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Graphene is a promising materials platform for metasurface flat optics at terahertz wavelengths, with the important advantage of active tunability. Here we review recent work aimed at the development of tunable graphene metasurfaces for THz wavefront shaping (including beam-steering metamirrors and metalenses) and light emission. Various design strategies for the constituent meta-units are presented, ranging from metallic phase-shifting elements combined with a nearby graphene sheet for active tuning to graphene plasmonic resonators providing the required phase control or radiation mechanism. The key challenge in the development of these devices, related to the limited radiative coupling of graphene plasmonic excitations, is discussed in detail together with recently proposed solutions. The resulting metasurface technology can be expected to have a far-reaching impact on a wide range of device applications for THz imaging, sensing, and future wireless communications.

The d electron plays a significant role in determining and controlling the properties of magnetic materials. However, the d electron transitions, especially d–d emission, have rarely been observed in magnetic materials due to the forbidden selection rules. Here, we report an observation of d–d emission in antiferromagnetic nickel phosphorus trisulfides (NiPS3) and its strong enhancement by stacking it with monolayer tungsten disulfide (WS2). We attribute the observation of the strong d–d emission enhancement to the charge transfer between NiPS3 and WS2 in the type-I heterostructure. The d–d emission peak splits into two peaks, D1 and D2, at low temperature below 150 K, from where an energy splitting due to the trigonal crystal field is measured as 105 meV. Moreover, we find that the d–d emissions in NiPS3 are nonpolarized lights, showing no dependence on the zigzag antiferromagnetic configuration. These results reveal rich fundamental information on the electronic and optical properties of emerging van der Waals antiferromagnetic NiPS3.

The investigation of twisted stacked few‐layer MoS₂has revealed novel electronic, optical, and vibrational properties over an extended period. For the successful integration of twisted stacked few‐layer MoS₂into a wide range of applications, it is crucial to employ a noninvasive, versatile technique for characterizing the layered architecture of these complex structures. In this work, we introduce a machine learning‐assisted low‐frequency Raman spectroscopy method to characterize the twist angle of few‐layer stacked MoS₂samples. A feedforward neural network (FNN) is utilized to analyze the low‐frequency breathing mode as a function of the twist angle. Moreover, using finite difference method (FDM) and density functional theory (DFT) calculations, we show that the low‐frequency Raman spectra of MoS₂are mainly influenced by the effect of the nearest and second nearest layers. A new improved linear chain model (TA‐LCM) with taking the twist angle into the consideration is developed to understand the interlayer breathing modes of stacked few‐layer MoS₂. This approach can be extended to other 2D materials systems and provides an intelligent way to investigate naturally stacked and twisted interlayer interactions.