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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 469 records · Page 26

Beam-energy dependence of correlations between mean transverse momentum and anisotropic flow of charged particles in Au+Au collisions at RHIC

The correlation between the mean transverse momentum, [ p T ], and the squared anisotropic flow, $v^2_n$, on an event-by-event basis has been suggested to be influenced by the initial conditions in heavy-ion collisions. We present measurements of the variances and covariance of [ p T ] and $v^2_n$, along with their dimensionless ratio, for Au+Au collisions at various beam energies: $\sqrt{s_{NN}}$ = 14.6, 19.6, 27, 54.4, and 200 GeV. Our measurements reveal a distinct energy-dependent behavior in the variances and covariances. In addition, the dimensionless ratio displays a similar behavior across different beam energies. We compare our measurements with hydrodynamic models and similar measurements from Pb+Pb collisions at the Large Hadron Collider (LHC). These findings provide valuable insights into the beam energy dependence of the specific shear viscosity ( η/s ) and initial-state effects, allowing for differentiating between different initial-state models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Probing late-stage hadronic interactions at high baryon density via $K^{⁎0}$ production in the RHIC beam energy scan program

A precision measurement of the $K^{⁎0}$ meson yield is reported in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7, 11.5, 14.6, 19.6, and 27 GeV using the high-statistics data sample collected by the STAR experiment during the Beam Energy Scan II (BES-II) program at RHIC. The transeverse momentum (p T )-integrated yield ratios $\large{(}K^{⁎0} + \overline{K^{⁎0}}\large{)}/(K^+ + K^{-})$ in central collisions show a suppression relative to peripheral collisions at the (1.7–3.6) σ level, while a thermal model without final-stage rescattering overpredicts this ratio with a deviation of (6.9–8.2) σ. These results indicate a loss of the measured $K^{⁎0}$ signal in central collisions due to re-scattering of its hadronic decay products in the hadronic phase. The p T -integrated yield of charged kaons exhibits an approximate scaling with charged-particle multiplicity, independent of collision energy and system size. A similar trend is observed for the short-lived $K^{⁎0}$ resonance, although significant deviations emerge at lower energies. At BES energies, the $K^{⁎0}/K$ ratio shows stronger suppression than at the highest RHIC and LHC energies within a given multiplicity bin, particularly in central and mid-central collisions. This behavior is consistent with changes in the effective hadronic interaction cross section and is supported by transport model calculations, which indicate dominant meson–baryon interactions at lower energies and meson–meson interactions at higher energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement of inclusive $J/ψ$ production in Au+Au collisions at $\sqrt{s_{\textrm{NN}}}$ = 54.4 GeV at STAR

This article presents measurements of inclusive J/ψ production at midrapidity (|y| < 1.0) in Au+Au collisions at $\sqrt{s_{\textrm{NN}}}$ = 54.4 GeV with the STAR detector at the Relativistic Heavy Ion Collider. A suppression of the J/ψ yield, quantified using the nuclear modification factors (R AA , R CP ), is observed with respect to the scaled production p + p in collisions. The dependence of R AA on collision centrality and J/ψ transverse momentum is measured with improved precision compared to previous measurements at 39 and 62.4 GeV, while the centrality dependence of R CP is measured and compared to the same results at 39, 62.4, and 200 GeV. In central collisions, no significant collision energy dependence of R AA is found within uncertainties for collision energies between 17.3 and 200 GeV. Two transport model calculations that include dissociation and regeneration contributions are consistent with the experimental results within uncertainties. Although no significant collision energy dependence of the J/ψ suppression in high energy heavy-ion collisions up to $\sqrt{s_{\textrm{NN}}}$ = 200 GeV is observed within uncertainties, the newly measured results at 54.4 GeV Au+Au collisions provide additional constraints on theoretical calculations of the hot medium evolution and cold nuclear matter effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗

miR-126 regulates angiogenesis in myocardial ischemia by targeting HIF-1α

Promoting angiogenesis by targeting various angiogenic regulators has emerged as a new treatment strategy for myocardial ischemia (MI). MicroRNA-126 (miR-126) has been identified as the main regulator of compensatory angiogenesis; however, its role in MI is unclear. A rat MI model and an EA. hy926 endothelial cell hypoxia model were constructed and it was found that miR-126 was highly expressed in both models. The knockdown of HIF-1α expression in EA. hy926 cells in turn downregulated VEGF and CD34 expression and consequently inhibited angiogenesis. MiR-126 inhibitor inhibited EA. hy926 cell migration and tube formation as well as downregulated VEGF and CD34 expression, and these were reversed by transfection of miR-126 mimics. Rescue tests using miR-126 and HIF-1α demonstrated that miR-126-mediated regulation of angiogenesis was dependent on HIF-1α. In summary, miR-126 regulates the occurrence and progression of angiogenesis during MI via HIF-1α and may be a potential new therapeutic target.

