We investigate the utility of various statistical and machine learning techniques for classifying and quantifying selected proteins using an array of porous silicon sensors with uniquely tuned properties. No capture agents or bioreceptors are utilized for the protein detection. The sensing approach relies on differences in non-specific physisorption and represents a step towards a new low cost, simple and robust sensor platform that can detect a vast range of biomolecules.
We report the use of a peptide-based capture agent as an alternative to antibodies and nucleic acid-based bioreceptors for porous silicon biosensors. Click chemistry is employed to attach azide-functionalized streptavidin-binding peptides to alkyne-modified porous silicon films. The attachment of the streptavidin-binding peptide and subsequent detection of streptavidin molecules are verified using optical reflectance and Fourier transform infrared spectroscopy measurements.
Porous silicon (PSi) has been recognized as an advantageous material for use in optical biosensors due to its large internal surface area, ability to form multilayer optical structures, and compatibility with standard silicon lithographic techniques. We demonstrate an order of magnitude improvement in small molecule detection sensitivity for on-chip PSi ring resonators and photonic crystal nanobeams compared to the same structures fabricated on silicon-on-insulator wafers. Moreover, we demonstrate that PSi optical structures can be exploited for mobile diagnostics by using a smartphone with no additional functional accessories to detect color changes in the PSi that result from molecule capture.
The formation of resonant photonic structures in porous silicon leverages the benefit of high surface area for improved molecular capture that is characteristic of porous materials with the advantage of high detection sensitivity that is a feature of resonant optical devices. This review provides an overview of the biosensing capabilities of a variety of resonant porous silicon photonic structures including microcavities, Bloch surface waves, ring resonators, and annular Bragg resonators. Detection sensitivities > 1000 nm/RIU are achieved for small molecule detection. The challenge of detecting molecules that approach and exceed the pore diameter is also addressed.
A colorimetric biosensing system based on a porous silicon (PSi) rugate filter is demonstrated. Using an imaged-based technique that monitors RGB intensity, a spectral shift less than 0.25nm can be reliably detected. The porous silicon rugate filter demonstrates a sensitivity of 310 nm/RIU, which corresponds to a detection limit near 7×10-4 RIU. In this work, an external light source and camera are employed for proof-of-concept demonstration. By utilizing a smartphone camera LED and smartphone camera as the light source and detector, respectively, this system could serve as an effective, low-cost, point-of-care diagnostic tool.
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