Review of Biosensors Based on Plasmonic-Enhanced Processes in the Metallic and Meta-Material-Supported Nanostructures.

Surface plasmons, continuous and cumulative electron vibrations confined to metal-dielectric interfaces, play a pivotal role in aggregating optical fields and energies on nanostructures. This confinement exploits the intrinsic subwavelength nature of their spatial profile, significantly enhancing light-matter interactions. Metals, semiconductors, and 2D materials exhibit plasmonic resonances at diverse wavelengths, spanning from ultraviolet (UV) to far infrared, dictated by their unique properties and structures. Surface plasmons offer a platform for various light-matter interaction mechanisms, capitalizing on the orders-of-magnitude enhancement of the electromagnetic field within plasmonic structures. This enhancement has been substantiated through theoretical, computational, and experimental studies. In this comprehensive review, we delve into the plasmon-enhanced processes on metallic and metamaterial-based sensors, considering factors such as geometrical influences, resonating wavelengths, chemical properties, and computational methods. Our exploration extends to practical applications, encompassing localized surface plasmon resonance (LSPR)-based planar waveguides, polymer-based biochip sensors, and LSPR-based fiber sensors. Ultimately, we aim to provide insights and guidelines for the development of next-generation, high-performance plasmonic technological devices.

Optical and Electrical Analyses of Solar Cells with a Radial PN Junction and Incorporating an Innovative NW Design That Mimics ARC Layers.

The implementation of a texturing pattern on the surface of a solar cell is well known for reducing reflection, thus increasing the absorption of sunlight by the solar cell. Nanowires (NWs) that are large in their height have been widely used for this purpose. Through rigorous numerical simulations, this work explores the benefits of short but index-matched NWs and how these designs are also affected by surface recombination. Additionally, this work further optimized power conversion efficiency (PCE) by placing two or three NWs of different heights and diameters on top of each other to mimic the performance of two-NW and three-NW ARC designs with PCEs of 16.8% and 17.55%, respectively, when a radial pn junction is considered. These are the highest reported so far for such a thin silicon solar cell. Furthermore, we also show how these designs were impacted by surface recombination velocity and compare these findings to simple NWs of different heights and diameters.

A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers.

Nanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to enhance light-matter interactions. Despite these breakthroughs, design, fabrication, and characterization of such exotic devices have remained through iterative processes which are often computationally costly, memory-intensive, and time-consuming. In contrast, deep learning approaches have recently shown excellent performance as practical computational tools, providing an alternate avenue for speeding up such nanophotonics simulations. This study presents a DNN framework for transmission, reflection, and absorption spectra predictions by grasping the hidden correlation between the independent nanostructure properties and their corresponding optical responses. The proposed DNN framework is shown to require a sufficient amount of training data to achieve an accurate approximation of the optical performance derived from computational models. The fully trained framework can outperform a traditional EM solution using on the COMSOL Multiphysics approach in terms of computational cost by three orders of magnitude. Furthermore, employing deep learning methodologies, the proposed DNN framework makes an effort to optimise design elements that influence the geometrical dimensions of the nanostructure, offering insight into the universal transmission, reflection, and absorption spectra predictions at the nanoscale. This paradigm improves the viability of complicated nanostructure design and analysis, and it has a lot of potential applications involving exotic light-matter interactions between nanostructures and electromagnetic fields. In terms of computational times, the designed algorithm is more than 700 times faster as compared to conventional FEM method (when manual meshing is used). Hence, this approach paves the way for fast yet universal methods for the characterization and analysis of the optical response of nanophotonic systems.

Performance optimization of a metasurface incorporating non-volatile phase change material.

Optical metasurface is a combination of manufactured periodic patterns of many artificial nanostructured unit cells, which can provide unique and attractive optical and electrical properties. Additionally, the function of the metasurface can be altered by adjusting the metasurface's size and configuration to satisfy a particular required property. However, once it is fabricated, such specific property is fixed and cannot be changed. Here, phase change material (PCM) can play an important role due to its two distinct states during the phase transition, referred to as amorphous and crystalline states, which exhibit significantly different refractive indices, particularly in the infrared wavelength. Therefore, a combination of metasurface with a phase change material may be attractive for achieving agile and tunable functions. In this paper, we numerically investigate an array of silicon cylinders with a thin PCM layer at their centers. The GST and GSST are the most well-known PCMs and were chosen for this study due to their non-volatile properties. This structure produces two resonant modes, magnetic dipole and electric dipole, at two different resonating wavelengths. We have numerically simulated the effect of cylinder's height and diameter on the reflecting profile, including the effect of thickness of the phase change material. Additionally, it is shown here that a superior performance can be achieved towards reduced insertion loss, enhanced extinction ratio, and increased figure of merit when a GST layer is replaced by a GSST layer.

Optical Fiber, Nanomaterial, and THz-Metasurface-Mediated Nano-Biosensors: A Review.

