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Site selectivity of single dopant in high-nickel cathodes for lithium-ion batteries
No full textImproving the structural stability of high-capacity high-Ni cathodes through doping has been investigated, but the structural stabilization mechanisms of dopants remain unclear. This study focused on unraveling the influence of individual dopants, Aluminium, Titanium, or Zirconium, on the structural stabilization of high-Ni cathodes. X-ray Diffraction and High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF-STEM) were employed for quantitative analysis of cation mixing, and for the first time, HAADF-STEM and deep learning were combined to improve the accuracy and efficiency of the analysis. The atomic-scale energy dispersive spectroscopy analysis identified transition metal sites as the primary doping sites in doped high-Ni cathodes. Density funtional theory calculations revealed that dopants enhance the interatomic bonds between Ni and O, thereby inhibiting cation mixing. Among the studied dopants, Ti was found to have the most substantial influence in enhancing structural stability. This study contributes to an understanding of single dopant on the structural stability of high-Ni cathodes, aiding the design of next-generation lithium-ion batteries. © 2024 The Authors11Nsciescopu
Object Function Retrieval by Model-Based Optimization in Fourier Holographic Endoscopy
No full textHolographic endoscopes have garnered extensive attention not only for their compactness but also for their high-resolution and wide-field imaging capabilities. However, their practical use is challenging due to the reliance on Fesnel approximations in the underlying image reconstruction protocol, limiting their real-world applications. In this study, we present a model-based optimization algorithm that successfully retrieves an object function in a fiber bundle holographic endoscope. By developing a mathematical model that eliminates the need for approximations, our optimization extends the working range and expands the field of view of a fiber bundle holographic endoscope while preserving its advantages. These advancements significantly enhance the utility and feasibility of holographic endoscopes for various diagnostic procedures. © 2024 American Chemical Society.11Nsciescopu
Repeatability and Reproducibility in the Chemical Vapor Deposition of 2D Films: A Physics-Driven Exploration of the Reactor Black Box
No full textAlthough chemical vapor deposition (CVD) remains the method of choice for synthesizing defect-free and high-quality 2D films (such as graphene and h-BN), the method has serious issues with process repeatability and reproducibility. This makes it difficult to build up from the literature, test a hypothesis quickly, or scale up a process. The primary reason for this is that the CVD reactor, to this day, remains a black box with a reaction environment that is poorly understood and cannot be measured or monitored directly. Consequently, it is also difficult to study process kinetics and growth mechanisms and correlate experimental results to atomic-level simulations. A possible way to overcome this problem is to use computational fluid dynamics (CFD), both to identify the measurable external (process and reactor) parameters that control the reaction environment and to simulate this reaction environment and understand how it changes when these controllable external parameters are varied. This paper describes how this may be done in practice using the growth of single-layer graphene in a hot-wall tube reactor as the representative case and the CFD toolbox OpenFOAM. Based on our findings, we have shown why it is critical (1) to understand the flow properties inside the reactor and combine it with experimental results to study the growth process for graphene and other 2D films and (2) to measure, monitor, and report all relevant external parameters to ensure process repeatability and reproducibility.11Nsciescopu
Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning
No full textEating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean +/- standard deviation [SD] age = 47.07 +/- 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean +/- SD age = 38.97 +/- 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity. We systematically investigated the heterogeneity of eating behavior traits of healthy adults using unsupervised machine learning and functional connectivity. We identified three distinct subgroups showing different eating behavior traits independent of the degree of obesity.image11Ysciescopu
Capturing Coherent Magnons by Tip-Assisted Terahertz Spectroscopy
No full textOur study highlights the versatility of tip-assisted terahertz spectroscopy in probing coherent magnons, the elementary quanta of spin waves in magnetic materials. We identify two distinct coherent magnon types in canted antiferromagnet YFeO3. The remarkable consistency with far-field terahertz spectroscopy in crucial magnon parameters, such as coherence time and resonance frequency, firmly establishes the credibility of tip-assisted terahertz spectroscopy. Notably, we capture more coherent ferromagnetic magnons near the sample surface, underscoring the strength of the technique. This approach paves the way for local, free-standing, and real-space investigations of spin waves in solid magnets.11Nsciescopu
Classes of intersection digraphs with good algorithmic properties
