactivity studies show that the reduced Ti 3 O 5 cluster has higher activity than Ti 3 O 6 for 2-propanol dehydration, although both clusters exhibit substantial activity for dehydrogenation to acetone. Calculations using DFT+U suggest that the differences in aggregate morphology and reactivity are associated with the number of undercoordinated Ti 3c sites in the supported clusters.

36 MATERIALS SCIENCE↗

Magnetic turnstiles in nonresonant stellarator divertor

Nonresonant stellarator divertors have magnetic flux tubes, called magnetic turnstiles, that cross cantori, which are fractal remnants of destroyed invariant tori with holes, that lie outside the outermost confining surface. The exiting and entering flux tubes can be adjacent as is generally expected but can also have the unexpected feature of entering or exiting at separate locations of the cantori. Not only can there be two types of turnstiles but pseudo-turnstiles can also exist. A pseudo-turnstile is formed when a cantorus has a sufficiently large, although limited, radial excursion to strike a surrounding chamber wall. The existence of non-adjacent and adjacent turnstiles and pseudo-turnstiles resolves issues that arose in earlier simulations of nonresonant stellarator divertors [A. Punjabi and A. H. Boozer, Phys. Plasmas 27, 012503 (2020)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Viewing convection as a solar farm phenomenon broadens modern power predictions for solar photovoltaics

We report heat mitigation for large-scale solar photovoltaic (PV) arrays is crucial to extend lifetime and energy harvesting capacity. PV module temperature is dependent on site-specific farm geometry, yet common predictions consider panel-scale and environmental factors only. Here, we characterize convective cooling in diverse PV array designs, capturing combined effects of spatial and atmospheric variation on panel temperature and production. Parameters, including row spacing, panel inclination, module height, and wind velocity, are explored through wind tunnel experiments, high-resolution numerical simulations, and operating field data. A length scale based on fractal lacunarity encapsulates all aspects of arrangement (angle, height, etc.) in a single value. When applied to the Reynolds number Re within the canonical Nusselt number heat transfer correlation, lacunarity reveals a relationship between convection and farm-specific geometry. This correlation can be applied to existing and forthcoming array designs to optimize convective cooling, ultimately increasing production and PV cell life.

14 SOLAR ENERGY↗

Constraining chaos: Enforcing dynamical invariants in the training of reservoir computers

Drawing on ergodic theory, we introduce a novel training method for machine learning based forecasting methods for chaotic dynamical systems. The training enforces dynamical invariants—such as the Lyapunov exponent spectrum and the fractal dimension—in the systems of interest, enabling longer and more stable forecasts when operating with limited data. The technique is demonstrated in detail using reservoir computing, a specific kind of recurrent neural network. Finally, results are given for the Lorenz 1996 chaotic dynamical system and a spectral quasi-geostrophic model of the atmosphere, both typical test cases for numerical weather prediction.

97 MATHEMATICS AND COMPUTING↗

Nanodiffraction imaging of ionically driven phase separation in cobaltite heterostructures

Controlling the anionic stoichiometry and distribution of perovskite cobaltites presents a powerful method for tailoring the magnetic and electronic properties for magneto-ionic applications. Nevertheless, the influence of nanoscale morphology, including phase separation and defects in cobaltite heterostructures, remains largely unexplored. We used x-ray nanodiffraction to directly image the nanoscale topotactic phase transformation in La 1−x Sr x CoO 3 (LSCO) heterostructures capped with a reactive aluminum (Al) layer (i.e., oxygen “getter”) of varying thicknesses (0.5, 3, and 7 nm). Nanodiffraction images reveal the formation of highly elongated BM filaments extending over mesoscopic lengths (>67 μm), indicating a strong tendency toward oxygen vacancy ordering in both P and BM phases in all heterostructures. Local strain and strain gradient analysis shows a strong correlation between the depletion of the P phase and strain gradients. Our measurements suggest that elongation of the BM filaments is the predominant mechanism for topotactic transformation in LSCO/Al heterostructures, preferred over coarsening, branching, and fractal growth. Our study provides a detailed nanoscale analysis of ionically driven phase transitions in LSCO/Al heterostructures, which is crucial for tailoring the functional properties of cobaltites for magneto-ionic devices.

