Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 42,
  • Issue 19,
  • pp. 6948-6957
  • (2024)

A Highly Sensitive Biosensing Method Using Differential Detection of Fano Resonance Lineshape

Not Accessible

Your library or personal account may give you access

Abstract

We propose a quad-stub microwave differential sensor which exhibits a single electromagnetic transparency window and Fano resonance when operated under symmetrical resonant conditions. When the resonance balance is slightly disturbed by introducing small dielectric variations on one of the stub pairs, a second transparency window appears in the stop-band whose amplitude corresponds to the extent of the differential imbalance. The narrow sensing window falls within the frequency range of 2.25–2.5 GHz. The differential sensing can be exploited in highly sensitive chemical sensing problems such as to differentiate quality of biofuel samples. Experimentally, the concept has been demonstrated by detecting ethanol concentration in aqueous solutions with varying molality. The high sensitivity is shown by resolving a 2.5% v/v ethanol-aqueous concentration. The compact design facilitates measurements for sample volumes as small as approximately 20 $\mu$ L. A good agreement is demonstrated between simulation and experimental results. Overall, the proposed sensor possesses a simple and compact geometry that can also be scaled to operate at optical frequencies. Furthermore, a metal slot waveguide structure is also designed to demonstrate the differential sensing mechanism adaptability to THz frequencies. The ease of operation and its capability to detect minor differences samples make it a competent candidate for high-sensitivity sensing applications in biofuel detection and biomedical sensing.

PDF Article

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.