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At least 253 records · Page 14

Influence of Potassium Metal-Support Interactions on Dendrite Growth

We report combined synchrotron X-ray nanotomography imaging, cryogenic electron microscopy (cryo-EM) and modeling elucidate how potassium (K) metal-support energetics influence electrodeposit microstructure. Three model supports are employed: O-functionalized carbon cloth (potassiophilic, fully-wetted), non-functionalized cloth and Cu foil (potassiophobic, nonwetted). Nanotomography and focused ion beam (cryo-FIB) cross-sections yield complementary three-dimensional (3D) maps of cycled electrodeposits. Electrodeposit on potassiophobic support is a triphasic sponge, with fibrous dendrites covered by solid electrolyte interphase (SEI) and interspersed with nanopores (sub-10 nm to 100 nm scale). Lage cracks and voids are also a key feature. On potassiophilic support, the deposit is dense and pore-free, with uniform surface and SEI morphology. Mesoscale modeling captures the critical role of substrate-metal interaction on K metal film nucleation and growth, as well as the associated stress state.

36 MATERIALS SCIENCE↗

Structure of the pellet-cladding interaction layer of a high-burnup Zr-Nb-O nuclear fuel cladding

Here, structure of the pellet/cladding-interaction (PCI) layer of a high-burnup nuclear fuel with niobium-bearing cladding was investigated using modern transmission electron microscopy (TEM) techniques. Morphology of the PCI consisted of uniform zirconia layer on the cladding side and finger-like features towards to the ceramic fuel. The PCI layer showed a complex microstructure that constitutes three distinct zirconia layers formed by two zirconia phases. From cladding to fuel, monoclinic, tetragonal, and another tetragonal phase were determined via TEM diffraction patterns and precession electron diffraction (PED) using ASTAR microscopy platform (AMP). Characterizations showed that monoclinic and tetragonal phases close to the cladding were crack-free, but the tetragonal layer adjacent to the fuel contained cracks and pores. Presence of the monoclinic layer suggested that its formation involved the gaseous diffusion of oxygen below threshold dose of fission product damage before the fuel/cladding contact occurred. Furthermore, high-resolution TEM revealed compound phase of (U,Zr)O 2 at fringes of zirconia fingers on the fuel side.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microscopic Observation of Solid Electrolyte Interphase Bilayer Inversion on Silicon Oxide

Silicon has been investigated in recent years as an alloying anode material to enhance gravimetric energy density in lithium-ion batteries. Although recent developments have suggested that silicon oxides exhibit improved cycling stability over pure Si, the origin of the improved cycling performance is still poorly understood. The initial solid electrolyte interphase (SEI) formation mechanisms on Si wafers with both native oxide and chemically etched thermal oxide coatings are investigated structurally, chemically, and morphologically in the nanoscale. After one electrochemical cycle, microscopy reveals that SEI formed on native SiO x features the typical SEI bilayer structure with a carbon-rich outer SEI layer and an inorganic-rich inner SEI layer. In contrast, the SEI formed on chemically etched thermal oxide shows an inversion in the structure. This work observes distinct initial SEI formation mechanisms on the HF-etched SiO 2 surface, which may be partially responsible for improved cycle life observed in SiO x -based anode materials.

25 ENERGY STORAGE↗

Compositional Phase Control in High-Entropy Alloy Electrocatalysts

High-entropy alloys (HEAs) provide uniquely tunable structural and electronic properties that enable robust electrocatalysis. While compositional manipulation of HEAs is well-known, systematically controlling the crystalline phase and morphology remains a challenge that could provide new avenues for controlling reactive sites and physical properties. Here, we show the preferential stabilization of mixed fcc/bcc to fcc phases by controlling the Au content in quinary AuPdFeCoNi HEA nanoparticles. This systematic structural and compositional control, when investigated with an ensemble of electronic, X-ray synchrotron, and surface techniques, allows us to identify the critical short- (few-Å) and medium- (6–10 Å) range structural motifs that deliver exceptional hydrogen evolution reaction (HER) catalysis. Specifically, these HEAs exhibit both outstanding durability (240 h) and high mass activity (50 A/mg PGM ) normalized to noble metal content, outperforming commercial Pt/C (3.18 A/mg PGM ). This structural control over HEA morphology, and its direct association with changes in specific metallic oxidation states and pair–pair atomic structural features, provides new means and strategies for finely designing robust and sustainable electrocatalysts with a majority nonprecious metal composition.

