Sim-SPR: an Open-Source Surface Plasmon Resonance Simulator for Academic and Industrial Purposes

Costa, Elton Brasil da; Rodrigues, Eloise P.; Pereira, Helder A.

doi:10.1007/s11468-019-00970-5

Cited by 10 publications

(3 citation statements)

References 26 publications

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“…Unfortunately, the processing of SPR/LSPR data is frequently a manual and time-consuming task. This is evident in software solutions like Anabel [16] and Sim-SPR [17]. Some applications include an important feature in their products: visualization of raw signal processing and analysis.…”

Section: Introductionmentioning

confidence: 99%

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation

Zhou,

Geng

2024

Micromachines

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The LSPR biosensor chip is a groundbreaking tool popular in laboratory settings for identifying disease markers. However, its use in clinical environments is not as widespread. One notable gap is the lack of a universal signal processing tool for LSPR biosensing. To escalate its precision, there is an emerging need for software that not only optimizes signal processing but also incorporates self-verification functionalities within LSPR biochemical sensors. Enter the visual LSPR sensor software—an innovative platform that processes real-time transmission or reflection spectra. This advanced software adeptly captures the nuanced structural changes at the nanostructure interface prompted by environmental fluctuations. It diligently records and computes a suite of parameters, including the resonance wavelength shift, full width at half maximum, sensitivity, and quality factor. These features empower users to tailor processing algorithms for each data capture session. Transcending traditional instruments, this method accommodates a multitude of parameters and ensures robust result validation while tactfully navigating nanostructure morphology complexities. Forsaking third-party tool dependencies, the software tackles challenges of precision and cost-effectiveness head-on, heralding a significant leap forward in nanophotonics, especially for high-throughput LSPR biosensing applications. This user-centric innovation marks substantial progress in biochemical detection. It is designed to serve both researchers and practitioners in the field of nanophotonic sensing technology, simplifying complexity while enhancing reliability and efficiency.

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Section: Introductionmentioning

confidence: 99%

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation

Zhou,

Geng

2024

Micromachines

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“…A diversity of surface plasmon simulators can be found elsewhere [7]- [16]. Briefly, examples like the WinSpall [7], [8], SimSPR [12], PAME [10] and SWSO [11] offers simulations in terms of Fresnel equations [3] for the surface plasmons excitation based on the attenuated total reflection method (ATR) [5], in both Kretschmann [1] and Otto [2] so-called configurations. Surface plasmon excitation approaches for Localized-SPR with nanoparticle simulations can be also founded in PAME and in Scattport.org website [16].…”

Section: Introductionmentioning

confidence: 99%

EasySPR: a web simulador for agile modeling surface plasmon resonance based sensors

Gomes

Oliveira

2022

Preprint

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Surface plasmon resonance (SPR) sensor is a technology for analysis of biomolecular interaction, largely applied in biology and pharmaceutical research. The simulation of the surface plasmon optical excitation is an important steps of the development process for sensors based on this phenomenon. The structure, design and configuration of the desired SPR sensor benefits from previously simulated, analyzing the responses generated and check the feasibility of the materials selected for the optical coupling. Here a online web-based SPR sensor's simulator is presented. With visual-oriented interface, enable drag \& drop actions to easily and quickly modeling a variety of sensors arrangement. The embedded materials database for metals, glasses, polymers and custom substance enable flexible configuration for sensors operating in angular and spectral modes. 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. Sensor dynamic behavior could be wispy knowledge by the Sensorgram simulation. Simulation scenario's in various configurations, designs and excitation were performed and compare with other simulator. The proposed simulator guarantee comparable results with an agile and intuitive flow of execution.

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“…Surface Plasmon Resonance Sensor Theory Concepts Using multilayer structures arranged on a prism, planar, grating, or cylindrical waveguides topped with a thin metallic layer, (SPR) can happen [15]. The Otto [16] and Kretschmann arrangements [17] are metal-dielectric arrangements to prism coupling for (SPR) excitation . In the two configurations, the polarized light ray is reflected from the separating surface between the prism and the thin metal layer to be received by a sensitive detector.…”

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confidence: 99%

Surface Plasmon Resonance (SPR) Simulation of a Gold-Bismuth Bi-layer Gas Sensor

Ulwali

Abbas

Karam

et al. 2022

eijs

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The features of plasmonic surface frequency sensor technology, such as the small number of sensor samples required, electromagnetic interference, and high sensitivity, have been found to be highly important.. In this paper, a simulation program was created in Matlab_b2018 by adopting Fresnel equations for calculating the reflectivity of the electromagnetic wave between different media. A surface plasmon resonance sensor based on electromagnetic wavelengths within the range (100 nm to 1000 nm) has been proposed. The transfer matrix was used for a system consisting of four different media. The first medium is a semicircular BK7 glass prism, the second medium is a gold layer (40 nm thick), then a bismuth layer of variable thicknes(10–80) nm, and the last medium is air as the sensing medium. The surface plasmon resonance (SPR) technique was adopted based on the Kretschmann configuration in the simulation of the proposed system. The simulation results showed that there is no SPR within the range of wavelengths (100-500nm), while SPR appears in the visible region and in the IR region at wavelengths (900 and 1000nm). The SPR phenomenon starts to weaken gradually with an increase in the thickness of the bismuth layer. The full width at half maximum (FWHM) decreases with the decrease of thickness of bismuth layer. The best value for it is (10) at thickness (d=10 nm) and wavelength (900 nm). While the height (H) of the SPR dip increased, with the best value of (0.95) at thickness (d=10 nm) and wavelength (700 nm). Also, the sensitivity increased with increasing the bismuth layer thickness at wavelengths (700 , 800, and 1000 ) nm. The highest obtained sensitivity(S) was (112.5 deg/RIU).

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Sim-SPR: an Open-Source Surface Plasmon Resonance Simulator for Academic and Industrial Purposes

Cited by 10 publications

References 26 publications

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation

EasySPR: a web simulador for agile modeling surface plasmon resonance based sensors

Surface Plasmon Resonance (SPR) Simulation of a Gold-Bismuth Bi-layer Gas Sensor

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