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Decay rates of optical modes unveiling the island structures in mixed phase space
No full textWe explore the decay rates of optical modes in asymmetric microcavities with mixed phase space across a wide range of wavelengths that extend deep into the semiclassical, i.e., short-wavelength, limit. Implementing an efficient numerical method, we computed 106 eigenmodes and discovered that certain decay rates form sequential separate branches with increasing wave number that eventually merge into smooth curves. The analysis of the localization properties and Husimi distributions reveals that each branch corresponds to a periodic orbit in the closed classical system. Our findings show that these decay rates gradually resolve the structure of the islands in mixed phase space as we approach the short-wavelength limit. We present an effective semiclassical model incorporating wave-number-dependent localization, Fresnel reflection, and the Goos-H & auml;nchen shift and demonstrate that these effects are crucial in accounting for the observed branches of decay rate curves.
Colloidal-nanoparticle-derived nickel/ferric oxide heterointerfaces for promoting the alkaline oxygen evolution reaction
No full textHeterointerface engineering is an effective strategy to enhance electrocatalytic activity for water splitting by binding two different materials. Specifically, it offers prospects in creating viable transition-metal-based anode materials for catalyzing the oxygen evolution reaction (OER). However, despite its promise, metal/metal oxide heterointerface engineering has not been comprehensively explored for maximizing the electrocatalytic performance, that is, for minimizing the OER overpotential and maintaining the physicochemical characteristics of the catalyst during operation. Therefore, to resolve these issues, the present study was aimed at synthesizing colloidal nanoparticles (NPs) in mixed form at various Ni/Fe ratios (100 : 0 to 0 : 100) to create heterointerfaces between metallic Ni and Fe2O3 NPs. Among the prepared NPs, the 75 : 25 sample annealed under H2/Ar atmosphere recorded the highest alkaline water oxidation activity (199 mV at 10 mA cm-2) with long-term durability for five days, indicating that the 75 : 25 ratio was the optimal composition for generating abundant Ni/Fe2O3 heterointerfaces. The practical applicability of the 75 : 25 sample was confirmed by its remarkable performance as an anode catalyst for an anion exchange membrane water electrolyzer (AEMWE). The outstanding electrocatalytic performance of the 75 : 25 specimen was induced not only by the interparticle interactions between Ni and Fe2O3 NPs, but also by the intraparticle interactions within the heterostructured NPs. Overall, this report illustrates the benefits of Ni/Fe2O3 heterointerface engineering in obtaining highly efficient anode catalysts for AEMWEs.
High glucose induces FABP3-mediated membrane rigidity via downregulation of SIRT1
No full textHigh glucose induces an atypical lipid composition in skeletal muscle, leading to loss of muscle mass and strength. However, the mechanisms underlying this glucose toxicity are not fully understood. Analysis of genes associated with a phenotype using the BXD phenome resource revealed that increased Fabp3 expression in skeletal muscle correlated with hyperglycemia. FABP3 expression was also increased in hyperglycemic mouse models such as leptin-deficient ob/ob, Ins2Akita, and high-fat fed mice, as well as in aged mice. In cultured myotubes, high glucose elevated the mRNA and protein levels of FABP3, which contributes to decreased membrane fluidity, along with other mechanisms. FABP3 expression was dependent on the NAD+/NADH ratio and SIRT1 activity, suggesting a mechanism by which FABP3 is upregulated in hyperglycemic conditions. Our findings propose that FABP3 links hyperglycemia to atypical membrane physicochemical properties, which may weaken contractile and metabolic function, particularly in skeletal muscle.
Ganglioside-incorporating lipid nanoparticles as a polyethylene glycol-free mRNA delivery platform
No full textIncorporation of polyethylene glycol (PEG) is widely used in lipid nanoparticle (LNP) formulation in order to achieve adequate stability due to its stealth properties. However, studies have detected the presence of anti-PEG neutralizing antibodies after PEGylated LNP treatment, which are associated with anaphylaxis, accelerated LNP clearance and premature release of cargo. Here, we report the development of LNPs incorporating ganglioside, a naturally occurring stealth lipid, as a PEG-free alternative. Physicochemical characterization showed that ganglioside-LNPs exhibited superior stability throughout prolonged cold storage compared to stealth-free LNPs, preventing particle aggregation. Additionally, there was no significant change in particle size after serum incubation, indicating the ability of ganglioside to prevent unwanted serum protein adsorption. These results exemplify the effective stealth properties of ganglioside. Furthermore, ganglioside-LNPs exhibited significantly higher mRNA transfection in vivo after intravenous administration compared to stealth-free LNPs. The ability of ganglioside to confer excellent stealth properties to LNPs while still enabling in vivo mRNA expression makes it a promising candidate as a natural substitute for immunogenic PEG in mRNA-LNP delivery platforms, contributing to the future advancement of gene therapy.