60 APPLIED LIFE SCIENCES↗

LaNi x Fe 1– x O 3–δ as a Robust Redox Catalyst for CO 2 Splitting and Methane Partial Oxidation

The current study reports LaNi 0.5 Fe 0.5 O 3–δ as a robust redox catalyst for CO 2 splitting and methane partial oxidation at relatively low temperatures (~700 °C) in the context of a hybrid redox process. Specifically, perovskite-structured LaNi x Fe 1–x O 3–δ (LNFs) with nine different compositions (x = 0.05–0.5) were prepared and investigated. Among the samples evaluated, LaNi 0.4 Fe 0.6 O 3–δ and LaNi 0.5 Fe 0.5 O 3–δ showed superior redox performance, with ~90% CO 2 and methane conversions and >90% syngas selectivity. The standalone LNFs also demonstrated performance comparable to that of LNF promoted by mixed conductive Ce 0.85 Gd 0.1 Cu 0.05 O 2–δ (CGCO). Long-term testing of LaNi 0.5 Fe 0.5 O 3–δ indicated that the redox catalyst gradually loses its activity over repeated redox cycles, amounting to approximately 0.02% activity loss each cycle, averaged over 500 cycles. This gradual deactivation was found to be reversible by deep oxidation with air. Further characterizations indicated that the loss of activity resulted from a slow accumulation of iron carbide (Fe 3 C and Fe 5 C 2 ) phases, which cannot be effectively removed during the CO 2 splitting step. Reoxidation with air removed the carbide phases, increased the availability of Fe for the redox reactions via solid-state reactions with La 2 O 3 , and decreased the average crystallite size of La 2 O 3 . As a result, reactivating the redox catalyst periodically, e.g., once every 40 cycles, was shown to be highly effective, as confirmed by operating the redox catalyst over 900 cumulative cycles while maintaining satisfactory redox performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impacts of Anisotropic Porosity on Heat Transfer and Off-Gassing during Biomass Pyrolysis

The pore structure of biogenic materials imbues the ability to deliver water and nutrients through a plant from root to leaf. This anisotropic pore granularity can also play a significant role in processes such as biomass pyrolysis that are used to convert these materials into useful products like heat, fuel, and chemicals. Evolutions in modeling of biomass pyrolysis as well as imaging of pore structures allow for further insights into the concerted physics of phase change-induced off-gassing, heat transfer, and chemical reactions. In this work, we report a biomass single particle model which incorporates these physics to explore the impact of implementing anisotropic permeability and diffusivity on the conversion time and yields predicted for pyrolysis of oak and pine particles. Simulation results showed that anisotropic permeability impacts predicted conversion time more than 2 times when the Biot number is above 0.1 and pyrolysis numbers (Py 1 , Py 2 ) are less than 20. Pore structure significantly impacts predicted pyrolytic conversion time (>8 times) when the Biot number is above 1 and the pyrolysis number is below 1, i.e., the “conduction controlled” regime. Therefore, these nondimensional numbers reflect that when internal heat conduction limits pyrolysis performance, internal pyrolysis off-gassing further retards effective heat transfer rates as a closely coupled phenomenon. Overall, this study highlights physically meaningful opportunities to improve particle-scale pyrolysis modeling and experimental validation relevant to a variety of feedstock identities and preparations, guiding the future design of pyrolyzers for efficient biomass conversion.

09 BIOMASS FUELS↗

Reduction-Controlled Atomic Migration for Single Atom Alloy Library

Here, picturing the atomic migration pathways of catalysts in a reactive atmosphere is of central significance for uncovering the underlying catalytic mechanisms and directing the design of high-performance catalysts. Here, we describe a reduction-controlled atomic migration pathway that converts nanoparticles to single atom alloys (SAAs), which has remained synthetically challenging in prior attempts due to the elusive mechanism. We achieved this by thermally treating the noble-metal nanoparticles M (M = Ru, Rh, Pd, Ag, Ir, Pt, and Au) on metal oxide (CuO) supports with H2/Ar. Atomic-level characterization revealed such conversion as the synergistic consequence of noble metal-promoted H2 dissociation and concomitant CuO reduction. The observed atomic migration pathway offers an understanding of the dynamic mechanisms study of nanomaterials formation and catalyst design.

36 MATERIALS SCIENCE↗