Journal of Electronic Materials最新文献

This study investigates the enhancement of methylcellulose (MC)-based polymer electrolytes by incorporating zinc-doped calcium ferrite (CaZnFe₂O₄) as a nanofiller. The polymer electrolyte system consists of MC as the host polymer, sodium nitrate (NaNO₃) as the salt, and glycerol as a plasticizer. The structural, electrochemical, and dielectric properties of the prepared samples were analyzed to determine the impact of nanofiller addition. Electrochemical impedance spectroscopy demonstrated a dramatic decrease in bulk resistance from 325 Ω (undoped) to 22 Ω (5 wt.% CaZnFe₂O₄), resulting in a 13.8-fold increase in direct current (DC) conductivity (from 7.73 × 10⁻⁵ S/cm to 1.07 × 10⁻³ S/cm). A shift in tan δ peak frequency from ~324 kHz in solid polymer electrolytes (SPE)-No to ~474 kHz in SPE-N5 evidences enhanced charge carrier mobility (shorter relaxation time). Alternating current (AC) conductivity analysis suggests enhanced ion mobility due to strong polymer-filler interactions. The findings suggest that 5% CaZnFe₂O₄ is the optimal concentration for achieving high ionic conductivity and stable electrochemical performance. This optimized polymer electrolyte system holds potential for applications in energy storage devices, including supercapacitors and rechargeable batteries. X-ray diffraction results indicate a reduction in crystallinity with increasing nanofiller content, favoring ion transport. The scanning electron microscope (SEM) results reveal that the CaZnFe₂O₄ particle size is below 50 nm (~37 nm), which favors the easy dispersion of the nanofiller within the polymer matrix. Fourier-transform infrared spectroscopy showed shifts in O-H (3352 cm⁻¹) and C-O-C (1035 cm⁻¹) bands, confirming strong polymer–filler–ion interactions between the polymer matrix, salt, and nanofiller, facilitating improved ionic conductivity.

The continuous increase in nitrogen oxide (NO_x) emissions from combustion processes, primarily from industrial factories and gasoline-powered vehicles, poses a significant threat to all living organisms. The detrimental effects of NO_x on human health and the environment necessitate concentrated efforts to reduce these emissions. Various strategies have been developed to mitigate NO_x emissions from exhaust fumes. Recently, photocatalytic oxidation technologies for removing NO_x have gained considerable attention within the scientific community. Photocatalytic NO_x removal (PNR) is a promising environmentally friendly and cost-effective method for reducing NO_x concentrations at room temperature. This review categorizes and summarizes the multifaceted aspects of PNR. It provides a concise overview of the photocatalytic mechanism and the NO_x abatement process. Investigations reveal that the efficiency of NO_x removal significantly depends on the bandgap and positions of the valence and conduction band edges, which can be tuned by incorporating suitable dopants or forming heterojunctions. The charge transfer at the photocatalyst surface can be enhanced by employing various methods to tune the surface morphology. This review offers comprehensive details on the semiconductor materials used for NO_x abatement and discusses how their unique properties contribute to efficient PNR.

Graphical Abstract

In this work, we establish models of amorphous Ga₂O₃(a-Ga₂O₃) and its five vacancy defects using molecular dynamics and density functional theory. Through hybrid functional calculations, we calculate the electronic structure, defect formation energies, and optical properties of these models. We explain the structural characteristics of the a-Ga₂O₃ model through bond lengths, bond angles, and radial distribution functions. Based on the coordination of oxygen and gallium atoms in the a-Ga₂O₃ model, the defects are divided into three types of oxygen vacancies (V_O) and two types of gallium vacancies (V_Ga). Electronic structure calculations show that V_O will introduce defect states in the band gap, which are contributed by the O 2p states and Ga 4s or 4p states. The V_Ga will induce spin polarization through the dangling bonds of the 2p orbitals of the surrounding oxygen atoms. The defect formation energy of V_O is lower than that of V_Ga, and a-Ga₂O₃ is more likely to exhibit n-type conductivity. The discussion on the changes in the optical absorption spectra and the imaginary part of the dielectric function reveal that different types of V_O and V_Ga cause optical absorption near 3 eV, 2.88 eV, 3.28 eV, 1.6 eV, and 3.45 eV, respectively. The introduction of defects increases the number of absorption peaks and induces a red shift in the absorption edge. This work provides a reference for explaining the influence mechanism of neutral vacancy defects inside a-Ga₂O₃ materials on the electronic structure and optical properties of the material.

