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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 307 records · Page 17

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey II: measurements in Fourier space with optimal weights

ABSTRACT We present measurements of the local primordial non-Gaussianity parameter $f_{\mathrm{NL}}^\mathrm{local} $from the clustering of 343 708 quasars with redshifts 0.8 < z < 2.2 distributed over 4808 deg2 from the final data release (DR16) of the extended Baryon Acoustic Oscillation Spectroscopic Survey (eBOSS), the largest volume spectroscopic survey up to date. Our analysis is performed in Fourier space, using the power spectrum monopole at very large scales to constrain the scale-dependent halo bias. We demonstrate the robustness of our analysis pipeline with EZ-mock catalogues that simulate the eBOSS DR16 target selection. We carefully assess the impact of systematics on our measurement, exploiting a novel neural network scheme for cleaning the DR16 sample as well as test multiple contamination removal methods. We estimate the bias due to the overcorrection of the systematic removal to be sub-dominant compared to the statistical uncertainty. We find fNL = −12 ± 21 (68 per cent confidence) for the main clustering sample including quasars with redshifts between 0.8 and 2.2, after applying redshift weighting techniques, designed for non-Gaussianity measurement from large scales structure, to optimize our analysis, which improve our results by 37 per cent.

79 ASTRONOMY AND ASTROPHYSICS↗

Graphene-polyelectrolyte multilayer membranes with tunable structure and internal charge

One great advantage of graphene-polyelectrolyte multilayer (GPM) membranes is their tunable structure and internal charge for improved separation performance. In this study, we synthesized GO-dominant GPM membrane with internal negatively-charged domains, polyethyleneimine (PEI)-dominant GPM membrane with internal positively-charged domains and charge-balanced dense/loose GPM membranes by simply adjusting the ionic strength and pH of the GO and PEI solutions used in layer-by-layer membrane synthesis. A combined system of quartz crystal microbalance with dissipation (QCM-D) and ellipsometry was used to analyze the mass deposition, film thickness, and layer density of the GPM membranes. The performance of the GPM membranes were compared in terms of both permeability and selectivity to determine the optimal membrane structure and synthesis strategy. One effective strategy to improve the GPM membrane permeability-selectivity tradeoff is to assemble charge-balanced dense membranes under weak electrostatic interactions. This balanced membrane exhibits the highest MgCl 2 selectivity (~86%). Another effective strategy for improved cation removal is to create PEI-dominant membranes that provide internal positively-charged barrier to enhance cation selectivity without sacrificing water permeability. Finally, these findings shine lights on the development of a systematic approach to push the boundary of permeability-selectivity tradeoff for GPM membranes.

42 ENGINEERING↗

Effect of heat treatment paths on the aging and rejuvenation of metallic glasses

Here, this study explores the influence of heat treatment paths on the structural relaxation of metallic glasses (MGs) in the regime of fast dynamics. We create MG samples using various quenching rates, from 10 9 to 10 11 K/s, and expose these samples to near-T g heat treatments with assorted combinations of heating/cooling rates, from 5×10 10 to 5×10 12 K/s, and annealing durations, from 10 ps to 10 ns. Results show that the effect of the heating rate is intricately tied to the initial structure of the MG, while a decrease in the cooling rate invariably intensifies the aging process. Extending the annealing duration may induce either aging or rejuvenation, subject to the specific thermal history. To interpret these findings, we hypothesize that the memory effect, governed by the activation and annihilation of reversible and irreversible flow units, underpins the rejuvenation-aging competition in MGs. Moreover, we suggest viewing the cooling stage as an annealing phase controlled by gradient temperature and fine-tuning its rate to achieve the targeted active flow unit distributions. This study illuminates the role of fast dynamics during the glass relaxation process and offers practical strategies for tailoring heat treatments to optimize MG structures and mechanical performance.

