Current Applied Physics最新文献

We investigated the compositional and temperature (T) dependences of vibrational frequencies in Hofmann-type Fe(L)₂[M(CN)₄] spin-crossover (SCO) coordination polymers in which {M = Ni, Pd or Pt with L = pyridine (py)}, or {L = 3-Cl-py or 3-methylpy with M = Ni}, using Raman spectroscopy. The SCO-driven peak shifts (in wavenumber) ranged up to ∼170 cm⁻¹, manifesting significant spin-dependent structural evolutions. Furthermore, there appear clear HS signatures even at T ≪ T_SCO for L = 3-Cl-py or 3-methylpy implying the steric effects of the organic ligands on the HS trapping. Meanwhile, for L = py, such HS trapping at the low temperature was not significant although some spectra taken under high laser fluence exhibit light-induced excited spin state trapping (LIESST) effect. The mechanism of the LIESST is discussed in detail in terms of the M d – C 2sp hybridization effects.

The unique properties of ferrimagnets including easy detection of their dynamic and static states, strong resistance to external disturbances, and rapid dynamic characteristics, have made them attractive in the spintronics community. Our study focuses on the engineering of these magnetic properties of ferrimagnets, particularly employing a GdFeCo alloy, a prominent ferrimagnetic material, by utilizing magnetron sputtering. A series of GdFeCo films are fabricated by altering their thicknesses and working pressure during the sputtering process. Our experimental results reveal that these sputtering parameters significantly influence a Gd composition within the films, which in turn affects critical properties of ferrimagnets such as magnetic anisotropy, and magnetic moment compensation temperature. By precisely controlling these sputtering parameters, we successfully tailored the magnetic properties of the GdFeCo thin films with desired properties, offering new possibilities for the creation of sophisticated magnetic materials tailored to specific technological needs.

Applying Cs_xFA_1-xPbI₃ perovskite is a useful strategy for synthesizing high-efficiency organic-inorganic lead halide perovskite solar cells because it improves the stability of the perovskite structure. High concentration of cesium (Cs) in CsFAPbI₃ synthesized under ambient conditions typically lead to phase separation due to δ-CsPbI₃ formation and moisture, thereby reducing light absorption and increasing non-radiative recombination. To counter this, we fabricated the mixed halide Cs_0.22FA_0.78Pb(I_1-xBr_x)₃ perovskite films. Introducing bromine (Br) content effectively reduced the δ-CsPbI₃ formation and grain boundaries, thus suppressing the non-radiative recombination between perovskite and charge transport layers. Employing this approach, our perovskite solar cells with a 10 % Br concentration achieved a power conversion efficiency of 15.81 %. This demonstrates the potential of Br incorporation in enhancing the stability and efficiency of perovskite solar cells.

This work introduces an ultra-thin tunable ultra-wideband (UWB) metasurface absorber (MSA) for the terahertz (THz) gap. The polarization-insensitive MSA provides an absorptivity ($A\left(f\right)$) ≥ 90% from 0.1 to 11.5 THz, corresponding to 196.6% fractional bandwidth. The usage of resonant slots engraved on top patterned graphene sheet ($G_{pat}$) and strong plasmonic coupling in the Fabry-Perot cavity formed between top $G_{pat}$ and bottom continuous graphene ($G_{cont}$) in bilayer stack configuration ensures absorptivity over a UWB THz spectrum. An equivalent circuit model (ECM) closely follows the $A\left(f\right)$ response of the proposed MSA. The proposed DC-biasing mechanism can regulate the chemical potential (${\mu }_c$) of the connected $G_{cont}$ efficiently. A DC bias voltage of 0 to 6.1 V is adequate to vary ${\mu }_c$ of $G_{cont}$ from 0 to 0.6 eV for achieving tunable $A\left(f\right)$. The structure maintains its ultra-thin nature and has a thickness of only ${\lambda }_0$/1500, where ${\lambda }_0$ is the free space wavelength calculated at 0.1 THz. In addition, the periodicity is only ${\lambda }_0$/300. The MSA also provides stable absorption response from 0.1 to 11.5 THz with $A\left(f\right)$ ≥ 80% for incidence angle (θ) up to ${60}^{\circ }$ under both transverse magnetic (TM) and transverse electric (TE) polarization.

Solution-processed amorphous oxide semiconductor thin films contain poor metal-oxygen-metal (M-O-M) networks and numerous impurities, making it difficult to manufacture high-performance semiconductor devices with excellent stability. In this study, we enhance the electrical performance and device stability of solution-processed oxide thin-film transistors (TFTs) by incorporating water molecular oxidants. In solution, a water molecule can be easily incorporated by adding deionized water (DW) to the precursor solution. The DW-incorporated precursor solutions induced the production of oxide semiconductor thin films with improved M-O-M networks and fewer defect states. Therefore, compared to conventional case, the DW-incorporated indium zinc oxide (InZnO) TFT showed improved device performances and significantly reduced changes of threshold voltage under positive gate bias stress and negative gate bias/illumination stress conditions. This approach of incorporating DW into the precursor solutions provides a promising route for fabricating high-quality amorphous semiconductor films and transistor devices.

Recent advancements in artificial intelligence (AI) techniques have significantly influenced daily life and the forefront of research and development. Data-driven research using AI accelerates the resolution of complex problems and aids in uncovering previously unknown knowledge and scientific discoveries. In this study, we propose a data-driven approach for investigating perovskite solar cells, a vibrant area within renewable energy applications. This approach incorporates the generation of a robust dataset, developing an interpretable machine learning model based on knowledge-based feature selection, and analyzing the impacts of material properties on the device performance. Through this framework, we successfully constructed accurate predictive models for the efficiency of perovskite solar cells and assessed the importance of each feature. Our analysis demonstrates that our models effectively capture existing knowledge about perovskite solar cells and can potentially inform the design of new perovskite solar cell configurations.