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Flatland Metasurfaces for Optical Gas Sensing.

Muhammad A Butt1

  • 1Institute of Microelectronics and Optoelectronics, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland.

Sensors (Basel, Switzerland)
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

Flatland metasurfaces offer advanced optical gas sensing by enhancing light-matter interactions at planar interfaces. This physics-driven review unifies diverse sensing methods, guiding the development of compact, integrated gas sensors.

Keywords:
THzflatlandgas sensingmetasurfacesvisible

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Area of Science:

  • Optics and Photonics
  • Materials Science
  • Chemical Sensing

Background:

  • Traditional gas sensing often relies on extended optical paths.
  • Metasurfaces enable light-matter interaction confinement to subwavelength interfaces.
  • Resonant energy storage and near-field enhancement are key metasurface principles.

Purpose of the Study:

  • To present a physics-driven perspective on metasurface-enabled optical gas sensing.
  • To unify diverse sensing modalities within a common perturbative framework.
  • To provide design guidance for compact and integrable gas sensing systems.

Main Methods:

  • Analysis of how gaseous analytes perturb engineered planar resonator eigenmodes.
  • Unified framework linking sensitivity to mode confinement, quality factor, and analyte overlap.
  • Examination of trade-offs across plasmonic, dielectric, polaritonic, and hybrid metasurface platforms (visible to terahertz).

Main Results:

  • Diverse sensing modalities (absorption, refractive index, loss, polarization, chemo-optical) are unified.
  • Sensitivity is linked to mode confinement, quality factor, and analyte overlap.
  • Fundamental trade-offs related to material dispersion, loss, and radiation balance are highlighted.

Conclusions:

  • Flatland metasurface architectures offer unique advantages for optical gas sensing.
  • Addressing chemical selectivity requires functional materials, multimodal transduction, and computational inference.
  • System-level factors like thermal stability and fabrication tolerance are crucial for real-world performance.