36 MATERIALS SCIENCE↗

Design optimization of lightweight automotive seatback through additive manufacturing compression overmolding of metal polymer composites

With the growing demand for enhanced automotive fuel efficiency and environmental sustainability, there is a need for lightweighting automotive components through innovative design and manufacturing processes. Here, this study leverages a combination of numerical iterative design optimization and hybrid additive manufacturing–compression molding (AM-CM) technique for metal polymer composites to lightweight an automotive seatback. The AM-CM process enables robust mechanical interlocking between metals and composites, boasting high stiffness and strength with low overall density. Replacing metallic components with such metal polymer composites allows for comparable mechanical performance while significantly reducing the overall weight. First, the automotive seatback design space is reduced to critical load carrying regions using topology optimization and high stress concentration areas are identified using finite element analysis. Next, a lightweight metal polymer subcomponent is designed for a high stress concentration region. The full seatback frame with spatially heterogeneous material-specific design is then iteratively optimized to enable enhanced stiffness with minimal weight. Overall, the automotive seatback frame designed with location-specific metal, polymer, and metal polymer composite materials weighs 20% less than the metal-only design while exhibiting similar stiffness.

36 MATERIALS SCIENCE↗

Molecular level insight into non-bilayer structure formation in thylakoid membranes: a molecular dynamics study

In oxygenic photosynthetic organisms, the light reactions are performed by protein complexes embedded in the lipid bilayer of thylakoid membranes (TMs). The organization of the bulk lipid molecules into bilayer structures provide optimal conditions for the build-up of the proton motive force (pmf) and its utilization for ATP synthesis. However, the lipid composition of TMs is dominated by the non-bilayer lipid species monogalactosyl diacylglycerol (MGDG), and functional plant TMs, besides the bilayer, contain large amounts of non-bilayer lipid phases. Bulk lipids have been shown to be associated with lumenal, stromal-side and marginal-region proteins and proposed to play roles in the self-assembly and photoprotection of the photosynthetic machinery. Furthermore, it has recently been pointed out that the generation and utilization of pmf for ATP synthesis according to the ‘protet’ or protonic charge transfer model Kell (Biochim Biophys Acta Bioenerg 1865(4):149504, 2024), requires high MGDG content Garab (Physiol Plant 177(2):e70230, 2025). In this study, to gain better insight into the structural and functional roles of MGDG, we employed all atom and coarse-grained molecular dynamics simulations to explore how temperature, hydration levels and varying MGDG concentrations affect the structural and dynamic properties of bilayer membranes constituted of plant thylakoid lipids. Our findings reveal that MGDG promotes increased membrane fluidity and dynamic fluctuations in membrane thickness. MGDG-rich stacked bilayers spontaneously formed inverted hexagonal phases; these transitions were enhanced at low hydration levels and at elevated but physiologically relevant temperatures. It can thus be inferred that MGDG plays important roles in heat and drought stress mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Gaseous cyclodextrin- closo -dodecaborate complexes χCD·B 12 X 12 2– (χ = α, β, and γ; X = F, Cl, Br, and I): electronic structures and intramolecular interactions

A fundamental understanding of cyclodextrin- closo -dodecaborate inclusion complexes is of great interest in supramolecular chemistry. Herein, we report a systematic investigation on the electronic structures and intramolecular interactions of perhalogenated closo -dodecaborate dianions B 12 X 12 2– (X = F, Cl, Br and I) binding to α-, β-, and γ-cyclodextrins (CDs) in the gas phase using combined negative ion photoelectron spectroscopy (NIPES) and density functional theory (DFT) calculations. The vertical detachment energy (VDE) of each complex and electronic stabilization of each dianion due to the CD binding (ΔVDE, relative to the corresponding isolated B 12 X 12 2– ) are determined from the experiments along α-, β- and γ-CD in the form of VDE (ΔVDE): 4.00 (2.10), 4.33 (2.43), and 4.30 (2.40) eV in X = F; 4.09 (1.14), 4.64 (1.69), and 4.69 (1.74) eV in X = Cl; 4.11 (0.91), 4.58 (1.38), and 4.70 (1.50) eV in X = Br; and 3.54 (0.74), 3.88 (1.08), and 4.05 (1.25) eV in X = I, respectively. All complexes have significantly higher VDEs than the corresponding isolated dodecaborate dianions with ΔVDE spanning from 0.74 eV at (α, I) to 2.43 eV at (β, F), sensitive to both host CD size and guest substituent X. DFT-optimized complex structures indicate that all B 12 X 12 2– prefer binding to the wide openings of CDs with the insertion depth and binding motif strongly dependent on the CD size and halogen X. Dodecaborate anions with heavy halogens, i.e. , X = Cl, Br, and I, are found outside of α-CD, while B 12 F 12 2– is completely wrapped by γ-CD. Partial embedment of B 12 X 12 2– into CDs is observed for the other complexes via multipronged B–X … H–O/C interlocking patterns. The simulated spectra based on the density of states agree well with those of the experiments and the calculated VDEs well reproduce the experimental trends. Molecular orbital analyses suggest that the spectral features at low binding energies originated from electrons detached from the dodecaborate dianion, while those at higher binding energies are derived from electron detachment from CDs. Energy decomposition analyses reveal that the electrostatic interaction plays a dominating role in contributing to the host–guest interactions for the X = F series partially due to the formation of a O/C–H … X–B hydrogen bonding network, and the dispersion forces gradually become important with the increase of halogen size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization of COMPASS-U Support Structure

