Abstract Coherent diffractive imaging (CDI) reconstructs object complex amplitudes from diffraction patterns using iterative phase retrieval algorithms, while multi-wavelength CDI (MW-CDI) improves reconstruction robustness through wavelength diversity. However, practical MW-CDI systems remain affected by probe-object coupling, non-uniform illumination, and sequential acquisition instability, leading to probe-related reconstruction artifacts. To address these limitations, a single-shot RGB MW-CDI framework combined with a gradient-based probe-decoupling reconstruction strategy is proposed. An RGB laser source and a color CCD camera are employed to simultaneously acquire diffraction patterns at three wavelengths, thereby reducing temporal instability associated with sequential acquisition. An illumination-weighted gradient update strategy is further incorporated into the iterative framework to suppress residual probe-related artifacts caused by non-uniform illumination. Numerical simulations and experimental results demonstrate improved reconstruction fidelity, faster convergence, and enhanced robustness compared with conventional MW-CDI reconstruction. Experimental imaging of a USAF1951 target and weakly absorbing biological samples further verifies the effectiveness of the proposed method for stable and high-precision multi-wavelength lensless imaging.
This paper presents a terahertz metamaterial-inspired biosensor designed for the label-free detection of Mycobacterium tuberculosis (TB). The proposed sensor consists of a lossy PTFE (polytetrafluoroethylene) dielectric layer sandwiched between a gold bottom plane and top gold metallic patch. The simulated absorptivity curve shows a pronounced absorption peak at 3.0271 THz with a near-perfect absorptivity of 99.99 RIU ^-1 for TB-1 detection. These results indicate reliable discrimination between infected and normal samples with good sensitivity.
Abstract We propose and numerically investigate a functionalized long-period fiber grating (LPFG) sensor for simultaneous temperature and humidity detection based on reconfigurable optical skyrmions. Around the 1550-nm operating band, variations in temperature and relative humidity are converted into changes in the LPFG resonance wavelength, modal coupling coefficient, and relative phase delay. These amplitudephase perturbations reshape the output Stokes-vector texture, enabling environmental information to be encoded into skyrmion features including the skyrmion radius R sk , texture rotation angle Θ sk , Stokes parameter s 3 contrast, and skyrmion number N sk . Over the simulated sensing range of 10-90 °C and 10-90%RH, the skyrmion radius varies from approximately 0.97 to 4.57 µm, while the texture rotation angle spans nearly 0-200°. The generated Stokes textures maintain a skyrmion number close to -1, confirming the topological stability of the reconfigurable polarization field. Inverse retrieval based on the multidimensional skyrmion-feature vector gives mean absolute errors of 12.16°C and 4.22%RH for temperature and humidity, respectively. Sensitivity and robustness analyses further show that the skyrmion readout remains distinguishable under readout-noise variation and an operating-wavelength detuning of ±0.5 nm. These results indicate that functionalized LPFGs can serve not only as spectral sensing elements but also as compact topological-light modulators, providing a promising route toward fiber-compatible multiparameter sensing using skyrmionencoded polarimetric fingerprints.
Although traditional subtractive and formative manufacturing techniques have long been the standard for producing high-quality imaging optics, these methods struggle to address microscale complexities, multi-material integration, and fabrication of intricate geometries demanded by next-generation applications in fields such as optical metamaterials, optical metrology, and advanced microscopy. In contrast, additive manufacturing is transforming optical fabrication by enabling free-form, multi-material optical structures at the micro and nanoscale for various imaging uses. Despite these advantages, the layer-by-layer printing process can introduce surface irregularities, index inhomogeneities, and form errors that directly impact imaging performance. However, these issues have been effectively reduced through design optimization for manufacturability, careful control of printer resolution, material selection, and post-processing methods. Recent advancements, such as multiphoton polymerization, achieve sub-micrometer layer and in-plane resolution, making them suitable for creating miniaturized optical components. In this systematic review, three key areas of focus are: fabrication techniques, material selection, and post-processing methods. We benchmark 3D-printed optics against their commercial counterparts, showing that off-the-shelf parts still rule in high-volume, cost-efficient precision, while prints win on custom shapes and rapid prototyping. This review also presents 3D-printed optics performance in biomedical imaging applications such as microscopy, revealing layer-induced artifacts and proposing mitigation strategies. By providing standardized performance comparisons, this review fills a critical gap in the literature, offering insights into recent breakthroughs and future directions for additive manufacturing.