36 MATERIALS SCIENCE↗

Multiple flat bands and topological Hofstadter butterfly in twisted bilayer graphene close to the second magic angle

Significance Multiple flat bands in high-quality twisted bilayer graphene close to the theoretically predicted second magic angle are observed. These well-isolated flat moiré bands host a nontrivial topology which is evidenced by a connecting multiband Hofstadter butterfly spectrum. This work provides a perspective for understanding the emergent quantum phases (i.e., strong correlation and band topology) in twisted bilayer graphene and the fractal Hofstadter spectra of multiple topological bands.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Self-consistent dispersal puts tight constraints on the spatiotemporal organization of species-rich metacommunities

Dispersal can be critical to the maintenance of ecosystems as it allows local communities to be recolonized after extinction. However, it remains unclear whether the extinction-mitigating effect of dispersal persists when the number of competing species is large. Based on a spatially explicit mathematical description of metacommunities, we show that when many species coexist, each species operates near its extinction threshold, barely surviving due to dispersal. This has general consequences for spatiotemporal abundance patterns. For short-range dispersal, species organize into fractal spatiotemporal extinction patterns characteristic of a directed percolation phase transition. As species approach their extinction threshold, biodiversity is very sensitive to perturbation, suggesting that dispersal within a metacommunity puts tight constraints on the robustness and evolution of species-rich metacommunities. Biodiversity is often attributed to a dynamic equilibrium between the immigration and extinction of species. This equilibrium forms a common basis for studying ecosystem assembly from a static reservoir of migrants—the mainland. Yet, natural ecosystems often consist of many coupled communities (i.e., metacommunities), and migration occurs between these communities. The pool of migrants then depends on what is sustained in the ecosystem, which, in turn, depends on the dynamic migrant pool. This chicken-and-egg problem of survival and dispersal is poorly understood in communities of many competing species, except for the neutral case—the “unified neutral theory of biodiversity.” Employing spatiotemporal simulations and mean-field analyses, we show that self-consistent dispersal puts rather tight constraints on the dynamic migration–extinction equilibrium. When the number of species is large, species are pushed to the edge of their global extinction, even when competition is weak. As a consequence, the overall diversity is highly sensitive to perturbations in demographic parameters, including growth and dispersal rates. When dispersal is short range, the resulting spatiotemporal abundance patterns follow broad scale-free distributions that correspond to a directed percolation phase transition. The qualitative agreement of our results for short-range and long-range dispersal suggests that this self-organization process is a general property of species-rich metacommunities. Our study shows that self-sustaining metacommunities are highly sensitive to environmental change and provides insights into how biodiversity can be rescued and maintained.

54 ENVIRONMENTAL SCIENCES↗

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗

Airborne Release Fractions from Surrogate Nuclear Waste Fires Containing Lanthanide Nitrates and Depleted Uranium Nitrate in 30% Tributyl Phosphate in Kerosene

Airborne contaminants from fires containing nuclear waste represent significant health hazards and shape the design and operation of nuclear facilities. Much of the data used to formulate DOE-HDBK-3010-94, “Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities,” from the U.S. Department of Energy, were taken over 40 years ago. The objectives of this study were to reproduce experiments from Pacific Northwest Laboratories conducted in June 1973 employing current aerosol measurement methods and instrumentation, develop an enhanced understanding of particulate formation and transport from fires containing nuclear waste, and provide modeling and experimental capabilities for updating current standards and practices in nuclear facilities. A special chamber was designed to conduct small fires containing 25 mL of flammable waste containing lutetium nitrate, ytterbium nitrate, or depleted uranium nitrate. Carbon soot aerosols showed aggregates of primary particles ranging from 20 to 60 nm in diameter. In scanning electron microscopy, ~200-nm spheroidal particles were also observed dispersed among the fractal aggregates. The 200-nm spherical particles were composed of metal phosphates. Airborne release fractions (ARFs) were characterized by leaching filter deposits and quantifying metal concentrations with mass spectrometry. The average mass-based ARF for 238 U experiments was 1.0 × 10 -3 with a standard deviation of 7.5 × 10 -4 . For the original experiments, DOE-HDBK-3010-94 states, “Uranium ARFs range from 2 × 10 -4 to 3 × 10 -3 , an uncertainty of approximately an order of magnitude.” Therefore, current measurements were consistent with DOE-HDBK-3010-94 values. ARF values for lutetium and ytterbium were approximately one to two orders of magnitude lower than 238 U. Furthermore, metal nitrate solubility may have varied with elemental composition and temperature, thereby affecting ARF values for uranium surrogates (Yb and Lu). In addition to ARF data, solution boiling temperatures and evaporation rates can also be deduced from experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multi-modal chemical characterization of highly viscous submicrometer organic particles