The global support structure for Compass Upgrade (COMPASS-U) employs many bolted and pinned components to improve the manufacturability of the whole structures. This is a departure from other designs used for highly loaded tokamaks, like Alcator C-Mod which used large forgings. Modeling of the numerous connections and interfaces was a challenge. This article will describe how to optimize the C-frame support structure with the goal to eliminate differential displacements at those interfaces and, importantly, minimize toroidal mutual displacement at the sliding joint of the toroidal field (TF) coils. The global support structure consists of 16 C-frames, and it can be simplified as a 1/8th cyclic symmetry model due to the eight vertical rods mounting that connect bottom CS and PF1-3 assemblies to the C-frames. Structure variants with different connection webs between two neighboring C-frames have been analyzed. The preloading of bolts can be split into several preload substeps to simulate the real assembly process of the COMPASS-U support structure. Additionally, the TF crown and the wedge plate can be further improved to become a solid part to better hold the TF coils.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dual 3D Ceramic Textile Electrodes: Fast Kinetics for Carbon Oxidation Reaction and Oxygen Reduction Reaction in Direct Carbon Fuel Cells at Reduced Temperatures

Abstract Direct carbon fuel cells (DCFCs) are an efficient energy‐conversion technology capable of generating electricity with carbon‐dioxide‐capture chemistry with solid carbon as fuels. The efficiency and performance of DCFCs depend on the kinetics of the carbon oxidation reactions (COR) and the oxygen reduction reactions (ORR), each occurring at anode and cathode, respectively. The limited active sites paired with reduced temperatures greatly decrease the efficiency of the electrochemical reactions. Ultraporous dual‐3D ceramic textiles (dual‐3DCT) are integrated into electrolyte‐supported DCFCs to enhance charge and mass transfer at the electrodes. Improved COR at the anode is achieved by the synergy between the 3DCT NiO–Ce 0.8 Gd 0.2 O 1.95 (GDC) structure and optimal carbon fuel choice. In a comparative study, DCFCs using graphitic carbon (GC) as fuel show the best COR performance when compared to DCFCs utilizing alternative fuels such as carbon black (CB) and activated carbon (AC). The 3DCT Sm 0.5 Sr 0.5 CoO 3‐δ –GDC (SSC–GDC) composite cathode shows electrochemical performance superior to that of the conventional screen‐printed SSC–GDC. A peak power density of 392 mW cm −2 at 600 °C is obtained in a DCFC using the 3DCT‐anode/electrolyte/3DCT‐cathode configuration, an unprecedented value for any reported DCFC as of yet. This points toward promising applications of dual‐3DCT electrodes for reduced‐temperature DCFCs.

