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Monte Carlo and particle swarm methods applied to the design of surface plasmon resonance sensors
... In the method, the convergence strongly depends on the initial guess for the sensor parameters, and the final solution is determined iteratively by successive corrections. Cavalcanti and Fontana [8] have used the particle swarm optimization (PSO) [9] technique to optimize SPR sensors in the Kretschmann or Otto configuration, a strategy followed by Sun et al. [10] to determine the optimum parameters for planar multilayer structures. The work in [8] culminated with development of the surface wave sensor optimizer (SWSO), an online web app openly available, for optimization of the SPR effect on planar structures [11]. ...
... Cavalcanti and Fontana [8] have used the particle swarm optimization (PSO) [9] technique to optimize SPR sensors in the Kretschmann or Otto configuration, a strategy followed by Sun et al. [10] to determine the optimum parameters for planar multilayer structures. The work in [8] culminated with development of the surface wave sensor optimizer (SWSO), an online web app openly available, for optimization of the SPR effect on planar structures [11]. Han et al. [12,13] used sophisticated and improved PSO strategies for optimization of multiple thicknesses of graphene-based SPR sensors. ...
In this work, the spectral dependence of optimum parameters of the surface plasmon resonance (SPR) effect on metallized sinusoidal diffraction gratings, under normal incidence, was determined using the particle swarm optimization method. The method was chosen due to its simplicity and effectiveness in providing reliable results, relative to direct search or gradient methods. The Rayleigh’s hypothesis, which restricts the analysis to the case of shallow gratings, is used to model the diffracted fields across the interface between the sensing medium and metal. A penalty function was applied to avoid the occurrence of singularities and violation of the validity of the Rayleigh hypothesis. Using this procedure, the optimum values of grating periodicity and amplitude that maximized the sensitivity function for gold, silver, copper, and aluminum—metals that yield high quality factor SPR effects—were determined in a wavelength range between 500 and 1600 nm, for both gaseous and aqueous sensing media.
... However, the authors limited themselves to studying grating configurations with a sinusoidal profile. Cavalcanti and Fontana [8] have used the particle swarm optimization (PSO) [9] technique to optimize SPR sensors in the Kretschmann or Otto configurations, a strategy followed by Araujo et al. [10] to determine the optimum parameters for a sinusoidal profile grating. ...
... Recently, Cavalcanti et al., demonstrated that the use of lorentzian fitting was not required and Monte Carlo or Partical Swarm Optimization (PSO) methods can be used to optimize SPR sensitivity when coupled with Fresnel equations. The authors left the frequency of incident radiation constant and focused on tuning gold thickness and incident angle [4]. Their methodology is effective for tuning materials which are known to host plasmons. ...
Various metals (Ag, Al, Au, Bi, Cu), polymers (polyvinylpyrrolidone, polystyrene), and electrically conductive polymers (polyacetylene, polyaniline, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate) were subjected to a particle swarm optimizer inboth the planar and grating configuration to optimize conditions which supported surface plasmon resonances (SPR) for chemical sensing. The objective functions for these configurations were based on absorption peak depth, full width at half maximum, or the enhancement factor (planar). Simple logic gates were constructed for both configurations which assessed if a lossy region was plasmonic by several figures of merit. The planar substrates returned viable sensing configurations for all of the metals tested, most notably bismuth metal at 2.1{\mu}m. The corrugated metal substrates also resulted in tuned SPRs. Most interestingly an optimized surface plasmon on the conductive polymer, polyaniline at 12{\mu}m, was also discovered.
Sensitivity and figure of merit (FoM) are the most significant performance metrics for surface plasmon resonance (SPR) based sensors. While designing an SPR based sensor, one of the major concerns rely in maximizing the sensitivity and accuracy of the sensor. In most of the SPR sensor designs, not only there is observed a trade-off between sensitivity and accuracy, but also these performance metrics are greatly influenced by different sensor parameters such as choice and layer thicknesses of plasmonic metals, adhesive layers, add-layers, field enhancement layers, and bio-recognition element (BRE) layers along with type of light coupling prisms/glasses. In this paper, rigorous analysis is carried out by considering most of the materials that are frequently used till date to achieve the optimized SPR sensor structure with high sensitivity and figure of merit (FoM). We have applied the inverse design approach utilizing the particle swarm optimization (PSO) method along with transfer matrix method (TMM) for this purpose. In this process, wide variety of frequently used sensor constituent layers are taken into account. The results indicate that a significantly high sensitivity, (
i.e
., 630.54 °/RIU) as well as FoM (
i.e
., 2277 RIU
-1
) can be achieved with the proposed method. The obtained results are closely compared with the sensor designs reported in the literature, and the comparison reveals a significant enhancement in both sensitivity and FoM. The findings of this study confirm the ample advantage and potential of utilizing this optimization approach for designing high-performance SPR sensors.