Distinguishing highly viscous organic particles within complex mixtures of atmospheric aerosol and accurate descriptions of their composition, size distributions, and mixing states are challenges at the forefront of aerosol measurement science and technology. Here, we present results obtained from complementary single-particle measurement techniques employed for the in-depth characterization of highly viscous particles. In this study, we demonstrate advantages and synergy of this multi-modal particle characterization approach based on the analysis of individual viscous particles formed in the air-discharged waste produced by a common sewer pipe rehabilitation technology. Using oil immersion flow microscopy, we investigate particle size distributions and morphology of colloidal components present in field-collected aqueous waste condensates. We compare these results with corresponding measurements of viscous particles formed in drying droplets of the aerosolized discharged waste. The colloidal components and viscous particles were found to be approximately 10 µm and 0.5 µm, respectively. The aerosolized viscous particles exhibited a spherical morphology, while the colloidal particles appeared noticeably fractal, resembling fragments of a cured composite material. Chemical imaging of the viscous particles collected on substrates was performed using scanning electron microscopy and soft X-ray spectro-microscopy techniques. Through these methods, comprehensive description of these particles emerged, confirming their high solid-like viscosity, wide-ranging sizes, diverse carbon speciation with high degrees of oxygenation, and high organic volume fractions. The aerosolized viscous particles were further characterized using high-throughput single particle mass spectrometry. This technique provides real-time measurements of composition, size, and morphological metrics for large numbers of individual particles, enabling the identification of their distinct mass spectrometric signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface structure of mass-selected niobium oxide nanoclusters on Au(111)

The structures formed by the deposition of mass-selected niobium oxide clusters, Nb 3 O y ( y = 5, 6, 7), onto Au(111) were studied by scanning tunneling microscopy. The as-deposited Nb 3 O 7 clusters assemble into large dendritic structures that grow on the terraces as well as extend from the top and bottom of step edges. The Nb 3 O 6 cluster also forms dendritic assemblies but they are generally much smaller in size. The assemblies are composed of smaller discrete structures (<1 nm) which are likely to be single clusters. Furthermore, the dendritic assemblies for both the Nb 3 O 7 and Nb 3 O 6 clusters have fractal dimensions of about 1.7 which is very close to that expected for simple diffusion limited aggregation. Annealing the Nb 3 O 7,6 /Au(111) surfaces up to 550 K results in changes in assembly sizes and increases in heights, while heating to 700 results in the disruption of the assemblies into smaller structures. By contrast, the as-deposited Nb 3 O 5 /Au(111) surface at RT exhibits compact cluster structures which become 3D nanoparticles when annealed above 550 K. Differences in the observed surface structures and thermal stability are attributed to differences in metal-oxygen stoichiometry which can influence cluster binding energies, mobility and inter-cluster interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the non-existence of stepped-pressure equilibria far from symmetry

The Stepped Pressure Equilibrium Code (SPEC) (Hudson et al 2012 Phys. Plasmas 19 112502) has been successful in the construction of equilibria in 3D configurations that contain a mixture of flux surfaces, islands and chaotic magnetic field lines. In this model, the plasma is sliced into sub-volumes separated by ideal interfaces, and in each volume the magnetic field is a Beltrami field. In the cases where the system is far from possessing a continuous symmetry, such as in stellarators, the existence of solutions to a stepped-pressure equilibrium with given constraints, such as a multi-region relaxed MHD minimum energy state, is not guaranteed but is often taken for granted. Using SPEC, we have studied two different scenarios in which a solution fails to exist in a slab with analytic boundary perturbations. Here we found that with a large boundary perturbation, a certain interface becomes fractal, corresponding to the break up of a Kolmogorov–Arnold–Moser (KAM) surface. Moreover, an interface can only support a maximum pressure jump while a solution of the magnetic field consistent with the force balance condition can be found. An interface closer to break-up can support a smaller pressure jump. We discovered that the pressure jump can push the interface closer to being non-smooth through force balance, thus significantly decreasing the maximum pressure it can support. Our work shows that a convergence study must be performed on a SPEC equilibrium with interfaces close to break-up. These results may also provide insights into the choice of interfaces and have applications in finding out the maximum pressure a machine can support.