Area-Efficient Non-Binary LDPC Decoder With Column-Wise Trellis Min-Max Algorithm
No full textConsidered a next-generation error-correction solution, non-binary low-density parity-check (NB-LDPC) codes exhibit remarkable correcting capabilities, outperforming binary counterparts for severe channel conditions. However, contemporary decoder designs encounter challenges due to the demanding hardware resources required by their high processing complexity. In this work, we propose a novel column-wise trellis min-max (CW-TMM) algorithm, which significantly reduces the sorter overheads in the existing TMM method without degrading the error-correcting power. We also deploy the message compression to the trellis-based algorithm for effectively reducing hardware costs, even allowing the storage-aware long codes by accommodating large-sized on-chip memories. Through the integration of advanced low-cost optimization schemes together, the prototype CW-TMM decoder in a 28-nm CMOS technology for 4-kB 0.9-rate NB-LDPC codes demonstrates a 54% reduction in on-chip memory size and a 63% decrease in decoding complexity, enhancing the area efficiency by more than 2.4 times than the state-of-the-art approaches.
Very high frequency (∼100 MHz) plasma enhanced atomic layer deposition high-κ hafnium zirconium oxide capacitors near morphotropic phase boundary with low current density & high-κ for DRAM technology
No full textHafnium dioxide-based ferroelectric (FE) films are emerging as pivotal materials for advanced memory storage and neuromorphic computing, particularly in ultra-scaled dynamic random-access memory (DRAM) technologies. To meet the stringent DRAM performance requirements-dielectric constants (kappa) exceeding 60 and leakage current densities below 10-6 A cm-2 at 0.8 V-hafnium zirconium oxide (HZO) films engineered near the morphotropic phase boundary (MPB) are leading candidates. These films offer a favorable balance of high dielectric properties and reduced equivalent oxide thickness while managing leakage. However, film thinning often escalates leakage currents, presenting a significant design challenge. Moreover, interfacial damage induced by conventional deposition techniques can undermine dielectric stability. Here, we present a novel approach utilizing very high frequency (VHF, 100 MHz) plasma-enhanced atomic layer deposition (PE-ALD) to fabricate 4.5 nm HZO films with superior crystalline quality and minimized oxygen vacancies. This method yields an impressive dielectric constant of 64.47, markedly surpassing radio frequency-deposited counterparts. Notably, at elevated temperatures up to 389 K, the dielectric constant reaches 69.9, approaching the theoretical tetragonal-phase limit. Our results demonstrate the transformative potential of VHF PE-ALD in optimizing HZO film properties, establishing a compelling pathway for future high-performance DRAM applications.
Heterogeneous pressure on croplands from land-based strategies to meet the 1.5 °C target
No full textAchieving the 1.5 degrees C target outlined in the Paris Agreement necessitates coordinated global efforts, particularly in the form of ambitious climate pledges. While current discussions primarily focus on energy and emissions pathways, the fine-scale, location-specific consequences for agriculture, land systems and sustainability remain uncertain. Here we evaluate global land-system responses at 5-km2 resolution in pursuit of the 1.5 degrees C target through recent country-specific climate pledges. Contrary to previous studies predicting cropland expansion under a 1.5 degrees C scenario, we reveal a 12.8% reduction in cropland area when accounting for cross-sectoral impacts of climate pledges and land-use intensity. The reduction is most pronounced in South America (23.7%), with the global south comprising 81% of the countries worldwide expected to experience cropland loss. Food security in the Global South faces additional pressure due to a projected 12.6% reduction in export potential from the global north.
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No full textDisclosed are a perovskite color converter and a method for manufacturing the same. In order to maintain strong physical properties, the siloxane resin is synthesized in two steps. The silane precursor performs siloxane bond through a non-aqueous sol-gel reaction to form a siloxane resin, and a bond between methacrylate group, and a bond between methacrylate group and an organic ligand are formed through a secondary cross-linking reaction
Extended multiphysics-informed neural network for conjugate heat transfer problems
No full textPhysics-informed neural networks have gained prominence as an innovative framework that combines machine learning and physics knowledges to solve complex physical problems. By integrating the partial differential equations of a physical system into the neural network architecture, physics-informed neural networks can approximate solutions for the system under given boundary and initial conditions. This allows the models to capture the underlying dynamics of the system while adhering to physical constraints. Despite their advantages, physics-informed neural networks exhibit performance degradation when applied to multiphysics and multidomain problems. Specifically, conjugate heat transfer problems, which are representative of such problems, tend to exhibit low accuracy along with training instability and convergence issues when conventional physicsinformed neural networks are used. Therefore, in this study, we propose a novel physics-informed neural network method called Extended Multiphysics-informed Neural Network to improve performance in solving conjugate heat transfer problems. The extended multiphysics-informed neural network framework uses distinct sub-networks designed to capture the characteristics of solid and fluid domains, enabling the accurate simulation of abrupt temperature changes at solid-fluid interfaces. Additionally, a novel training scheme incorporating physical phenomena ensures the stability and convergence of the model. The efficiency of extended multiphysics-informed neural network is validated through its application to representative two-dimensional conjugate heat transfer problems, demonstrating significant improvements in predictive performance and computational efficiency compared to existing methods. This study highlights the potential of advanced physics-informed neural network method for solving complex multiphysics problems.