Intensity-Based Camera Setup for Refractometric and Biomolecular Sensing with a Photonic Crystal Microfluidic Chip.
Fabio Aldo KraftStefanie LehmannCarmela Di MariaLeonie JokschStefanie Fitschen-ÖsternSabine FuchsFrancesco Dell'OlioMartina GerkenPublished in: Biosensors (2023)
Label-free sensing is a promising approach for point-of-care testing devices. Among optical transducers, photonic crystal slabs (PCSs) have positioned themselves as an inexpensive yet versatile platform for label-free biosensing. A spectral resonance shift is observed upon biomolecular binding to the functionalized surface. Commonly, a PCS is read out by a spectrometer. Alternatively, the spectral shift may be translated into an intensity change by tailoring the system response. Intensity-based camera setups (IBCS) are of interest as they mitigate the need for postprocessing, enable spatial sampling, and have moderate hardware requirements. However, they exhibit modest performance compared with spectrometric approaches. Here, we show an increase of the sensitivity and limit of detection (LOD) of an IBCS by employing a sharp-edged cut-off filter to optimize the system response. We report an increase of the LOD from (7.1 ± 1.3) × 10 -4 RIU to (3.2 ± 0.7) × 10 -5 RIU. We discuss the influence of the region of interest (ROI) size on the achievable LOD. We fabricated a biochip by combining a microfluidic and a PCS and demonstrated autonomous transport. We analyzed the performance via refractive index steps and the biosensing ability via diluted glutathione S-transferase (GST) antibodies (1:250). In addition, we illustrate the speed of detection and demonstrate the advantage of the additional spatial information by detecting streptavidin (2.9 µg/mL). Finally, we present the detection of immunoglobulin G (IgG) from whole blood as a possible basis for point-of-care devices.
Keyphrases
- label free
- high speed
- high intensity
- optical coherence tomography
- high resolution
- high throughput
- magnetic resonance imaging
- computed tomography
- convolutional neural network
- machine learning
- health information
- energy transfer
- magnetic resonance
- social media
- gas chromatography
- single cell
- simultaneous determination
- cataract surgery