3D equilibrium↗

Fungal drops: a novel approach for macro- and microscopic analyses of fungal mycelial growth

Abstract This study presents an inexpensive approach for the macro- and microscopic observation of fungal mycelial growth. The ‘fungal drops’ method allows to investigate the development of a mycelial network in filamentous microorganisms at the colony and hyphal scales. A heterogeneous environment is created by depositing 15–20 µl drops on a hydrophobic surface at a fixed distance. This system is akin to a two-dimensional (2D) soil-like structure in which aqueous-pockets are intermixed with air-filled pores. The fungus (spores or mycelia) is inoculated into one of the drops, from which hyphal growth and exploration take place. Hyphal structures are assessed at different scales using stereoscopic and microscopic imaging. The former allows to evaluate the local response of regions within the colony (modular behaviour), while the latter can be used for fractal dimension analyses to describe the hyphal network architecture. The method was tested with several species to underpin the transferability to multiple species. In addition, two sets of experiments were carried out to demonstrate its use in fungal biology. First, mycelial reorganization of Fusarium oxysporum was assessed as a response to patches containing different nutrient concentrations. Second, the effect of interactions with the soil bacterium Pseudomonas putida on habitat colonization by the same fungus was assessed. This method appeared as fast and accessible, allowed for a high level of replication, and complements more complex experimental platforms. Coupled with image analysis, the fungal drops method provides new insights into the study of fungal modularity both macroscopically and at a single-hypha level.

Buffi, Matteo↗

Entanglement phases in large- N hybrid Brownian circuits with long-range couplings

Here, we develop solvable models of large-N hybrid quantum circuits on qubits and fermions with tunable long-range power-law interactions and continuous local monitoring. These models provide analytical access to the entanglement phase diagram and error-correcting properties of many-body entangled nonequilibrium states generated by such dynamics. In one dimension, the long-range couplings are irrelevant for α > 3/2, where α is the power-law exponent, and the models exhibit a conventional measurement-induced phase transition between volume- and area-law entangled phases. For 1/2 < α < 3/2, the long-range couplings become relevant, leading to a nontrivial dynamical exponent at the measurement-induced phase transition. More interestingly, for α < 1, the entanglement pattern receives a subvolume correction for both area-law and volume-law phases, indicating that the phase realizes a quantum error correcting code whose code distance scales as L 2–2α . While the entanglement phase diagram is the same for both the interacting qubit and fermionic hybrid Brownian circuits, we find that long-range free-fermionic circuits exhibit a distinct phase diagram with two different fractal entangled phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Deep learning Hamiltonians from disordered image data in quantum materials

The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length- and timescales. Many such materials feature inhomogeneous electronic properties with intricate pattern formation on the observable surface. This rich spatial structure contains information about interactions, dimensionality, and disorder—a spatial encoding of the Hamiltonian driving the pattern formation. Image recognition techniques from machine learning are an excellent tool for interpreting information encoded in the spatial relationships in such images. Here, we develop a deep learning framework for using the rich information available in these spatial correlations in order to discover the underlying Hamiltonian driving the patterns. We first vet the method on a known case, scanning near-field optical microscopy on a thin film of V⁢O 2 . We then apply our trained convolutional neural network architecture to new optical microscope images of a different V⁢O 2 film as it goes through the metal-insulator transition. We find that a two-dimensional Hamiltonian with both interactions and random field disorder is required to explain the intricate, fractal intertwining of metal and insulator domains during the transition. This detailed knowledge about the underlying Hamiltonian paves the way for using the model to control the pattern formation via, e.g., tailored hysteresis protocols. Finally, we also introduce a distribution-based confidence measure on the results of a multilabel classifier, which does not rely on adversarial training. In addition, we propose a machine-learning-based criterion for diagnosing a physical system's proximity to criticality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