Results
Studies on Sensors Used for the Detection of Biological Biomarkers through Near-Field and Far-Field Microscopy Techniques
In this stage, dedicated studies were conducted to characterize sensors designed for the detection of biological biomarkers, using complementary near-field and far-field microscopy techniques. The combined approach enables the investigation of both the global optical properties of the sensors (uniformity, refractive index, plasmonic behavior) and the local nanometric-scale phenomena that are inaccessible through conventional methods. Through near-field microscopy in an s-SNOM (scattering-type scanning near-field optical microscopy) configuration, correlated topographical and optical information will be obtained regarding the distribution of the electromagnetic field on the surface of the active metallic elements and the manner in which this distribution is influenced by functionalization and interaction with biomarkers. The integration of data from the two types of techniques allows the evaluation of detection mechanisms, the identification of possible inhomogeneities or critical defects, and the optimization of sensor design to improve sensitivity and reproducibility. This stage thus contributes to the experimental foundation necessary for the development of advanced sensors for biomarker detection.
Activity 1: Use of Far-Field and Near-Field Microscopy Techniques for the Characterization of Sensors Used in Biological Marker Detection – Experimental Development
Far-Field Microscopy
Far-field microscopy (typical for brightfield imaging) is one of the most widely used optical methods for observing biological and material samples. In this configuration, the light beam reaches the sample and is subsequently collected either in transmission or reflection using a standard objective, with the resulting image being characterized by a resolution limited by light diffraction (approximately 300 nm laterally under optimal conditions). The observed optical signal is primarily the contrast generated by light absorption or scattering by structures within the sample, which enables the identification of shapes, sizes, and distributions of cells, tissues, or particles. The advantages of this technique include simplicity, rapid acquisition, and the ability to analyze large regions of the sample in a non-invasive manner.
Regarding resolution, there are far-field microscopy techniques (such as stimulated emission depletion microscopy – STED) that can achieve resolutions of 20–50 nm; however, STED can only be applied to fluorescent samples. In the case of the sensors investigated in this stage, the samples are non-fluorescent; therefore, only brightfield microscopy can be employed in the far-field regime.
In the context of advanced research, far-field microscopy is often used complementarily with near-field microscopy to select the regions of interest to be investigated at the nanometric scale. Brightfield microscopy enables rapid imaging of the entire surface and highlights areas with morphological particularities, defects, or relevant structures, which can subsequently be examined with higher-resolution near-field techniques. Thus, far-field microscopy remains a fundamental tool for initial screening, contextualization, and guidance in detailed nanometric-level analysis.
Near-Field Microscopy
In this activity, we employed scattering-type near-field optical microscopy (s-SNOM) techniques for the characterization of sensors designed for exosome detection. The investigated sensors are fabricated on Si substrates and contain micro-structured Au electrodes that function as active elements for interaction with exosomes and specific bioreceptors (e.g., antibodies).
Using s-SNOM together with AFM (atomic force microscopy), local optical and topographical information (AFM) can be simultaneously obtained with nanometric resolution (on the order of tens of nanometers), enabling the correlation of Au electrode roughness and morphology with their local optical properties. Near-field images (amplitude and phase) can be recorded at different wavelengths relevant to the intended sensing operation and to the absorption bands associated with exosomes.
The s-SNOM investigations were performed by illuminating the AFM tip with a laser beam and detecting the scattered light, enabling:
- simultaneous acquisition of topography and local optical signal (amplitude and phase)
- lateral resolution of ~30 nm
- mapping of the electromagnetic field distribution on the Au regions
- identification of local variations induced by the biomolecular layer.
Simple Electro-Chemical Sensors
The sensors were fabricated by Xsensio (Switzerland) on Si chips with Au metallic regions deposited through standard techniques (physical evaporation/sputtering), followed by photolithographic patterning. The dimensions and geometry of the active regions were selected to ensure compatibility with biochemical functionalization and near-field analysis.
A SiO₂ layer was subsequently deposited for passivation and electrical insulation of the tracks, and to define the active windows (Au electrodes). Thus, the Au electrode surface appears “deeper” than the passivation layer surface due to the defined window regions.
Surface preparation included:
- Preliminary cleaning (solvents)
- Functionalization with a specific capture layer for exosomes
- Controlled incubation in exosome suspensions of defined concentration
- Washing and drying steps.
Electro-Chemical Sensors with Periodic Nanostructures
Exosome aggregation on the sensor surface is an issue that may cause measurement distortions. For this reason, periodic nanostructures were fabricated on the active region of the sensor by Xsensio. The Au nanostructures were created through sputtering and electron beam lithography, having the shape of nano-pillars designed to enable individual attachment of exosomes (thus preventing aggregation) while also increasing the signal-to-noise ratio by enhancing the surface-to-volume ratio.
Surface preparation for s-SNOM imaging followed the same steps as for simple electro-chemical sensors.
Objectives of s-SNOM Imaging
A first objective of the investigations was to characterize the initial surface state: optical field distribution in the absence of exosomes, potentially after biochemical functionalization. This allows evaluation of optical response uniformity on Au electrodes, identification of possible defects (inhomogeneities, residual particles, aggregates), and their influence on near-field distribution.
Subsequently, s-SNOM measurements were carried out after sensor exposure to exosome suspensions under controlled conditions (concentration, incubation time, washing procedures). We monitored near-field signal changes on Au electrodes associated with:
- formation of a biomolecular layer on the metallic surface
- changes in local dielectric properties (effective refractive index, absorption)
- possible occurrence of modified plasmonic modes due to coupling between the metallic field and the exosome layer.
Comparative analysis of s-SNOM images before and after exosome binding allows identification of local optical “signatures” (amplitude/phase contrast, spectral variations) correlated with exosome presence and density on the sensor surface. Thus, near-field imaging will be used both for optimizing Au electrode design (geometry, dimensions, roughness) and for validating the nanoscale detection mechanism.
The results will contribute to understanding the relationship between microscopic sensor structure, local optical properties, and exosome sensitivity, providing relevant parameters for improving detection performance and for future functional calibrations (e.g., detection limits, selectivity).
Activity 2: Characterization of Sensors Fabricated by Xsensio for Biomarker Detection Optimization
For sensor characterization, a series of topographic and near-field parameters were evaluated on different sensor regions. Regarding topography, we examined height differences (between materials), average height, and roughness (Sq).
s-SNOM images were qualitatively evaluated in terms of amplitude and phase variations, based on the proportionality between:
- s-SNOM amplitude and reflectivity
- s-SNOM phase and optical absorption.
Therefore, parameters extracted from s-SNOM images included mean amplitude and phase values, phase difference (when two materials were present), and standard deviation of amplitude and phase.