Photonics (Apr 2025)

Metasurfaces in Optical Biosensing: Revolutionizing Detection Techniques and Shaping the Future

  • Sunil Kumar,
  • Harbinder Singh,
  • Dhiraj Kumar Singh

DOI
https://doi.org/10.3390/photonics12040360
Journal volume & issue
Vol. 12, no. 4
p. 360

Abstract

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Metasurfaces have been widely investigated across the disciplines of optical biosensing due to their exceptional ability to manipulate electromagnetic fields. Consequently, over the past few years, there has been growing interest in the application of metasurfaces in optical biosensors in the field of biomedical sensing. While being label-free and offering real-time tracking, high sensitivity, and a quick response are among the benefits of conventional optical biosensors, the incorporation of metasurfaces improves their wavefront manipulation, selectivity for versatile sensing, and capacity for device miniaturization to satisfy increasingly complex application requirements. Furthermore, there is a lack of comprehensive evaluations that address the current research developments and future possibilities, despite the encouraging advancements in this emerging field. Hence, this work provides a comprehensive review and serves as a valuable resource for researchers exploring metasurface-based optical biosensors. This review delves into defining the basic sensing concepts, design procedures, and important figures of merit (FOM) for metasurface-based optical biosensors and their applications, including the detection of numerous analytes, such as viruses, toxins, antibodies, tumors, and drugs and the monitoring of blood sugar. Furthermore, presenting a critical evaluation of structural fabrication techniques with a view toward potential future commercialization, this review ends by highlighting several fascinating areas for further investigation. For this review article, a total of 5844 effective documents about metasurface optical biosensors were retrieved from the Scopus database. The VOSviewer version 1.6.20 bibliometric software was used for the scientific analysis of the data retrieved from the Scopus database from 2010 to 2025.

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