The increasing use of nanomaterials and scalable, high-yield nanofabrication process are revolutionizing the development of novel biosensors. Over the past decades, researches on nanotechnology-mediated biosensing have been on the forefront due to their potential application in healthcare, pharmaceutical, cell diagnosis, drug delivery, and water and air quality monitoring. The advancement of nanoscale science relies on a better understanding of theory, manufacturing and fabrication practices, and the application specific methods. The topology and tunable properties of nanoparticles, a part of nanoscale science, can be changed by different manufacturing processes, which separate them from their bulk counterparts. In the recent past, different nanostructures, such as nanosphere, nanorods, nanofiber, core-shell nanoparticles, nanotubes, and thin films, have been exploited to enhance the detectability of labelled or label-free biological molecules with a high accuracy. Furthermore, these engineered-materials-associated transducing devices, e.g., optical waveguides and metasurface-based scattering media, widened the horizon of biosensors over a broad wavelength range from deep-ultraviolet to far-infrared. This review provides a comprehensive overview of the major scientific achievements in nano-biosensors based on optical fiber, nanomaterials and terahertz-domain metasurface-based refractometric, labelled and label-free nano-biosensors.

Artificial Neural Network Modelling for Optimizing the Optical Parameters of Plasmonic Paired Nanostructures.

The Artificial Neural Network (ANN) has become an attractive approach in Machine Learning (ML) to analyze a complex data-driven problem. Due to its time efficient findings, it has became popular in many scientific fields such as physics, optics, and material science. This paper presents a new approach to design and optimize the electromagnetic plasmonic nanostructures using a computationally efficient method based on the ANN. In this work, the nanostructures have been simulated by using a Finite Element Method (FEM), then Artificial Intelligence (AI) is used for making predictions of associated sensitivity (S), Full Width Half Maximum (FWHM), Figure of Merit (FOM), and Plasmonic Wavelength (PW) for different paired nanostructures. At first, the computational model is developed by using a Finite Element Method (FEM) to prepare the dataset. The input parameters were considered as the Major axis, a, the Minor axis, b, and the separation gap, g, which have been used to calculate the corresponding sensitivity (nm/RIU), FWHM (nm), FOM, and plasmonic wavelength (nm) to prepare the dataset. Secondly, the neural network has been designed where the number of hidden layers and neurons were optimized as part of a comprehensive analysis to improve the efficiency of ML model. After successfully optimizing the neural network, this model is used to make predictions for specific inputs and its corresponding outputs. This article also compares the error between the predicted and simulated results. This approach outperforms the direct numerical simulation methods for predicting output for various input device parameters.

Phase-matched multi-layer based polarisation-independent spot-size converter for silicon nanowire.

The efficient coupling of optical power from a silicon nanowire (NW) to an optical fibre is challenging for both the quasi-TE and quasi-TM polarisations. Here, we propose a polarisation-independent spot-size converter (PI-SSC) based on phase-matched multi-layer waveguides for efficient coupling between a silicon NW and an optical fibre for both the polarisations. The fabrication process of the proposed PI-SSC is compatible with the complementary metal-oxide-semiconductor (CMOS) process. The optimisation for the proposed PI-SSC is studied by using a numerically efficient algorithm, combining a rigorous H-field based full-vectorial finite element method (VFEM) and the least squares boundary residual (LSBR) method. The simulation results show that using an eleven-layer based PI-SSC, the coupling losses between a silicon NW and a lensed fibre of radius 2 µm can be reduced to only 0.34 dB and 0.25 dB for the quasi-TE and quasi-TM polarisations, respectively. Furthermore, the output multi-layer is horizontally tapered, which further reduces the coupling loss for both the polarisations and the end face is easy to be polished.

Optimization of a horizontal slot waveguide biosensor to detect DNA hybridization.

A full-vectorial H-field formulation-based finite element approach is used to optimize a biosensor structure incorporating a horizontal slot waveguide. It is designed to detect DNA hybridization through the change of the effective index of the waveguide structure. The key parameters, such as normalized power confinement, power density, change in effective index, and sensitivity are presented by optimizing the device parameters of the slot waveguide. It is shown here that a 90.0 µm long compact Mach-Zehnder section can be designed with horizontal slot waveguide to detect DNA hybridization and for a ring resonator arrangement a sensitivity of 893.5 nm/RIU is obtained.

Label-free slot-waveguide biosensor for the detection of DNA hybridization.

A finite element method based on the full-vectorial H-field formulation has been employed to achieve the maximum field penetration in the sensing medium of the slot-waveguide-based ring resonator biosensor. The use of nanometer scale guiding structure where optical mode is confined in a low-index region permits a very compact sensor with high optical intensity in the region, which makes it possible to detect minimum refractive index change, and offers higher sensitivities. We analyze the change in effective refractive index of mode, sensitivity, and power confinement of the proposed slot-waveguide-based ring resonator biosensor for the detection of DNA hybridization. The biosensor exhibited theoretical sensitivity of 856 nm per refractive index unit (RIU) and a detection limit of 1.43×10(-6) RIU.