No full textWhile intersection graphs play a central role in the algorithmic analysis of hard problems on undirected graphs, the role of intersection digraphs in algorithms is much less understood. We present several contributions towards a better understanding of the algorithmic treatment of intersection digraphs. First, we introduce natural classes of intersection digraphs that generalize several classes studied in the literature. Second, we define the directed locally checkable vertex (DLCV) problems, which capture many well-studied problems on digraphs, such as (Independent) Dominating Set, Kernel, and (Formula presented.) -Homomorphism. Third, we give a new width measure of digraphs, bi-mim-width, and show that the DLCV problems are polynomial-time solvable when we are provided a decomposition of small bi-mim-width. Fourth, we show that several classes of intersection digraphs have bounded bi-mim-width, implying that we can solve all DLCV problems on these classes in polynomial time given an intersection representation of the input digraph. We identify reflexivity as a useful condition to obtain intersection digraph classes of bounded bi-mim-width, and therefore to obtain positive algorithmic results. © 2023 The Authors. Journal of Graph Theory published by Wiley Periodicals LLC.11Nsciescopu
Construction of Kuranishi structures on the moduli spaces of pseudo-holomorphic disks: II
No full textThis is the second of a series of two articles in which we provide detailed and self-contained account of the construction of a system of Kuranishi structures on the moduli spaces of pseudo-holomorphic disks. Using the notion of obstruction bundle data introduced in [10], we give a systematic way of constructing a system of Kuranishi structures on the moduli spaces of pseudo-holomorphic disks which are compatible at the boundary and corners. More specifically, it defines a tree-like K-system in the sense of [8, Definition 21.9], [11, Definition 21.9]. The method given in this paper does not only simplify the description of the constructions in the earlier literature, but also is designed to provide a systematic utility tool for the construction of a system of Kuranishi structures in the future research. We also establish its uniqueness.11Nsciescopu
Dichotomy of metallic electron density and charge density wave in 1T-TiSe2
No full text1T-TiSe2 has been intensely investigated for its intriguing charge density wave (CDW) phase, which competes with emerging superconductivity. However, the mechanism of the CDW transition has been elusive with the possibility of strong excitonic interaction. Here, we investigate, using angle-resolved photoelectron spectroscopy and density functional theory calculations, the evolution of the CDW band structure upon electron doping into the surface layer by alkali metal adsorbates. Alkali metal adsorption induces substantial electron donation into the Ti 3d conduction band with strong band renormalization while the Se 4p valance band is contrastingly intact. The density functional theory calculations reveal that only the spectator-type Ti 3d band is selectively doped with the CDW band gap largely intact. This result indicates that the CDW formation is not critically related to the metallic electron density and, in turn, to the excitonic coupling due to its unique multiband configuration. © 2024 American Physical Society.11Nsciescopu
The complement factor H-related protein-5 (CFHR5) exacerbates pathological bone formation in ankylosing spondylitis
No full textAbstract: Ankylosing spondylitis (AS) is a chronic inflammatory disease, characterized by excessive new bone formation. We previously reported that the complement factor H-related protein-5 (CFHR5), a member of the human factor H protein family, is significantly elevated in patients with AS compared to other rheumatic diseases. However, the pathophysiological mechanism underlying new bone formation by CFHR5 is not fully understood. In this study, we revealed that CFHR5 and proinflammatory cytokines (TNF, IL-6, IL-17A, and IL-23) were elevated in the AS group compared to the HC group. Correlation analysis revealed that CFHR5 levels were not significantly associated with proinflammatory cytokines, while CFHR5 levels in AS were only positively correlated with the high CRP group. Notably, treatment with soluble CFHR5 has no effect on clinical arthritis scores and thickness at hind paw in curdlan-injected SKG, but significantly increased the ectopic bone formation at the calcaneus and tibia bones of the ankle as revealed by micro-CT image and quantification. Basal CFHR5 expression was upregulated in AS-osteoprogenitors compared to control cells. Also, treatment with CFHR5 remarkedly induced bone mineralization status of AS-osteoprogenitors during osteogenic differentiation accompanied by MMP13 expression. We provide the first evidence demonstrating that CFHR5 can exacerbate the pathological bone formation of AS. Therapeutic modulation of CFHR5 could be promising for future treatment of AS. Key messages: Serum level of CFHR5 is elevated and positively correlated with high CRP group of AS patients. Recombinant CFHR5 protein contributes to pathological bone formation in in vivo model of AS. CFHR5 is highly expressed in AS-osteoprogenitors compared to disease control. Recombinant CFHR5 protein increased bone mineralization accompanied by MMP13 in vitro model of AS. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.11Nsciescopu
Bioengineering toolkits for potentiating organoid therapeutics
No full textOrganoids are three-dimensional, multicellular constructs that recapitulate the structural and functional features of specific organs. Because of these characteristics, organoids have been widely applied in biomedical research in recent decades. Remarkable advancements in organoid technology have positioned them as promising candidates for regenerative medicine. However, current organoids still have limitations, such as the absence of internal vasculature, limited functionality, and a small size that is not commensurate with that of actual organs. These limitations hinder their survival and regenerative effects after transplantation. Another significant concern is the reliance on mouse tumor-derived matrix in organoid culture, which is unsuitable for clinical translation due to its tumor origin and safety issues. Therefore, our aim is to describe engineering strategies and alternative biocompatible materials that can facilitate the practical applications of organoids in regenerative medicine. Furthermore, we highlight meaningful progress in organoid transplantation, with a particular emphasis on the functional restoration of various organs. © 2024 Elsevier B.V.11Nsciescopu