Optical and Quantum Electronics最新文献

In this experimental work, Zn thin films were oxidized via annealing to produce transparent ZnO nanostructured films. The initial Zn thin films were deposited by DC magnetron sputtering and the annealing process was done at a temperature of 700 °C for different time intervals, i.e., 1, 2, 3, 4, and 5 h. Afterward, the effect of annealing time on structural, morphological, optical, and electrical properties was precisely investigated. X-ray diffraction studies verify a hexagonal wurtzite crystal structure for all ZnO thin films. The average crystal size of spherical ZnO nanoparticles which is obtained using Scherrer and Williamson-Hall methods is in good agreement with SEM images. Annealing for different time intervals influences surface roughness and average grain size of deposited films, which have been observed through AFM images. Optical characteristics of samples are obtained via absorption and transmission of UV spectra besides photoluminescence spectrum, confirming that direct optical energy bandgap -ranging from 3.19 to 3.26 eV for the samples- is directly influenced by annealing time. Thereafter, other optical parameters such as penetration depth, extinction coefficient, refractive index, dielectric constant, and optical conductivity have been calculated and discussed. Furthermore, a four-needle probe is adopted to measure ZnO thin films’ electrical resistance, which results in the calculation of resistivity and electrical conductivity. All results were well confirmed and validated by XPS testing. Hopefully, these results will facilitate the progress of high-efficiency optoelectrical devices produced by pure ZnO thin films.

Graphical abstract

In this study, the transmission of Super-Gaussian optical pulses through a one-dimensional photonic crystal containing two defect layers based on Weyl semimetal was investigated using the transfer matrix method and Fourier transform analysis. By leveraging the non-reciprocal enhancement provided by the Weyl semimetal and considering the spectral broadening of Super-Gaussian pulses compared to Gaussian pulses, transmitted energy, average pulse duration, and time delay were examined as key metrics for pulse transmission. The results demonstrate a significant dependence of these metrics on the pulse type and the direction of propagation incident on the structure. A comparative analysis with the transmission of Gaussian pulses highlights notable differences in the non-reciprocal behavior and transmission efficiency of Super-Gaussian pulses in the presence of topological defects, underscoring the crucial role of pulse shape in regulating direction-dependent light transmission in photonic architectures.

In this work, a fundamental single-band graphene-based biosensor structure is proposed, where the patterned graphene layer is designed in an octagonal geometry. Based on this configuration, dual-band absorbers are developed by integrating additional ring and plus-shaped resonators. All the proposed sensors share a simple three-layer configuration consisting of a metallic ground plane, a SiO₂ dielectric spacer, and a patterned graphene sheet functionalized by the target analyte. By optimizing the geometrical parameters and tuning the chemical potential and relaxation time of graphene, both the resonance frequencies and absorption intensity can be effectively controlled. The designed structures exhibit near-perfect absorption at their resonance bands and provide a compact and efficient platform for terahertz biosensing applications. The first proposed sensor shows a single absorption peak with 99.88% absorption and demonstrates promising results in detecting breast, cervical, and PC12 cancer cells, with the highest sensitivity of 2.14 THz/RIU observed for PC12 cancer cells. The second proposed sensor has two resonance bands, each exhibiting over 97.5% absorption, and shows notable sensitivity for detecting breast, Jurkat, and PC12 cancer cells, with the highest sensitivity of 4.21 THz/RIU observed for breast cancer at the second band. The third proposed sensor also has two resonance bands with over 98.5% absorption for each band and provides suitable sensitivity for detecting basal, cervical, and MCF-7 cancer cells, with the highest sensitivity of 1.66 THz/RIU observed for cervical cancer at the second band. The proposed technology offers a rapid and economical approach for oncological detection, enabling real-time tracking and tailored therapeutic strategies. All computational analyses were conducted using CST software.