Design of bent photonic crystal fiber supporting a single polarization.

In this work, it is shown that the differential loss between the TE- and TM-polarized fundamental modes in a highly birefringent photonic crystal fiber (PCF) can be enhanced by bending the fiber. As a result, a design approach for single-mode single-polarization operation has been developed and is discussed. A rigorous full-vectorial H-field-based finite element approach, which includes the conformal transformation and the perfectly matched layer, is used to determine the single-polarization properties of such a highly birefringent PCF by exploiting its differential bending losses.

Resonance condition of a microfiber knot resonator immersed in liquids.

Effects of immersing a microfiber knot resonator (MKR) in liquid solutions that have refractive indices close to that of silica are experimentally demonstrated and theoretically analyzed. Significant improvement in resonance extinction ratio within 2 to 10 dB was observed. To achieve a better understanding, a qualitative analysis of the coupling ratio and round-trip attenuation of the MKR is performed by using a curve-fitting method. It was observed that the coupling coefficient at the knot region increased when immersed in liquids. However, depending on the initial state of the coupling and the quantity of the increment in the coupling coefficient when immersed in a liquid, it is possible that the MKR may experience a deficit in the coupling parameter due to the sinusoidal relationship with the coupling coefficient.

Mode degeneration in bent photonic crystal fiber study by using the finite element method.

The development of highly dispersive lower and higher order cladding modes and their degeneration with respect to the fundamental core mode in a bent photonic crystal fiber is rigorously studied by use of the full-vectorial finite element method. It is shown that changes in the bending radius can modify the modal properties of large-area photonic crystal fibers, important for a number of potential practical applications.

Optimization of compact lateral, vertical, and combined tapered spot-size converters by use of the beam-propagation method.

A study of lateral, vertical, and combined spot-size converters is presented that employs full-vectorial numerical techniques such as modal solution and beam propagation based on the finite-element method. Spot-size expansion, coupling efficiency to an optical fiber, the mode-beating phenomenon, and transmission losses are demonstrated for all three spot-size-converter designs. Optimization of the device fabrication parameters is also reported. A significant improvement in the coupling efficiency and reduction of the device length are achieved when the length and the width are changed simultaneously.

Numerical modeling of polarization conversion in semiconductor electro-optic modulators.

An accurate numerical simulation study of a polarization conversion phenomenon in deeply etched semiconductor electro-optic waveguide modulators is presented. Based on a powerful and versatile finite element package, the effect of various imperfect fabrication conditions on unwanted and unexpected polarization conversion in electro-optic semiconductor modulators is, for the first time to our knowledge reported and explained in terms of its origin.

Rigorous comparison of parabolically tapered and conventional multimode-interference-based 3-dB power splitters in InGaAsP/InP waveguides.

Design issues such as optical transmission, interference mechanisms, the splitting ratio, the polarization dependence, and the fabrication tolerances of a compact parabolically tapered multimode-interference (MMI)-based 3-dB power splitter on an InP-based deeply etched ridge waveguide, by use of the finite-element-based beam-propagation method, are presented. The benefits and drawbacks of the use of the tapered structure, in comparison with an untapered MMI-based 3-dB splitter, have also been investigated.

Bandwidth estimation for ultra-high-speed lithium niobate modulators.

The effects of velocity matching, impedance matching, conductor loss, and dielectric loss on the optical bandwidth of an ultra-high-speed lithium niobate modulator are reported. It is shown that both dielectric loss and impedance matching play a key role for velocity-matched high-speed modulators with low conductor loss. The effects of etch depth, buffer thickness, electrode width, and thegap between the electrodes on device performance are also illustrated.

Velocity matching of a GaAs electro-optic modulator.

New designs for the velocity matching of a deep-etched semiconductor electro-optic modulator are presented. A tantalum pentoxide (Ta2O5) coating is considered here for achieving velocity matching between the microwave and the optical signals. The effects of the velocity mismatch, the conductor loss, the dielectric loss, and the impedance mismatch are studied in relation to the optical bandwidth of a high-speed semiconductor modulator. It is shown that both the dielectric loss and the impedance matching play key roles for velocity-matched high-speed modulators with low conductor loss. The effects of Ta2O5 thickness on the overall bandwidth and on the half-wave voltage-length product VpiL are also reported.

Design issues of a multimode interference-based 3-dB splitter.

We have investigated important issues such as the power loss, the loss imbalance the fabrication tolerances, and the wavelength dependence for the design of a multimode interference-based 3-dB splitter on deeply etched InP waveguides under general, restricted, and symmetric interference mechanisms. For this investigation, we used the finite-element-based beam propagation approach. Results are presented.