Surface plasmon resonance (SPR) sensor is a consolidated technology for analysis of biomolecular interaction, largely applied in biology and pharmaceutical research. The simulation of the surface plasmon optical excitation response is an important step in the development process of SPR based sensors. The structure, design and configuration of the desired sensor benefits from a previous simulated analyses of the generated responses, defining operational conditions and feasibility of the selected materials to composed the optical coupling layers. Here an online web-based SPR sensor’s simulator is presented. With a visual-oriented interface, enable drag & drop actions to easily and quickly model a variety of sensor arrangements. Presenting an embedded materials database for metals, glasses, 2D materials, nanoparticles, polymers, and custom substances, the simulator enables flexible configuration for sensors operating in angular and spectral modes, as well as localized SPR. The light propagation through the multilayer of materials is presented in terms of Fresnel coefficients, which are graphically displayed. The so-called SPR morphology parameters can be visualized. Moreover, sensor dynamic behavior could be knowledge by a Sensorgram simulation. Localized surface plasmon resonance (LSPR) in homogeneous and spherical nanoparticles is also present in the simulator. Simulated scenario’s in various configurations, designs and excitation were performed and compare with other simulator. The proposed simulator guarantees comparable results with low-code, agile, and intuitive flow of execution.
Surface plasmon resonance (SPR) based sensors are usually designed using the Kretschmann prism coupling configuration in which an input beam couples with a surface plasmon through a thin metal film. This is generally preferred by sensor developers for building planar devices instead of the Otto prism coupling configuration, which, for efficient coupling, requires the metal surface to be maintained at a distance on the order of the wavelength from the input prism surface. In this paper, we report on the microfabrication and characterization of an Otto chip device, which is suitable for applications of the SPR effect in gas sensing and biosensing.
We investigate the performance of Pd films for the development of H2 sensors based on the surface plasmon resonance (SPR) effect. Experimental measurements were carried out on glass substrates sputtered with Pd thin films, using a homemade automatic reflectometer based on Kretschmann's prism coupling configuration. The sensitivity for H2 detection measured experimentally was approximately 60% lower than that expected from calculations based on the optical constants tabulated in the literature, but exhibited the approximate trend in thickness dependency predicted theoretically. In spite of this difference, these results yield important findings for the design of SPR-based H2 sensors with maximum sensitivity.
The surface plasma wave technique for determining the dielectric constant ∊(ω) and the thickness d of a metal film without a preset expression for ∊(ω) is discussed. Two sets of solutions can be derived at a given frequency. By comparing d determined at another frequency, the correct ∊(ω) and d solution can be determined.
A new method of exciting nonradiative surface plasma waves (SPW) on smooth surfaces, causing also a new phenomena in total reflexion, is described. Since the phase velocity of the SPW at a metal-vacuum surface is smaller than the velocity of light in vacuum, these waves cannot be excited by light striking the surface, provided that this is perfectly smooth.However, if a prism is brought near to the metal vacuum-interface, the SPW can be excited optically by the evanescent wave present in total reflection. The excitation is seen as a strong decrease in reflection for the transverse magnetic light and for a special angle of incidence. The method allows of an accurate evaluation of the dispersion of these waves. The experimental results on a silver-vacuum surface are compared with the theory of metal optics and are found to agree within the errors of the optical constants.