Optical fiber networks are highly susceptible to physical-layer impairments, including macrobending. A major limitation of existing Self-Optimizing Optical Network (SOON) frameworks is that they primarily optimize routing and resource allocation while providing limited support for physical-layer impairment estimation. This paper proposes an AI-assisted framework that combines synthetic Optical Time-Domain Reflectometry (OTDR) trace modeling with Random Forest regression to estimate macrobending loss. A realistic synthetic dataset is generated by simulating attenuation, reflective and non-reflective events, wavelength-dependent propagation loss, and additive noise based on established physical principles. The proposed framework first characterizes OTDR signatures and subsequently estimates macrobending-induced attenuation, bending radius, and external pressure using empirical inverse models. This paper demonstrates that the Random Forest model achieves an R^2 score of 0.9856 and a mean squared error (MSE) of 0.0123, outperforming Linear Regression, Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Gradient Boosting, and Multi-Layer Perceptron (MLP) models. The proposed framework provides a practical foundation for integrating AI-assisted physical-layer diagnostics into future autonomous optical networks (AONs).
The rapid expansion of 5G networks and smart city infrastructure demands high-capacity, low-latency communication backbones that can adapt to dense urban deployments. The dynamic environmental conditions in urban environments, lead to poor visibility, such as in the case of smog. The current work investigates a hybrid WDM-FSO Passive Optical Network (PON), based on C-RAN architecture, a spectrum efficient network optimized for dense 5G front-haul deployment. It specifically focuses on the performance degradation because of severe smog in Indian urban cities such as New Delhi. It leverages the polarization diversity for transmission from BBUs to dense RUs in the C-RAN framework. A Random Forest Regressor model is developed using real-time data to assess the effect of smog on the visibility during winters and to accurately estimate the attenuation coefficient for the FSO link. The investigated framework is promising in mitigating performance degradation due to aerosol scattering and attenuation in Delhi’s winter smog, maintaining a 10 Gbps (4-QAM modulated bit sequence) transmission over 2.3 km FSO links under dense smog conditions at minimum visibility (< 500 m). This study emphasizes the potential of intelligent, weather-aware optical networks in delivering robust, high-bandwidth 5G connectivity for smart cities under challenging atmospheric conditions.
Abstract This paper proposes and experimentally validates a microwave photonic system for joint blind source separation (BSS) and angle of arrival (AOA) estimation of multi-source signals. By integrating digital signal processing algorithm, the system enables effective separation of multiple signals and accurate angle identification. In the experiment, two RF signals at 18 GHz and 21 GHz are directly generated by an arbitrary waveform generator. The two RF signals are applied to a dual-drive Mach–Zehnder modulator (DDMZM) together with a local oscillator signal. The modulator is biased at its minimum transmission point, and the desired difference‐frequency component is selected. The photodetector converts the optical signal output from DDMZM into a down-converted intermediate-frequency (IF) signal. The waveforms of the mixed IF signal are collected by an oscilloscope. In the data processing stage, the JADE algorithm is used to perform BSS on the IF mixed signal, then two IF signals are separated and recovered. Subsequently, the separated signals are input into the MUSIC algorithm. Through spatial spectrum construction and peak searching, precise estimation of the incident angle of each signal is achieved. Experimental results show that, under the emulated AOA conditions, the estimation error over the range of 0° to 90° is within ±1.4°.
