Optically Resonant Nanophotonic Devices for Label-Free Biomolecular Detection

  • Julie Goddard
  • Sudeep Mandal
  • David Erickson
Part of the Integrated Analytical Systems book series (ANASYS)


Optical devices, such as surface plasmon resonance chips and waveguide-based Mach–Zehnder interferometers, have long been successfully used as label-free biomolecular sensors. Recently, however, there has been increased interest in developing new approaches to biomolecular detection that can improve on the limit of detection, specificity, and multiplexibility of these early devices and address emerging challenges in pathogen detection, disease diagnosis, and drug discovery. As we describe in this chapter, planar optically resonant nanophotonic devices (such as ring resonators, whispering gallery modes, and photonic crystal cavities) are one method that shows promise in significantly advancing the technology. Here we first provide a short review of these devices focusing on a handful of approaches illustrative of the state of the art. We then frame the major challenge to improving the technology as being the ability to provide simultaneously spatial localization of the electromagnetic energy and biomolecular binding events. We then introduce our “Nanoscale Optofluidic Sensor Arrays” which represents our approach to addressing this challenge. It is demonstrated how these devices serve to enable multiplexed detection while localizing the electromagnetic energy to a volume as small as a cubic wavelength. Challenges involved in the targeted immobilization of biomolecules over such a small area are discussed and our solutions presented. In general, we have tried to write this chapter with the novice in mind, providing details on the fabrication and immobilization methods that we have used and how one might adapt our approach to their designs.


Capture Probe Resonant Wavelength Evanescent Field Microring Resonator Local Refractive Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Julie Goddard
    • 1
  • Sudeep Mandal
  • David Erickson
    • 1
  1. 1.Sibley School of Mechanical and Aerospace EngineeringCornell UniversityIthacaUSA

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