Photonic crystal enhanced cytokine immunoassay.

Patrick C. Mathias, Nikhil Ganesh, Brian T. Cunningham

Research output: Contribution to journalArticlepeer-review


Photonic crystal surfaces are demonstrated as a means for enhancing the detection sensitivity and resolution for assays that use a fluorescent tag to quantify the concentration of an analyte protein molecule in a liquid test sample. Computer modeling of the spatial distribution of resonantly coupled electromagnetic fields on the photonic crystal surface are used to estimate the magnitude of enhancement factor compared to performing the same fluorescent assay on a plain glass surface, and the photonic crystal structure is fabricated and tested to experimentally verify the performance using a sandwich immunoassay for the protein Tumor Necrosis Factor-alpha (TNF-alpha). The demonstrated photonic crystal fabrication method utilizes a nanoreplica molding technique that allows for large-area inexpensive fabrication of the structure in a format that is compatible with confocal microarray laser scanners. The signal-to-noise ratio for fluorescent spots on the photonic crystal is increased by at least five-fold relative to the glass slide, allowing a TNF-alpha concentration of 1.6 pg/ml to be distinguished from noise on a photonic crystal surface. In addition, the minimum quantitative limit of detection on the photonic crystal surface is one-third the limit on the glass slide - a decrease from 18 pg/ml to 6 pg/ml. The increased performance of the immunoassay allows for more accurate quantitation of physiologically relevant concentrations of TNF-alpha in a protein microarray format that can be expanded to multiple cytokines.

Original languageEnglish (US)
Pages (from-to)1036-1038
Number of pages3
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics


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