Approaches for deep-ultraviolet surface plasmon resonance sensors.

Aluminum (Al) is a preferred metal for designing deep-ultraviolet (DUV) surface plasmon resonance (SPR)-based sensors. The native oxide layer (alumina), which grows when the Al film is exposed to air, adds an extra layer to the multilayer stack and consequently affects the DUV-SPR sensing performance. To mitigate the performance loss in DUV-SPR-based sensing, new, to the best of our knowledge, approaches are considered here. We first consider chromium, indium (In), nickel, and platinum as alternative plasmonic materials to Al. In-film-based DUV-SPR sensors exhibit the best performance parameters compared to these alternative materials. We next consider the approach of replacing the native oxide layer by an ultrathin gold (Au) layer on top of bare Al or In. With an optimal Au thickness, higher sensitivity as compared to oxidized metals is observed. The next approach adds one or more graphene layers on top of the bare metal film. In this case, the performance depends on the number of graphene layers, but improvement in sensor characteristics in the DUV is also obtained. The use of Au or graphene overlayers increases the refractive index sensing dynamic range, which can be significant for In with these overlayers under certain operating conditions.

Numerical tool for estimating the dielectric constant, the thickness, and the coverage of immobilized inhomogeneous protein films on gold in aqueous solution.

A numerical simulation tool is reported for nanometer thin and inhomogeneous immobilized protein films on gold in aqueous solution. It allows for the first time, to the best of our knowledge, the simultaneous assessment of refractive index, film thickness, and surface coverage. The model relies on and combines the convective diffusion equation, the Langmuir adsorption isotherm, and the Helmholtz equation, with appropriate boundary conditions. These three differential equations were jointly solved using a multiphysics software. The physical film parameters were extracted employing an optimization procedure for immobilized bovine serum albumin, hemoglobin, and neutravidin films. The relatively good agreement between the extracted values for the refractive index, film thickness, and surface coverage and the corresponding values reported in the open literature show the correctness of the proposed methodology.

A novel simulador for agile and graphical modeling of surface plasmon resonance based 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.

SmartSPR sensor: Machine learning approaches to create intelligent surface plasmon based sensors.

Surface plasmon resonance (SPR) based sensors allow the evaluation of aqueous and gaseous solutions from real-time measurements of molecular interactions. The reliability of the response generated by a SPR sensor must be guaranteed, especially in substance detection, diagnoses, and other routine applications since poorly handled samples, instrumentation noise features, or even molecular tampering manipulations can lead to wrong interpretations. This work investigates the use of different machine learning (ML) techniques to deal with these issues, and aim to improve and attest to the quality of the real-time SPR responses so-called sensorgrams. A new strategy to describe a SPR-sensorgram is shown. The results of the proposed ML-approach allow the creation of intelligent SPR sensors to give a safe, reliable, and auditable analysis of sensorgram responses. Our arrangement can be embedded in an Intelligence Module that can classify sensorgrams and identify the substances presents in it. Also made it possible to order and analyze interest areas of sensorgrams, standardizing data, and supporting eventual audit procedures. With those intelligence features, the new generation of SPR-intelligent biosensors is qualifying to perform automated testing. A properly protocol for Leishmaniasis diagnosis with SPR was used to verify this new feature.

Polymer-based surface plasmon resonance biochip: construction and experimental aspects

Abstract Introduction: Surface plasmon resonance biosensors are high sensitive analytical instruments that normally employ glass materials at the optical substrate layer. However, the use of polymer-based substrates is increasing in the last years due to favorable features, like: disposability, ease to construction and low-cost design. Review Recently, a polymer-based SPR biochip was proposed by using monochromatic and polychromatic input sources. Its construction and experimental considerations are detailed here. Experimental considerations and results, aspects from performance characteristics (resonance parameters, sensitivity and full width at half maximum – FWHM – calculations) are presented for hydrophilic and hydrophobic solutions. It is included also a brief description of the state of the art of polymer-based SPR biosensors.