To address the issues of poor load-bearing capacity, low design efficiency, and the difficulty of integrating structural and functional design in current absorbing structures, a study on the integrated reverse design of load-bearing metamaterial absorbers was conducted. A parametric model of the load-bearing metamaterial absorber was developed using a combination of composite core structures and electromagnetic resonant layers. A dataset of electromagnetic and structural properties of the absorber was established. A deep learning-based forward prediction network for the absorber’s absorbance and a design parameter reverse prediction network were developed and trained, achieving high-accuracy predictions of both the absorbance and design parameters. Based on the forward and reverse prediction networks, an integrated reverse design method for metamaterial absorbers was proposed. This method enables the reverse design of the metamaterial absorber on the basis of specified electromagnetic and structural properties while addressing the issue of unattainable design goals through polar coordinate transformation. The method was applied to reverse design tasks for single-frequency, multi-frequency, and broadband load-bearing metamaterial absorbers. The proposed integrated reverse design method holds significant potential for applications in radar stealth material design for military targets, such as naval vessels, and offers broad generalizability and engineering applicability.

We present NanoSensorLab, an open-access MATLAB-based simulation toolbox grounded in Mie scattering theory for the advanced modeling and optimization of plasmonic nanoparticle-based sensors. The toolbox comprises two integrated modules: Nanoscattering, which computes scattering (Q_sca), absorption (Q_abs), and extinction (Q_ext) efficiencies alongside key optical metrics such as peak wavelength, line width, and quality factor (QF); and Nanosensor, which evaluates sensor performance parameters including sensitivity (S) and figure-of-merit (FOM). NanoSensorLab supports multilayered spherical geometries, nanoshells, nanomatryoshkas, and gain-assisted configurations, and incorporates a material library that includes noble metals, transition metal nitrides, and graphene with user-defined optical properties. The toolbox enables rapid design of high-performance LSPR-based sensors and facilitates parametric studies via an intuitive graphical interface. Simulations demonstrate that graphene-integrated TiN-based nanomatryoshkas can achieve sensitivities up to 925.28 nm/RIU, representing a 125.52% enhancement over conventional designs. Benchmarking against COMSOL Multiphysics validates the numerical accuracy of the implementation. NanoSensorLab offers a streamlined, customizable platform for designing plasmonic biosensors targeting biomedical diagnostics such as glucose monitoring and cancer cell detection. The toolbox is freely available at: https://github.com/aloksinghphy/Toolbox.

Understanding the mechanisms of charge storage in supercapacitors is crucial for optimizing their performance in advanced energy storage applications. Supercapacitors exhibit a blend of both electric double-layer capacitance (EDLC) and pseudocapacitance, making it essential to differentiate these contributions for material design and device optimization. Among various analytical methods, Dunn’s method, which uses cyclic voltammetry (CV) at varying scan rates, has emerged as a widely employed technique. As it is a relatively straightforward approach for deconvoluting capacitive and diffusion-controlled processes, this review provides a comprehensive overview of Dunn’s method, encompassing its theoretical background, analytical procedure, advantages, limitations, and applications across diverse electrode materials. Furthermore, the comparison of Dunn’s method with other electrochemical characterization techniques such as electrochemical impedance spectroscopy (EIS), galvanostatic charge–discharge (GCD), and Trasatti’s method also underscores future prospects for enhancing its accuracy and applicability. This review aims to serve as a practical guide for researchers looking to employ Dunn’s method in supercapacitor research.

Coal-based active carbon (CAC) is an ideal supercapacitor (SC) electrode material owing to its rich microporosity, high surface area, and excellent capacitance. Taixi anthracite (TXA) features high fixed-carbon content (<8% ash) and a well-ordered microporous structure. This renders TXA critical for CAC-based SC electrodes. For non-biomass SC electrodes, ash content management is critical. In this study, CAC was obtained by physical and chemical sequential activation of TXA using H₂O and KOH. Ultralow-ash D-CAC was prepared via oxalic acid deashing of CAC, with process conditions optimized. CAC’s extensive porosity enables efficient oxalic acid penetration and deashing. D-CAC demonstrated superior specific capacitance and cycling stability. D-CAC had the largest specific surface area of 2106 m²/g and a total pore volume of 1.03 cm³/g. D-CAC also exhibited a high specific capacitance of 339.4 F/g at a current density of 0.5 A/g. After 10,000 charge and discharge cycles, the specific capacitance showed a 99.1% retention rate. Furthermore, assembled symmetric SC exhibited a high specific capacitance of 156 F/g at 0.5 A/g and an energy density value of 6.25 Wh/kg with a power density of 12,500 W/kg. This organic acid (OA) deashing strategy enables the production of high-performance capacitive carbon.

