We theoretically demonstrate the coupling between the unit cells and the interaction between constituents within each cell in metamaterials consisting of stacked split ring resonator arrays which are embedded in a homogeneous dielectric. It is found that the resonant frequency due to plasmon hybridization depends on the symmetry of resonance modes. Both for the first and third order plasmon resonances, we show that the resonances at lower frequency are not sensitive to the variation of lattice density, while the resonances at higher frequency rely on the coupling between cells due to the symmetric distribution of current. The underlying physics is qualitatively interpreted according to the quasistatic electric and magnetic dipole coupling model combined by the calculated field distributions.
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http://dx.doi.org/10.1088/0953-8984/23/21/215303 | DOI Listing |
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December 2024
School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China.
The development of highly stable and strongly active electrode materials for sodium-ion batteries (SIBs) and overall water splitting (OWS) is critical in sustainable energy storage and conversion systems. Here, a new electrode material N-Fe-C@NbCT is introduced, with a layered sandwich structure consisting of N-doping Fe-MOF derived-nanorods (Fe-C) and NbCT MXenes. Specifically, NbCT obtained by etching NbAlC with HF acid is used as the main body to construct the layered sandwich structure with Fe-C as the filler.
View Article and Find Full Text PDFInorg Chem
December 2024
Laboratory of Complex Heterostructures and Multifunctional Materials, National Institute of Materials Physics, Atomistilor 405A, Magurele 077125, Romania.
CuZnSnSe (CZTSe) is a promising material for thin-film solar cells due to its suitable band gap, high absorption coefficient, and composition of earth-abundant and nontoxic elements. In this study, we prepared CZTSe thin films from Cu/SnSe and ZnSe stacks using a two-step annealing process. Initially, Cu-Sn-Se (CTSe) films were synthesized by sequential deposition and annealing of Cu and SnSe precursors in either a selenium (Se) or tin-selenium (Sn+Se) atmosphere.
View Article and Find Full Text PDFChem Sci
November 2024
Department of Chemical Sciences, Indian Institute of Science Education and Research (IISER) Kolkata Mohanpur West Bengal India-741246
Red emission in crystals has been observed with an ultra-small-single-benzenic -fluorophore () with a molecular weight (MW) of only 197 Da, bettering the literature report of fluorophores with the lowest MW = 252 Da. Supramolecular extensive hydrogen-bonding and J-aggregate type centrosymmetric discrete-dimers or a 1D chain of s led to red emission ( = 610-636 nm) in crystals. Unlike in the solution phase showing one absorption band, in thin films and in crystals the transition from the S state to both the S state and S state becomes feasible.
View Article and Find Full Text PDFPhys Chem Chem Phys
December 2024
Univ. Artois, CNRS, Centrale Lille, Univ. Lille, UMR 8181, Unité de Catalyse et de Chimie du Solide (UCCS), F-62300 Lens, France.
The effects of biaxial tensile and compressive strain on the structural, electronic, and photocatalytic properties of tetragonal [001] (SnO)/(TiO) superlattices have been theoretically explored using density functional theory (DFT) calculations. Various stacking periodicities between SnO layers and TiO layers, including ( = ), (, 1), and (1, ) were studied in the context of water splitting for hydrogen production. The results reveal that the (1, ) stacking periodicity exhibit the highest bulk modulus, Poisson's ratio, and Debye temperature values.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Electrical Engineering, Qatar University, Doha 2713, Qatar. Electronic address:
Sepsis, a life-threatening condition triggered by the body's response to infection, remains a significant global health challenge, annually affecting millions in the United States alone with substantial mortality and healthcare costs. Early prediction of sepsis is critical for timely intervention and improved patient outcomes. This study introduces an innovative predictive model leveraging machine learning techniques and a specific data-splitting approach on highly imbalanced electronic health records (EHRs).
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