36 MATERIALS SCIENCE↗

Decoding NGC 7252 as a blue elliptical galaxy

Elliptical galaxies with blue optical colours and significant star formation are hypothesised to be major merger remnants of gas-rich spiral galaxies or normal elliptical galaxies with a sudden burst of star formation. We present here a scenario in which blue elliptical galaxies identified in shallow imaging surveys may fail to recover faint features that are indicative of past merger activity using a nearby major merger remnant. Based on deep optical imaging data of the post-merger galaxy, NGC 7252, we demonstrate that the galaxy can appear as an elliptical galaxy if it is observed at higher redshifts. The main body and the low surface brightness merger features found at the outskirts of the galaxy are blue in the optical g – r colour map. We argue that the higher-redshift blue elliptical galaxies discovered in surveys as shallow as the SDSS or DECaLS may be advanced mergers whose defining tidal features fall below the detection limits of the surveys. This should be taken into consideration during the morphological classification of these systems in future and ongoing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Disturbed, diffuse, or just missing? A global study of the H I content of Hickson compact groups

Hickson compact groups (HCGs) are dense configurations of four to ten galaxies, whose H I morphology appears to follow an evolutionary sequence of three phases, with gas initially confined to galaxies, then significant amounts spread throughout the intra-group medium, and finally with almost no gas remaining in the galaxies themselves. It has also been suggested that several groups may harbour a diffuse H I component that is resolved out by interferometric observations. The H I deficiency of HCGs is expected to increase as the H I morphological phase progresses along the evolutionary sequence. If this is the case, H I deficiency would be a rough proxy for the age and evolutionary state of a HCG. We aim to test this hypothesis for the first time using a large sample of HCGs and to investigate the evidence for diffuse H I in HCGs. We performed a uniform reduction of all publicly available VLA H I observations (38 HCGs) with a purpose-built pipeline that also maximises the reproducibility of this study. The resulting H I data cubes were then analysed with the latest software tools to perform a manual separation of emission features into those belonging to galaxies and those extending into the intra-group medium. We thereby classified the H I morphological phase of each group as well as quantified their H I deficiency compared to galaxies in isolation. We find little evidence that H I deficiency can be used as a proxy for the evolutionary phase of a compact group in either of the first two phases, with the distribution of H I deficiency being consistent in both. However, for the final phase, the distribution clearly shifts to high H I deficiencies, with more than 90% of the expected H I content typically missing. Across all HCGs studied, we identify a few cases where there is strong evidence for a diffuse gas component in the intra-group medium, which might be detectable with improved observations. We also classify a new sub-phase where groups contain a lone H I -bearing galaxy, but are otherwise devoid of gas. The new morphological phase we have identified is likely the result of an evolved, gas-poor group acquiring a new, gas-rich member. The large spread of H I deficiencies in the first two morphological phases suggests that there is a broad range of initial H I content in HCGs, which is perhaps influenced by large-scale environment, and that the timescale for morphological changes is, in general, considerably shorter than the timescale for the destruction or consumption of neutral gas in these systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Facet-Dependent Ni Segregation in a Micron-Sized Single-Crystal Li 1.2 Ni 0.2 Mn 0.6 O 2 Cathode