In this work, we present a type of compact binary diffractive optical element named Dual-Channel Radially-Coupled-Spiral Phase-Shift Zone Plate (DC-RCS-PZP) able to create two independent helico-conical vortex beams simultaneously. The proposed element makes it possible to individually control the topological charge, position, and effective handedness of the two beams in a unified optical aperture. The independent control of the two beams is achieved through the coherent addition of two non-separable radial- and azimuthal-phases belonging to the two channels. The parallel creation of two separate helico-conical beams with two independent vortex morphologies is demonstrated through both numerical and experimental results for the presented element. The two created beams display typical properties of helico-conical beams, including self-healing and radial- and azimuthal-flows of energy. The effectiveness of the proposed element makes it useful for realizing other applications involving the parallel and independent manipulation of structured optical beams in laser processing and optical communication applications such as simultaneous optical manipulation of two particles or parallel laser material processing and multiplexing of the orbital angular momentum.

Rapid advancements in 5G and the internet of things (IoT) have significantly increased global mobile network traffic as they require very high bandwidth. Consequently, there is growing interest in alternative communication technologies like visible light communication (VLC) that has a vast bandwidth in addition to the advantage of low implementation costs, and more secure system, since it achieves high immunity to electromagnetic interference, which is a very needed requirement in IoT. But despite all these advantages, VLC faces challenges like high peak-to-average power ratio (PAPR) that results from the superposition of transmitted peaks of several subcarriers. PAPR is considered one of the high-priority issues, especially in the VLC systems, as we always aim to keep the LED working within its linear range to prevent LED damage or burn. So, This paper studied, simulated, and designed a proposed optical modulation scheme named precoding Flip-OFDM (PF-OFDM), to mitigate this issue in VLC systems by suggesting a PAPR precoding reduction scheme like discrete sine transform (DST), and discrete cosine transform (DCT), while evaluating the system BER. The proposed PF-OFDM substantially reduces PAPR without compromising the system BER performance as it requires energy per bit to noise ratio at BER=(:{10}^{-4}:)of 15, 19.2, 24, 29, and 34.4 dB at modulation orders of 16, 64, 256, 1024, and 4096-QAM, which is nearly the same as the traditional Flip-OFDM. Moreover, the PF-OFDM employing DST demonstrates substantial improvements by comparing it with FLIP-OFDM as it reduces the PAPR by approximately 3.25 dB, 2.96 dB, 2.73 dB, 2.85 dB, and 2.58 dB at modulation orders of 16, 64, 256, 512, and 1024-QAM, respectively. Moreover, a comparison between PF-OFDM and other state-of-the-art techniques in the literature is provided to validate the effectiveness of the proposed approach.

Optical networks are designed to handle wireless traffic by interlinking heterogeneous uplink and downlink communication networks. This work introduces an Augmented Wavelength Division Allocation Method (AWDAM) using a perceptron learning model. The proposed allocation method probabilistically estimates the in-link traffic flow over the different peak intervals. The perceptron learning estimates the allocation and acceptance capacity of the interlinking devices to disperse the peak traffic. The learning augments verify the interlinking device’s capacity to dissolve the peaks through mesh-interconnected routing. More specifically, the wavelength augmentation and division for joint traffic management using multiple interlinking points is preceded based on the blocking probability. This blocking probability reduction for heterogeneous outflows is ensured by both the perceptron layer decisions during the peak interval. Therefore, the traffic grooming is augmented and divided according to the layer’s decision that jointly improves wavelength allocations. The traffic grooming is pursued aided by dual operations of routing and allocation, reducing the blocking rate by 10.79% for the maximum device load. This method is efficient in improving resource allocation and network throughput by 13.31% and 11.28% for the same device loads.