Abstract This study introduces a mode-locked pulsed random fiber laser that utilizes a nonlinear optical loop mirror (NOLM) and a random phase-shift fiber Bragg grating. The features of saturable absorption and inverse saturable absorption in the NOLM are replicated in the experiment. By precisely adjusting the polarization controller (PC) in the NOLM, a mode-locked pulse output with a fundamental repetition frequency of 40.45 kHz can be achieved, and fourth-order harmonic mode-locked is achieved when the pump power is set at 200.1 mW. Using a pump power of 350 mW, alternating bright and dark optical pulses at repetition rates of 40.45 kHz and 80.91 kHz can be achieved by continuously adjusting the PC. The laser has a maximum power variation of less than 0.299 dB and a maximum wavelength variation of less than 0.04 nm, indicating stability. The proposed laser is promising for low-repetition-rate pulsed applications.
This paper introduces a novel approach to address the demands of the upcoming 5G era and its associated applications, emphasizing high data rates and minimal power consumption. A conventioanl WDM-PON system is constrained by limited user scalability and transmission capacity. To overcome these limitations and to support a high split ratio, the proposed system combines Space Division Multiplexing (SDM) with Wavelength Division Multiplexing (WDM) in a Passive Optical Network (PON), strengthened by Distributed Raman Amplification (DRA). In SDM-WDM PON configuration, upstream WDM transmission serves 200 users, while downstream SDM-WDM transmission accommodates 80 users across 40 wavelengths with two spatial modes. Upstream channels operate within the wavelength range of 1550 to 1628 nm, while downstream channels utilize wavelengths ranging from 1302 nm to 1223 nm. In the proposed SDM-WDM PON architecture, each user transmits at 9 Gbps, and the Optical Line Terminal simultaneously receives information from 280 users. Both upstream and downstream transmitters support either RZ or NRZ modulation formats. The corresponding Bit Error Rate (BER) evaluations have been done by employing a 50 Km DRA, powered by 1480 nm source at 10 mW, which ensures long reach and enhances network capacity. This configuration allows 280 users to access the network with minimal pumping and transmission power requirements. The proposed system provides an aggregate capacity of 2.52 Tbps. Comparison with prior literature reveals that the proposed SDM-WDM PON utilizing DRA, highlighting its potential to meet the evolving demands of modern telecommunications networks.
The growing need for sustainable and clean energy has fueled important developments in photovoltaic technology. Because of its improved environmental stability and lead-free makeup, double perovskite solar cells (PSCs) have become one of the most attractive options for next-generation photovoltaics. This study investigates the performance of carbon-based, hole-transport-layer-free (HTL-free) Cs₂AgBiBr₆ PSCs through numerical simulations using SCAPS-1D. The device optimization concentrates on important parameters such absorber thickness, defect density, doping concentration, and operating temperature in order to obtain a significant improvement in power conversion efficiency (PCE) from 16.73
Pure-Anatase Titanium-dioxide (TiO2) and Copper-doped TiO2 NPs at varying Cu-concentrations (2,4,6) wt t_r=2.43 s and t_f=4.58 s . Experimental-results confirmed that the produced device-configuration is highly sensitive to solar-light to which it was exposed and suitable in optoelectronic applications.