Elemental surface segregation in cathode materials is critical for determining the phase and interfacial reaction between electrode and electrolyte, which consequently affects the electrochemical properties. Single-crystal cathode of Li 1.2 Ni 0.2 Mn 0.6 O 2 and Li 1.2 Ni 0.2 Mn 0.6 O 1.95 F 0.05 with an octahedral morphology of (102) and (003) dominated facets have been manifested to show enhanced electrochemical properties. However, the surface structural features of such single crystals have not been investigated. Herein, using scanning transmission electron microscopy, energy dispersive X-ray spectroscopy, and electron energy loss spectroscopy, we probe the elemental surface segregation characteristics in these single-crystal cathode. We reveal that Ni surface segregation shows dependence on the crystal facet such that it occurs on crystal facets with a mix of cations and anions, but not on the facets with only cations or anions. Furthermore, facet-dependent surface reconstructions are observed, featuring a spinel-like structure at the Ni-rich facet but rock-salt structure at the facet without Ni segregation. The commonly known Mn reduction appears at the single crystal surfaces, more pronounced at the facet without Ni segregation. We further reveal that fluorination leads to the stabilization of surface oxygens. In conclusion, this study provides detailed structural and chemical information about the facet-dependent Ni surface segregation and the resulted phase formation in the rather less explored micron-sized octahedral Li 1.2 Ni 0.2 Mn 0.6 O 2 and Li 1.2 Ni 0.2 Mn 0.6 O 1.95 F 0.05 single crystals, which is key to further exploration of electrochemical properties of cathode in the form of micro-sized single crystal.

25 ENERGY STORAGE↗

A robust approach to 3D neuron shape representation for quantification and classification

We consider the problem of finding an accurate representation of neuron shapes, extracting sub-cellular features, and classifying neurons based on neuron shapes. In neuroscience research, the skeleton representation is often used as a compact and abstract representation of neuron shapes. However, existing methods are limited to getting and analyzing “curve” skeletons which can only be applied for tubular shapes. This paper presents a 3D neuron morphology analysis method for more general and complex neuron shapes. First, we introduce the concept of skeleton mesh to represent general neuron shapes and propose a novel method for computing mesh representations from 3D surface point clouds. A skeleton graph is then obtained from skeleton mesh and is used to extract sub-cellular features. Finally, an unsupervised learning method is used to embed the skeleton graph for neuron classification. Extensive experiment results are provided and demonstrate the robustness of our method to analyze neuron morphology.

3D neuron morphology↗

Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation

The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. Here, this review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies.

Materials science↗

Effects of Asymmetric Molecular Architecture on Chain Stretching and Dynamics in Miktoarm Star Copolymers

We use broad-band dielectric spectroscopy (BDS) and small-angle X-ray scattering (SAXS) to investigate the impact of architectural asymmetry in the miktoarm star copolymer on the dielectric polymer relaxations. The miktoarm copolymers studied contain one or two polystyrene (PS) chains of constant molecular weight and two identical poly(cis-1,4-isoprene) (PI) chains with varied molecular weights. Using the chains in the PI block as dielectric probes, we find that the architecturally asymmetric miktoarm star copolymer systems (PSPI 2 ) feature distributions in chain relaxation times and dielectric relaxation strengths that are not dependent on molecular weight or morphology, in stark contrast to the effects of morphological confinement observed for symmetric diblock systems (PS-b-PI or PS 2 PI 2 ). Along with evidence from the SAXS measurements regarding phase separation, these results are attributed to influences from chain stretching within the framework of the Gaussian chain model for block copolymer systems. As such, the molecular architecture in block copolymers happens to be a versatile handle to control polymer chain dynamics and, ultimately, the macroscopic physicochemical properties in architecturally complex polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of substrate misorientation on the optical properties of Mg-doped GaN

The GaN substrate miscut angle has a significant effect on the optical properties of Mg-doped GaN grown by metal-organic chemical vapor deposition. We have studied the optical properties of epilayers grown on c-plane GaN wafers with nominal miscut angles of 0.3° and 4° toward the [11¯00] direction. Periodic surface steps are observed in thin films grown on 0.3° miscut substrates. The step separation and height, as well as the surface roughness, increase with layer thickness, leading to a decrease in Mg doping efficiency. For films grown on 4° miscut substrates, step bunching causes the formation of visually observable wavy features on the film surface with strong spatial variations in cathodoluminescence characteristics, indicating a significant effect of surface morphology on the nature of Mg incorporation and p-type characteristics.

