Protein sensing using deep subwavelength-engineered photonic crystals.

We demonstrate a higher sensitivity detection of proteins in a photonic crystal platform by including a deep subwavelength feature in the unit cell that locally increases the energy density of light. Through both simulations and experiments, the sensing capability of a deep subwavelength-engineered silicon antislot photonic crystal nanobeam (PhCNB) cavity is compared to that of a traditional PhCNB cavity. The redistribution and local enhancement of the energy density by the 50 nm antislot enable stronger light-molecule interaction at the surface of the antislot and lead to a larger resonance shift upon protein binding. This surface-based energy enhancement is confirmed by experiments demonstrating a nearly 50% larger resonance shift upon attachment of streptavidin molecules to biotin-functionalized antislot PhCNB cavities.

Peptide-Based Capture of Chikungunya Virus E2 Protein Using Porous Silicon Biosensor.

The detection of pathogens presents specific challenges in ensuring that biosensors remain operable despite exposure to elevated temperatures or other extreme conditions. The most vulnerable component of a biosensor is typically the bioreceptor. Accordingly, the robustness of peptides as bioreceptors offers improved stability and reliability toward harsh environments compared to monoclonal antibodies that may lose their ability to bind target molecules after such exposures. Here, we demonstrate peptide-based capture of the Chikungunya virus E2 protein in a porous silicon microcavity biosensor at room temperature and after exposure of the peptide-functionalized biosensor to high temperature. Contact angle measurements, attenuated total reflectance-Fourier transform infrared spectra, and optical reflectance measurements confirm peptide functionalization and selective E2 protein capture. This work opens the door for other pathogenic biomarker detection using peptide-based capture agents on porous silicon and other surface-based sensor platforms.

Morlet Wavelet Filtering and Phase Analysis to Reduce the Limit of Detection for Thin Film Optical Biosensors.

The ultimate detection limit of optical biosensors is often limited by various noise sources, including those introduced by the optical measurement setup. While sophisticated modifications to instrumentation may reduce noise, a simpler approach that can benefit all sensor platforms is the application of signal processing to minimize the deleterious effects of noise. In this work, we show that applying complex Morlet wavelet convolution to Fabry-Pérot interference fringes characteristic of thin film reflectometric biosensors effectively filters out white noise and low-frequency reflectance variations. Subsequent calculation of the average difference in extracted phase between the filtered analyte and reference signals enables a significant reduction in the limit of detection (LOD). This method is applied on experimental data sets of thin film porous silicon sensors (PSi) in buffered solution and complex media obtained from two different laboratories. The demonstrated improvement in the LOD achieved using wavelet convolution and average phase difference paves the way for PSi optical biosensors to operate with clinically relevant detection limits for medical diagnostics, environmental monitoring, and food safety.

High contrast cleavage detection for enhancing porous silicon sensor sensitivity.

Using porous silicon (PSi) interferometer sensors, we show the first experimental implementation of the high contrast cleavage detection (HCCD) mechanism. HCCD makes use of dramatic optical signal amplification caused by cleavage of high-contrast nanoparticle labeled reporters instead of the capture of low-index biological molecules. An approximately 2 nm reflectance peak shift was detected after cleavage of DNA-quantum dot reporters from the PSi surface via exposure to a 12.5 nM DNase enzyme solution. This signal change is 20 times greater than the resolution of the spectrometer used for the interferometric measurements, and the interferometric measurements agree with the response predicted by simulations and fluorescence measurements. These proof of principle experiments show a clear path to achieving a real-time, highly sensitive readout for a broad range of biological diagnostic assays that generate a signal via nucleic acid cleavage triggered by specific molecular binding events.

Thermally Carbonized Porous Silicon for Robust Label-Free DNA Optical Sensing.

In this work, thermal carbonization is shown to provide the necessary surface passivation to enable highly robust DNA detection on a porous silicon (PSi) platform, overcoming previous corrosion challenges with detection of negatively charged biomolecules. The stability of thermally carbonized PSi (TCPSi), oxidized PSi (OPSi), and undecylenic acid-modified PSi (UAPSi) is compared in phosphate-buffered saline and during DNA sensing experiments. Reflectance measurements reveal an improvement in stability and DNA sensor response for TCPSi compared to OPSi and UAPSi. TCPSi exhibits a large positive sensor response with >90% DNA hybridization efficiency. In comparison, UAPSi shows a smaller positive DNA sensor response, likely lessened by a small corrosion effect, while OPSi exhibits a large negative sensor response, indicating significant induced PSi corrosion that confounds the ability of OPSi to yield meaningful readouts of DNA hybridization events. This work expands the application of TCPSi for its more widespread usage in sensing applications where competing substrate corrosion may influence device stability.

A smartphone biosensor based on analysing structural colour of porous silicon.

We report a smartphone compatible, low-cost porous silicon biosensor, which correlates the structural colour of a porous silicon microcavity (PSiM) to spectral peak position. Molecules captured in the PSiM cause a colour change that can be quantified through image analysis. Minimal external accessories are employed. Spectrometer measurements of the PSiM reflectance spectrum shifts are carried out concurrently with the smartphone measurements to benchmark the accuracy of the smartphone biosensor. We estimate that the smartphone biosensor supports an equivalent accuracy of 0.33 nm for the detection of colour changes corresponding to spectral shifts of the PSiM. Biosensing functionality is demonstrated using a biotin-streptavidin assay with an estimated detection limit of 500 nM. The PSiM-smartphone biosensor is a promising platform for label-free point of care diagnostics.