To overcome the critical problem of toxicity and stability of conventional perovskites, SCAPS-1D is used to design and analyse a device with the incorporation of a lead free (FA)2BiCuI6. Four organic electron transport layers (ETLs), F16NiPc, Cl16NiPc, Br16NiPc, and I16NiPc, were analyzed, and I16NiPc was identified as the most suitable ETL, while Copper Phthalocyanine (CuPc) acts as the hole transport layer (HTL) because of the band alignment at the absorber interface, I16NiPC outperformed other ETLs. It has the best conduction band offset (CBO of − 0.11 eV), which enhances electron extraction and reduces charge recombination, yielding an impressive power conversion efficiency (PCE) of 29.20
A 1 × 2 broadband polarization-independent power splitter based on a two-dimensional photonic crystal with a honeycomb-lattice is proposed. By optimizing the radii of the dielectric rods on both sides of the waveguide and the radii and offsets of the dielectric rods at the waveguide junction, the transmittance and broadband performance of the splitter are effectively improved. To improve the optimization efficiency and splitting performance, the downhill simplex algorithm is employed to inverse-design the proposed 1 × 2 photonic crystal beam splitter. The results show that within the bandwidth range of 1520 to 1580 nm, the proposed splitter exhibits a minimum transmittance of 82.0
The best operation of a solar cell involves several steps and layers, each designed to optimize the absorption of sunlight and the generation of electrical current. Multilayer solar cells p-MoS₂/p-CdSe/n-ZnS/n-ITO, composed of molybdenum disulfide (MoS₂) and cadmium selenide (CdSe), exhibit potential for thin-film photovoltaic technology due to their ability to modify optical absorption and electrical characteristics. This study evaluates the performance of a p-MoS₂/p-CdSe/n-ZnS/n-ITO device structure by analysing critical parameters such as fill factor (FF), open-circuit voltage (Voc), short-circuit current density (Jsc), operating temperature, and overall collection efficiency. This multilayer device smartly combines the functional layers MoS₂, CdSe, ZnS, and ITO. . The temperature dependence of the electrical parameters of p-MoS₂/p-CdSe/n-ZnS/n-ITO solar cells is important for evaluating their stability and performance under practical operating conditions. Using the experimental data in the tables and the J-V characteristics shown in the figures, .a comprehensive analysis of the effect of temperature on the solar-cell parameters was performed. A comparison of the two configurations demonstrates that increasing the ZnS buffer layer thickness from 50 nm to 100 nm significantly enhances junction quality.
This work investigates light propagation in one-dimensional cylindrical photonic crystals (CPCs) using the transfer matrix method for periodic and Fibonacci sequences. The effects of externally applied mechanical pressure are modeled by simultaneously considering the photoelastic modification of the refractive indices and the elastic deformation of the silicon and polystyrene layers. The results show that increasing the pressure from 0 to 3 gigapascals (GPa) shifts the photonic band gaps toward higher reduced frequencies owing to pressure-induced changes in the effective optical thickness of the structure. In addition, pressure modifies the widths of the photonic band gaps, producing a slight narrowing of the central band gap in the periodic crystal, whereas the Fibonacci structures exhibit a more complex response, with the first band gap broadening and the second becoming progressively narrower. These findings demonstrate that mechanical pressure can effectively tune the spectral position and width of photonic band gaps, providing a theoretical basis for the future development of pressure-tunable photonic devices.
In this research, the impact of the geometrical parameters of In₀.₃Ga₀.₇N/GaN disk-like quantum dots (QDs) on their optical properties and quantum efficiency (QE) is explored. For this purpose, a quantum-disk model is numerically simulated via the use of MATLAB program for calculation of absorption coefficient and quantum efficiency (QE) in the range of wavelengths from 300 to 700 nm. Moreover, the impacts of both the radius and height of the disks on the optical properties are investigated, and the results are compared with other theoretical and experimental investigations available in the literature. It is found out that the best optical performance for such QDs can be reached at a disk radius of 3 nm and disk height of 2 nm, with a maximum absorption coefficient of about ∼ 9303 cm^-1 and a maximum QE of 86.3
In this study, a channel plasmonic waveguide based on a bulk Dirac semimetal (BDS) is proposed, consisting of a 0.2-µm-thick BDS layer deposited on a channel etched in a silicon substrate (ε ≈ 11.9) with an air cladding. The BDS response is modeled using the Kubo–RPA formalism in the long-wavelength limit, and mode simulations are carried out by the finite element method (FEM). The operational range of 0.2–3.5 THz is considered, with a carrier relaxation time of τ = 4.5 ps at low temperature. The influence of Fermi energy (EF), groove geometry (width wg and height hg), and inter-groove dielectric material is systematically investigated. The results demonstrate that the proposed structure supports tightly confined SPP modes at the BDS-silicon interface, particularly at frequencies above 2.5 THz. At these frequencies, the propagation length surpasses 1.5 mm while the figure-of-merit (FOM) increases and the normalized mode area (Aeff/λ₀2) decreases. A parametric study shows that the performance is highly dependent on the substrate and channel geometry: for a fixed channel width, at thinner substrate width (w 10 µm) the propagation length and FOM are optmized, whereas increasing the substrate width (w 28 µm) causes significant degradation. Additionally, employing higher-permittivity dielectric materials within the etched cavity of the substrate enhances confinement and improves the FOM at the expense of reduced propagation length. Consequently, the proposed architecture constitutes a highly tunable and efficient platform for subwavelength terahertz waveguiding, presenting considerable potential for implementation in advanced filters, sensors, and integrated photonic circuits.