This study presents the synthesis and characterization of the metal orthophosphate salt Pb(Sb_0.5Al_0.5)(PO₄)₂. The compound was meticulously prepared via solid-state reactions under ambient air conditions. The crystal structure was determined using Rietveld refinement based on powder X-ray diffraction data, providing detailed information on their atomic arrangements and spatial configurations. Pb(Sb_0.5Al_0.5)(PO₄)₂ adopts a low-yavapaiite structure crystallizing in the monoclinic lattice with space group C2/c and Z = 4; a = 16.605(9) Å; b = 5.128(6) Å; c = 8.073(3) Å; β = 115.17(1)°; V = 631(1) ų. Complementary Raman and infrared spectroscopy techniques allowed us to study in more detail the structural and bonding properties of the crystalline solid. In addition, the morphology was studied, and the chemical composition was confirmed by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The material's optical bandgap was estimated using ultraviolet–visible (UV–Vis) spectroscopy, and the result was roughly 3.8 eV. The insulating nature of a material cannot be verified by optical observation alone, although the wide bandgap increases the likelihood of such an occurrence. Measuring electrical conductivity is necessary for certain verification of an insulating nature. This study also presents a comprehensive study of the dielectric and electrical conductivity properties of this new material with mixed Sb⁵⁺ and Al³⁺ ions in the octahedral sites of the yavapaiite structure which exhibits very high electrical resistivity over a wide range of frequencies and temperatures. The study uses an approach combining the analysis of permittivity, impedance, complex modulus, and alternating current (AC) conductivity curves, which is very useful for understanding the electrical conduction and relaxation mechanisms in this type of material.

Nanographene immobilized by transition metals such as Cu and Ni has been synthesized and characterized using Fourier-transform infrared (FTIR), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), and ultraviolet (UV)–visible spectroscopy techniques. The particles were rod-shaped, measuring 90–100 nm in diameter. SEM data revealed the stalking together of exfoliated graphene oxide. Reduced graphene oxide immobilized by transition metals (Cu and Ni) showed surface plasmon effect. The porosity of the surface revealed that the surface plasmons were localized and dominated by the collective oscillation of electrons in the valence band of the metal. The three-dimensional reduced graphene oxide sheets resembled a loose sponge-like structure. Transmission electron microscopy (TEM) images revealed rod-shaped metal particles immobilized on the RGO surface when exposed to a diffracted electron beam. The size of RGO was found to be less than 100 nm, while the size of GO was more than 100 nm. The band gap energy of RGO, RGO-Cu, and RGO-Ni was 1.35 eV, 0.46 eV, and 1.26 eV, respectively. The primary 2θ peak for GO was a broad peak centered at around 11–12°, corresponding to the (001) plane, whereas RGO exhibited two prominent 2θ peaks at 25° and 43°. Copper-doped RGO displayed five peaks at 19°, 25°, 43°, 50°, and 74°, while the 2θ peaks of nickel-doped RGO were observed at 25°, 43°, 51°, and 52°. The synthesized compounds were tested for their ability to retain dissolved oxygen, revealing that RGO-Cu traps bacteria to a greater extent, with the dissolved oxygen (DO) level in water being maintained even after 5 days. RGO-Ni works as a potent absorber of other pollutants in water to release more DO than normal bacteria, using oxygen to trap the harmful bacteria and reducing other metal oxides into neutral forms.

Graphical Abstract

A structure representing the formation of graphene-immobilized transition metal (Cu²⁺ and Ni²⁺) by the reverse micelle method: Transition metals are immobilized in the micelle, and subsequently, graphene sheets interact with immobilized transition metal ions by facilitating their distribution on its surface.

Supercapacitors have garnered significant attention among today’s researchers due to their high capacitance. For supercapacitors, two-dimensional materials like graphene and its derivatives (graphene oxide [GO] and reduced graphene oxide [rGO]) and their composites with transition metal oxides are of great interest. In this study, one of the transition metal oxides, Fe₂O₃, was synthesized using a modified sol–gel method, and synthesized GO was used. Three composites with different concentrations of GO (10%, 20% and 30%) were formed via the ball milling method. X-ray diffraction (XRD) confirmed the rhombohedral structure of the prepared samples, with (104) as the highest peak. A carbon (103) peak also appeared in the composite samples, which confirmed the successful formation of the composite materials. The surface morphology was studied by scanning electron microscopy (SEM). Reduced agglomeration was seen in SEM images with increasing concentration of GO. Frequency-dependent dielectric and electrical properties were determined using a precision component analyzer in a range of 100 Hz to 3 MHz. The electrochemical performance was investigated using cyclic voltammetry (CV) and galvanostatic charge/discharge (GCD). Fe₂O₃ with 0% GO showed the highest specific capacitance of 152 F/g at 10 mV/s and discharge time of 119 s at 0.5 A/g, which decreased with the increasing concentration of GO, due to oxygen-containing functional groups present in GO.