We present modeling and simulation of optimal performance parameters for inverted organic solar cells (OSC) to enhance their efficiency. Several different simulation models, including the drift diffusion model (DDM), the exciton diffusion and transfer matrix model (TMM), were employed. First, the thickness of the photoactive layer (PAL) was optimized. The TMM shows that the maximum absorption in the visible portion within the PAL. The absorption distribution pattern provides valuable insights into photon absorption behavior and photon escape probability distribution. Moreover, the effects of surface temperature (ST), sunlight intensity, and the electron and hole transport layers were optimized. In addition, the carrier concentration and the mobilities of electrons (µ_e) and holes (µ_h) change as the temperature increases from 300 to 400 K, which affects the efficiency of the devices. The results also show that both the short-circuit current density (Jsc) and the open-circuit voltage (Voc) increase with illumination intensity, ranging from 0.01 to 1.5 suns. Additionally, by adding ZnO as the electron transport layer (ETL) and WO₃ as the hole-extracting layer (HEL), the optimized device showed an increased efficiency of 5.8%. Moreover, the best performance was observed when the hole-to-electron ratio was equal to 1, confirming efficient transport and minimum recombination losses. These results highlight that using optimum device parameters is an effective approach for fabricating inverted OSCs suitable for industrial photovoltaic applications.

This study presents the design and comprehensive numerical analysis of a tunable graphene-based metasurface designed for high-sensitivity plasmonic and refractive index sensing applications. The proposed structure combines a graphene nanoribbon and a U-shaped graphene resonator on a dielectric substrate, forming a hybrid metasurface that supports multiple strongly coupled plasmonic modes. Finite-difference time-domain (FDTD) method are employed to investigate the optical response under variations in geometrical parameters and environmental refractive index. The results reveal that modulation of the nanoribbon and U-shaped dimensions enables precise control over the resonance frequencies and transmission characteristics through plasmonic mode hybridization. The hybrid structure exhibits multiple, distinct resonance dips with enhanced near-field confinement and broad spectral tunability. Sensitivity analysis based on a linear dependence of resonance frequency on the surrounding refractive index yields average sensitivities of 284, 540, and 748 GHz/RIU for Modes I–III, respectively, confirming the strong and predictable sensing performance of the device. The electric field distributions further verify intense plasmon localization and near-field coupling between the graphene elements. These findings demonstrate that the proposed graphene-based hybrid metasurface offers a compact, dynamically tunable, and highly sensitive platform suitable for next-generation terahertz and mid-infrared photonic and biosensing applications.

The rapid advancement of quantum computing poses a significant threat to conventional encryption methods, necessitating the development of novel communication technologies that offer enhanced security. In response to this challenge, we present a dual-layer optical communication scheme designed to ensure robust data protection in the post-quantum era. At the physical layer, security is achieved using perfect spatiotemporal optical vortices (PSTOVs), generated via Bessel beams from an ultrafast pulsed laser. Information is encoded in the beam’s spatiotemporal phase structure, which can only be deciphered through a specific interference pattern—effectively concealing the data from unauthorized access. Complementing this, a coordinated algorithm based on pre-shared knowledge between sender and receiver (Alice and Bob) governs the encoding and decoding process, adding a second layer of security independent of quantum protocols. The integration of physical-layer obfuscation via ultrafast PSTOVs with algorithmic control introduces a promising paradigm for secure, high-throughput optical communication, tailored to meet the demands of a future shaped by quantum computing capabilities.

This work integrates computational simulations with a hybrid machine learning framework to investigate the nonlinear relationships between plasmonic layer geometry, refractive index variations, and spectral response in a photonic crystal fiber (PCF) surface plasmon resonance (SPR) sensor. The proposed approach achieves reliable detection of small refrative index chances from a simple yet optimized PCF SPR sensing structure, reaching competitive sensitivity levels in the refractive index range of 1.33–1.39. Accurate predictions were obtained with (R^{2}> 0.99) and minimal error ((epsilon < 0.1)). A central contribution of this work is the simultaneous optimization of multiple optical metrics. Beyond maximizing wavelength sensitivity, the methodology balances sensitivity, figure of merit, Q-factor, and FWHM. This multiobjective strategy enables precise tailoring of the plasmonic layer geometry, producing sharp resonances, high-quality factors, and robust performance. Overall, the results demonstrate how plasmonic engineering in photonic crystal fibers can drive high-performance SPR sensing platforms. The methodology provides valuable insights into the geometry–plasmonics interplay while opening avenues for practical implementations in biochemical detection, environmental monitoring, and chemical sensing.