Surface plasmon resonance (SPR) sensors using the PCF have been studied extensively due to their high sensitivity and compact size which makes them suitable for sensing refractive index (RI) applications in real time. In this paper, a D-shaped PCF SPR sensor utilizing periodic array of gold nanowire (GnW) is designed and numerically optimized for an extraordinary enhancement in its RI sensing capability. The proposed sensor is designed as a multitude of gold nanowire arrays which are embedded in a D-shaped surface-plasmon-launched silica PCF. The D shaped geometry provides more contacts of evanescent field and the sensing medium, and the periodic gold nanowire arrays demonstrate that strong localizing surface plasmon resonance of gold nanowire creates strong interaction between the sensing material and the electromagnetic field. The numerical simulation shows that the proposed configuration in this work has high sensitivity in the refractive index detection, high linearity, narrow resonance linewidth, and is accurate in the wide range of the refractive index detection. Relatively simple geometry, stable plasmonic response, and high sensing capability make it an interesting platform for biomedical application such as diagnostics, biochemical detection, environmental monitoring, food safety analysis and chemical applications sensor to be used.
In this work, an efficient and highly sensitive Fiber Bragg Grating (FBG) sensing scheme based on wavelength-to-power mapping is proposed for monitoring breathing-induced strain. The impact of the grating length on the sensitivity of the proposed sensor and on the respiration induced strain is investigated. Six grating lengths—5 mm, 9 mm, 12 mm,15 mm, 20 mm and 25 mm—are used to systematically examine the impact of grating length on sensor sensitivity and respiration-induced strain detection. Among these, a grating length of 25 mm achieves the highest sensitivity of 0.84 dB/µε and provides a significantly improved signal-to-noise ratio compared to a 15 mm grating for the same respiration-induced strain. The proposed scheme’s ability to monitor breathing-induced strain under two physiological postures, namely sitting and standing, is also evaluated. The scheme also provides temperature compensation strategy whereby the temperature induced power reduction in one FBG is offset by an equivalent power increase in other FBG, effectively compensating for temperature variation. This approach is applied to respiratory monitoring under realistic body-temperature variations, and the proposed scheme is found to be robust against temperature changes of up to ± 2 °C. It is observed that the proposed scheme can measure strain as low as 0.05 µε amid body temperature with good accuracy and thus eliminates the use of OSA. The proposed scheme offers the advantages of simplicity and high sensitivity, making it suitable for small-amplitude microstrain monitoring applications such as respiration monitoring, while ensuring robustness against thermal fluctuations.
A novel metamaterial is designed using In0.53Ga0.47As multilayers (CD)m, which exhibits impressive type-I hyperbolic metamaterial (HMM) behavior as well as epsilon negative (ENG) metamaterial behavior over specific wavelengths. Using effective medium theory, the effective relative permittivity components of In0.53Ga0.47As multilayers (CD)m are estimated, whereas plasma model is used to calculate the permittivity of the In0.53Ga0.47As layers (C D). One-dimensional photonic crystal (1D-PC) with In0.53Ga0.47As multilayers as HMM (layer A) and Si3N4 (layer B), exhibits angle insensitive photonic band gap (PBG) in the visible region hence narrow band filtering can be achieved. With an increase in the doping density (nd) of the In0.53Ga0.47As layers, the metamaterial transitions from being anisotropic HMM to isotropic ENG metamaterial. Transmission peaks as well as omnidirectional photonic band gaps (OPBGs) in the visible region are observed with In0.53Ga0.47As layers as ENG metamaterial based 1D-PC, and thus find applications in signal processing and photovoltaic devices.