Extinction coefficients k(λ) for water at 25°C were determined through a broad spectral region by manually smoothing a point by point graph of k(λ) vs wavelength λ that was plotted for data obtained from a review of the scientific literature on the optical constants of water. Absorption bands representing k(λ) were postulated where data were not available in the vacuum uv and soft x-ray regions. A subtractive Kramers-Kronig analysis of the combined postulated and smoothed portions of the k(λ) spectrum provided the index of refraction n(λ) for the spectral region 200 nm ≤ λ ≤ 200 μm.
Intensity interrogation of surface plasmon resonance (IISPR) biosensors possesses the greatest sensitivity beyond other interrogations and is operated at a fixed incident angle to enable real-time analysis without time delay, so that it promises excellent performance in biological/chemical detection and SPR imaging systems. Here we provide a general model to describe its sensitivity based on Lorentz equation and unveil the relation between the sensitivity and the metal thickness. This model presents the dependency between sensitivity and metal thickness, and the optimal thickness of gold layers to maximize the sensitivity in our experiment is 53 nm that agrees well in both measurement and simulation. This general model can be further applied in other intensity-interrogation SPR configurations as a design rule for sensing and imaging applications.
The surface-plasmon resonance (SPR) effect in metals is highly sensitive to fluctuations in the optical properties of the interface and has been frequently employed in the Kretschmann configuration for optical sensing. The operating conditions required for using the SPR effect for probing nonabsorbing media under maximum sensitivity are derived analytically under the Lorentzian approximation. It is found that the film thickness that maximizes sensitivity occurs when the radiation damping of the oscillation is half the intrinsic damping. Numerical results are presented for the spectral dependence of the optimum thickness as well as of the SPR parameters of gold, copper, silver, and aluminum films, useful for the design of optical sensors for both gaseous and aqueous environments.
We present models for the optical functions of 11 metals used as mirrors and contacts in optoelectronic and optical devices: noble metals (Ag, Au, Cu), aluminum, beryllium, and transition metals (Cr, Ni, Pd, Pt, Ti, W). We used two simple phenomenological models, the Lorentz–Drude (LD) and the Brendel–Bormann (BB), to interpret both the free-electron and the interband parts of the dielectric response of metals in a wide spectral range from 0.1 to 6 eV. Our results show that the BB model was needed to describe appropriately the interband absorption in noble metals, while for Al, Be, and the transition metals both models exhibit good agreement with the experimental data. A comparison with measurements on surface normal structures confirmed that the reflectance and the phase change on reflection from semiconductor–metal interfaces (including the case of metallic multilayers) can be accurately described by use of the proposed models for the optical functions of metallic films and the matrix method for multilayer calculations.
This paper focuses on the engineering and computer science aspects
of developments, applications, and resources related to particle swarm
optimization. Developments in the particle swarm algorithm since its
origin in 1995 are reviewed. Included are brief discussions of
constriction factors, inertia weights, and tracking dynamic systems.
Applications, both those already developed, and promising future
application areas, are reviewed. Finally, resources related to particle
swarm optimization are listed, including books, Web sites, and software.
A particle swarm optimization bibliography is at the end of the paper
Since the first application of the surface plasmon resonance (SPR) phenomenon for sensing almost two decades ago, this method has made great strides both in terms of instrumentation development and applications. SPR sensor technology has been commercialized and SPR biosensors have become a central tool for characterizing and quantifying biomolecular interactions. This paper attempts to review the major developments in SPR technology. Main application areas are outlined and examples of applications of SPR sensor technology are presented. Future prospects of SPR sensor technology are discussed.
In this paper the Evolutionary Method (EM) and the Particle Swarm Optimization (PSO), which are based on competitiveness and collaborative algorithms respectively, are investigated for plasmonic design. Actually, plasmonics represents a rapidly expanding interdisciplinary field with numerous devices for physical, biological and medicine applications. In this study, four EM and PSO algorithms are tested in two different plasmonic applications: design of surface plasmon resonance (SPR) based biosensors and optimization of hollow nanospheres used in curative purposes (cancer photothermal therapy). Specific problems-in addition of being multimodal and having different topologies are related to plasmonic design; therefore the most efficient optimization method should be determined through a comparative study. Results of simulations enable also to characterize the optimization methods and depict in which case they are more efficient.
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.
Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences.
SWSO- Surface Wave Sensor Optimizer
- L M Cavalcanti
- E Fontana