Liu, Hanxiao (ORCID:0000000331067542)↗

Mechanistic assessment of tolerance to iron deficiency mediated by Trichoderma harzianum in soybean roots

Abstract Aims Iron (Fe) deficiency in soil is a continuing problem for soybean (Glycine max L.) production, partly as a result of continuing climate change. This study elucidates how Trichoderma harzianum strain T22 (TH) mitigates growth retardation associated with Fe-deficiency in a highly sensitive soybean cultivar. Methods and Results Soil TH supplementation led to mycelial colonization and the presence of UAOX1 gene in roots that caused substantial improvement in chlorophyll score, photosynthetic efficiency and morphological parameters, indicating a positive influence on soybean health. Although rhizosphere acidification was found to be a common feature of Fe-deficient soybean, the upregulation of Fe-reductase activity (GmFRO2) and total phenol secretion were two of the mechanisms that substantially increased the Fe availability by TH. Heat-killed TH applied to soil caused no improvement in photosynthetic attributes and Fe-reductase activity, confirming the active role of TH in mitigating Fe-deficiency. Consistent increases in tissue Fe content and increased Fe-transporter (GmIRT1, GmNRAMP2a, GmNRAMP2b and GmNRAMP7) mRNA levels in roots following TH supplementation were observed only under Fe-deprivation. Root cell death, electrolyte leakage, superoxide (O2•–) and hydrogen peroxide (H2O2) substantially declined due to TH in Fe-deprived plants. Further, the elevation of citrate and malate concentration along with the expression of citrate synthase (GmCs) and malate synthase (GmMs) caused by TH suggest improved chelation of Fe in Fe-deficient plants. Results also suggest that TH has a role in triggering antioxidant defence by increasing the activity of glutathione reductase (GR) along with elevated S-metabolites (glutathione and methionine) to stabilize redox status under Fe-deficiency. Conclusions TH increases the availability and mobilization of Fe by inducing Fe-uptake pathways, which appears to help provide resistance to oxidative stress associated with Fe-shortage in soybean. Significance and Impact of the Study These findings indicate that while Fe deficiency does not affect the rate or degree of TH hyphal association in soybean roots, the beneficial effects of TH alone may be Fe deficiency-dependent.

59 BASIC BIOLOGICAL SCIENCES↗

Cis-regulatory evolution shapes facial diversity in birds and mammals

Birds and mammals exhibit extraordinary facial diversity, reflecting adaptations to distinct ecological niches and feeding strategies. While core face-building developmental programs are conserved and orchestrated by interactions between ectodermal organizers and the underlying mesenchyme, mechanisms driving facial shape variation remain poorly understood. Here, we integrate single-cell transcriptomic and chromatin accessibility profiling of mouse and chicken developing face to construct a comparative regulatory map. Although both ectodermal and mesenchymal populations display distinct regulatory features in each species, the mesenchyme exhibits markedly greater divergence, pointing to its central role in shaping facial morphology. We further reveal unexpected molecular complexity in the main face-shaping organizer, including a mouse-specific Shh/Wnt5a expression domain. At key morphogen loci (Bmp4, Fgf8, and Wnt5a), conserved and lineage-specific enhancers exhibit spatially restricted activity patterns that mirror divergent signaling domains. These findings demonstrate how cis-regulatory evolution modulates conserved developmental programs to generate morphological novelty, providing a valuable resource for studying vertebrate facial evolution.

Kyomen, Stella [Max Planck Institute for Evolution↗

Towards libraries of different ultrasmall amorphous silica cage topologies

Cage topology controlled at the nanometer length scale is expected to enable original functionalities, e.g., in catalysis and therapeutics. Cages are fundamental structural motifs of clathrates and their topological duals, Frank-Kasper phases, and are constituents of mesoporous silica frameworks. However, with one exception, they have not been synthesized as discrete particles. By varying reactant ratios of surfactant, oil, and silane, we report the discovery of 5(12)6(2) and 5(12)6(8) amorphous silica polyhedra, each coexisting with the previously identified 5(12) cage, using combined cryo-transmission electron microscopy (cryo-TEM) and single-particle reconstruction (SPR). Notably, the 5(12)6(8) polyhedron represents a topology not previously observed in mesoporous silica frameworks. Control over structural features is demonstrated, and insights into cage formation mechanisms are provided. Structural outcomes are summarized in a ternary morphology diagram alongside prior results, bridging serendipitous discovery and intentional design of silica cages displaying a level of control over silica polymerization rivaling nature.