Bian, Wenjuan↗

Electron Redistributed S-Doped Nickel Iron Phosphides Derived from One-Step Phosphatization of MOFs for Significantly Boosting Electrochemical Water Splitting

Nonprecious transition metal-organic frameworks (MOFs) are one of the most promising precursors for developing electrocatalysts with high porosity and structural rigidity. This study reports the synthesis of high efficiency electrocatalysts based on S-doped NiFeP. MOF-derived S-doped NiFeP structure is synthesized by a one-step phosphorization process with using S-doped MOFs as the precursor, which is more convenient and environment friendly, and also helps retain the samples’ framework. The oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) performance of the NiFeP catalysts can be improved after partially replacing P by S due to the tunable electronic structure. The optimized CCS-NiFeP-10 reaches a current density of 10 mA cm –2 for OER with an overpotential of 201 mV and outperforms most NiFe-based catalysts. The S doping plays an important role in tuning the ΔG values for intermediates formation in Ni atoms to a suitable value and exhibits a pronouncedly improved the OER performance. CCS-NiFeP-20 sample presents excellent HER performance due to the d-band center downshifting from the Fermi level. When the voltage of the electrolytic cell is 1.50 V, a current density of 10 mA cm –2 can be obtained. This strategy paves the way for designing highly active none-noble metal catalysts.

36 MATERIALS SCIENCE↗

Dual-Solvent Li-Ion Solvation Enables High-Performance Li-Metal Batteries

Novel electrolyte designs to further enhance the lithium (Li) metal battery cyclability are highly desirable. Here, fluorinated 1,6-dimethoxyhexane (FDMH) is designed and synthesized as the solvent molecule to promote electrolyte stability with its prolonged –CF 2 – backbone. Meanwhile, 1,2-dimethoxyethane is used as a co-solvent to enable higher ionic conductivity and much reduced interfacial resistance. Combining the dual-solvent system with 1 m lithium bis(fluorosulfonyl)imide (LiFSI), high Li-metal Coulombic efficiency (99.5%) and oxidative stability (6 V) are achieved. Using this electrolyte, 20 µm Li||NMC batteries are able to retain ≈80% capacity after 250 cycles and Cu||NMC anode-free pouch cells last 120 cycles with 75% capacity retention under ≈2.1 µL mAh -1 lean electrolyte conditions. Such high performances are attributed to the anion-derived solid-electrolyte interphase, originating from the coordination of Li-ions to the highly stable FDMH and multiple anions in their solvation environments. This work demonstrates a new electrolyte design strategy that enables high-performance Li-metal batteries with multisolvent Li-ion solvation with rationally optimized molecular structure and ratio.

25 ENERGY STORAGE↗

Efficient, Color-Stable, and Long-Lived White Organic Light-Emitting Diodes Utilizing Phosphorescent Molecular Aggregates

Highly efficient and stable single-stack hybrid white organic light-emitting diode (WOLED) devices are developed using two emissive layers: one with amber-colored phosphorescent molecular-aggregate emission from the Pd(II) complex, Pd(II) 7-(3-(pyridine-2-yl-κN)phenoxy-κC)(benzo-κC)([c]benzo[4,5]imidazo-κN)[1,2-a][1,5]naphthyridine, Pd3O8-Py5, and the other with blue fluorescence emission. Here, an optimized device structure achieves high color stability under various current densities, an external quantum efficiency (EQE) of 45.5%, a power efficiency of 97.4 Lm W -1 , and an estimated LT 95 (operational time to 95% of the initial luminance) of 50 744 h at an initial luminance of 1000 cd m -2 .

36 MATERIALS SCIENCE↗

Recent Progress in Solid‐State Lithium Batteries through Cathode Microstructure Engineering

A high‐performance cathode is necessary to realize the great potentials of solid‐state batteries such as high energy density and long cycle life. It is also needed to validate electrolyte performance, which is lacking. Currently, cathodes for solid‐state batteries are thinner and have lower cathode active material content than their lithium‐ion battery counterpart, resulting from insufficient conductivity and limiting the battery energy density. This review article provides an overview of recent development in cathode microstructures and their impact on battery properties, including compatibility between cathode and electrolyte, cathode architecture design, interface engineering, correlation between material properties, cathode processing approaches, and performance, as well as the advanced characterization methods used to understand the above correlations . Some perspectives on future development are shared including utilizing in situ and operando characterization tools to better understand dynamic evolution of the cathode/electrolyte interface, adapting artificial intelligence and machine learning to design and optimize cathode structures. The article is aimed to promote research interest on cathode development and advance solid‐state battery technologies.

