Abstract

Chirality, the absence of mirror symmetry, is predominant in nature. The chiral nature of the electromagnetic field behaves differently with chiral matter for left circularly polarized and right circularly polarized light. The chiroptical behavior in the sensing of naturally occurring chiral objects is weak, and improving the chiroptical response enhances the chiral sensing platform. This review covers the fundamental concepts of chiral metasurfaces and various types of single- and multi-layered chiral metasurfaces. In addition, we discuss tunable and deep-learning-based chiral metasurfaces. Tunability is achieved by manipulating the meta-atom’s property in response to external stimuli for applications such as optical modulation, chiral photonics, advanced sensing, and adaptive optics. Deep-learning modeling techniques, such as CNNs and GANs, offer efficient learning of the complex relationships in data, enabling the optimization and accurate prediction of chiral metasurface properties. The challenges in the design and fabrication of chiral metasurface include achieving broadband performance and scalability and addressing material limitations. Chiral metasurface performance is evaluated by optical rotation, circular dichroism enhancement, and tunability, which are quantified through the spectroscopic measurement of circular dichroism and optical rotation. Chiral metasurface progress enables applications, including metaholography, metalenses, and chiral sensing. Chiral sensing improves the detection of pharmaceuticals and biomolecules, increasing the sensitivity and accuracy of analytical diagnostics.

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