Jang, Dong June [Department of Materials Science a↗

Effect of 316 stainless steel powder processing conditions on microstructure

One parameter that has both economic and performance effects in the manufacturing of steel parts is the powder feedstock used. 316 L steel powder can be produced through water atomization or gas atomization, where both the powder size and the atomization process determine the cost of powder feedstock. Gas atomized powder is spherical and has a lower oxygen content than water atomized powder, making it the preferred choice for performance, but comes at a higher financial cost. Here, in this study, various 316 L powder batches are characterized to understand physical properties and microstructural variations. Density and flowability were determined using gas pycnometry and Hall flow tests. Powder morphology and porosity were qualitatively analyzed via optical microscopy and scanning electron microscopy, Finally, transmission electron microscopy was used to determine changes in phases present. Spherical gas atomized powder of 30–100 μm contained Mn$-$Si rich oxides both on the surface and within the matrix. Meanwhile, irregular water atomized powder 30 μm in diameter contained silicon oxides without manganese. All powder particles contained a nickel rich cellular structure which was shown to support the formation of additional phases. While literature has observed general microstructural features across 316 L powder particles, transmission electron microscopy (TEM) in this study has identified variations in precipitation and cell structures. Information regarding morphology, flowability, density, and phase distributions can be applied to understand variations in part consolidation, which will in turn show which powder aspects are significant for production.

Chemical segregation↗

Unveiling 3D Morphology of Multiscale Micro-Nanosilver Sintering for Advanced Electronics Manufacturing by Ptychographic X-ray Nanotomography

The sintering processing–structure–property relationship of a multiscale silver materials is investigated: microparticles with nanofeatures, particularly on their three-dimensional (3D) morphology. The target application is to replace conventional lead-based solders in advanced electronic manufacturing. Unlike lead-based solders, silver powders are suited to satisfy increasingly demanding mechanical, electrical, and thermal requirements, meanwhile being free of health effect. Sintering the material at a low temperature and without applied pressure are desirable conditions, which results in a preferred use of silver nanoparticles, as nanofeatures have higher driving force to sinter with the decrease in particle size. However, nanosized powders present potential health/environmental effects. To address the trade-off between the benefits and shortcomings of nano-versus microparticles, this work studies a novel multiscale silver paste, namely micron-sized powders with nanosized features. To get quantitative 3D visualization of micro- and nanoscale features, ptychographic X-ray computed nanotomography is applied. The correlations between conditions (thermal aging, pressure, and substrate metallization), mechanical properties, and morphological parameters are established. Finally, using novel 3D X-ray nanoimaging technique, it is demonstrated that one can design multiscale materials while balancing complex demands required in advanced electronics manufacturing and research directions in materials design and characterization.

36 MATERIALS SCIENCE↗

Jet classification using high-level features from anatomy of top jets

Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to less interpretable models, emphasizing the need to understand the decision-making process and to identify the high-level features (HLFs) crucial for explaining jet classification. To address this, we consider the top jet tagging problems and introduce an analysis model (AM) that analyzes selected HLFs designed to capture important features of top jets. Our AM mainly consists of the following three modules: a relation network analyzing two-point energy correlations, mathematical morphology and Minkowski functionals for generalizing jet constituent multiplicities, and a recursive neural network analyzing subjet constituent multiplicity to enhance sensitivity to subjet color charges. We demonstrate that our AM achieves performance comparable to the Particle Transformer (ParT) while requiring fewer computational resources in a comparison of top jet tagging using jets simulated at the hadronic calorimeter angular resolution scale. Furthermore, as a more constrained architecture than ParT, the AM exhibits smaller training uncertainties because of the bias-variance tradeoff. We also compare the information content of AM and ParT by decorrelating the features already learned by AM. Lastly, we briefly comment on the results of AM with finer angular resolution inputs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