cathode engineering↗

Microstructural Underpinnings of Giant Intrinsic Exchange Bias in Epitaxial NiCo 2 O 4 Thin Films

Understanding intrinsic exchange bias in nominally single-component ferromagnetic or ferrimagnetic materials is crucial for simplifying related device architectures. However, the mechanisms behind this phenomenon and its tunability remain elusive, which hinders the efforts to achieve unidirectional magnetization for widespread applications. Inspired by the high tunability of ferrimagnetic inverse spinel NiCo 2 O 4 , the origin of intrinsic exchange bias in NiCo 2 O 4 (111) films deposited on Al 2 O 3 (0001) substrates are investigated. The comprehensive characterizations, including electron diffraction, X-ray reflectometry and spectroscopy, and polarized neutron reflectometry, reveal that intrinsic exchange bias in NiCo 2 O 4 (111)/Al 2 O 3 (0001) arises from a reconstructed antiferromagnetic rock-salt Ni x Co 1-x O layer at the interface between the film and the substrate due to a significant structural mismatch. Remarkably, by engineering the interfacial structure under optimal growth conditions, it can achieve exchange bias larger than coercivity, leading to unidirectional magnetization. Such giant intrinsic exchange bias can be utilized for realistic device applications. This work establishes a new material platform based on NiCo 2 O 4 , an emergent spintronics material, to study tunable interfacial magnetic and spintronic properties.

36 MATERIALS SCIENCE↗

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗

Engineering intricacies of implementing single-atom alloy catalysts for low-temperature electrocatalytic CO 2 reduction

Catalysts research for electrocatalytic CO 2 reduction reactions (CO 2 R) has undergone rapid growth in the last decade. Single-atom alloy catalysts (SAAs) featuring atomically dispersed metal dopants on host metal surfaces have shown promises in boosting CO 2 R yield by optimizing the structure and synergy of the catalytic metals at the atomic scale. Despite the exciting development of SAAs for CO 2 R in fundamental science, dedicated studies for its engineering implementation have been absent. We use this perspective to discuss our non-exhaustive engineering considerations for implementing SAAs for CO 2 R. Here, the perspective starts with a brief overview of the current research status for SAAs in CO 2 R, followed by focal points on structure uncertainties associated with catalyst manufacturing, catalyst layer degradation during reaction, and possibilities for SAAs to mitigate the salt precipitation issue at the device level. We hope our opinions will engage increasing attention toward the engineering catalysis research for applying SAAs to CO 2 R at scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response

Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To predict the performance of particular microstructural configuration and thereby overall performance, constitutive models of materials with microstructure are needed. In this work we provide neural network architectures that provide effective homogenization models of materials with anisotropic components. These models satisfy equivariance and material symmetry principles inherently through a combination of equivariant and tensor basis operations. We demonstrate them on datasets of stochastic volume elements with different textures and phases where the material undergoes elastic and plastic deformation, and show that the these network architectures provide significant performance improvements.

anisotropy↗

Towards physics-informed explainable machine learning and causal models for materials research

From emergent material descriptions to estimation of properties stemming from structures to optimization of process parameters for achieving best performance – all key facets of materials science and related fields have experienced tremendous growth with the introduction of data-driven models. This gradual progression goes at par with developments of machine learning workflows, from purely data-driven shallow models to those that are well-capable in encoding more complex graphs, symbolic representations, invariances, and positional embeddings. Furthermore, this perspective aims at summarizing strategic aspects of such transitions while providing insights into the requirements of bringing in explainable, interpretable predictive models, and causal learning to aid in materials design and discovery. Although the focus remains on a variety of functional materials by providing a handful of case studies, the applications of such integrated methodologies are universal to facilitate fundamental understandings of materials physics while enabling autonomous experiments.

36 MATERIALS SCIENCE↗