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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.

 

In this review paper, we summarized the recent progress of using graphene as a sensing platform for environmental applications. Especially, we highlight the electrical and optical sensing devices developed based on graphene and its derivatives. We discussed the role of graphene in these devices, the sensing mechanisms, and the advantages and disadvantages of specific devices. The approaches to improve the sensitivity and selectivity are also discussed. 

Correlated-electron systems have long been an important platform for various interesting phenomena and fundamental questions in condensed matter physics. As a pivotal process in these systems, d-d transitions have been suggested as a key factor toward realizing optical spin control in two-dimensional (2D) magnets. However, it remains unclear how d-d excitations behave in quasi-2D systems with strong electronic correlation and spin-charge coupling. Here, we present a systematic electronic Raman spectroscopy investigation on d-d transitions in a 2D antiferromagnet—NiPS 3 , from bulk to atomically thin samples. Two electronic Raman modes originating from the scattering of incident photons with d electrons in Ni 2+ ions are observed at ~1.0 eV. This electronic process persists down to trilayer flakes and exhibits insensitivity to the spin ordering of NiPS 3 . Our study demonstrates the utility of electronic Raman scattering in investigating the unique electronic structure and its coupling to magnetism in correlated 2D magnets. 

Advanced microscopy and/or spectroscopy tools play indispensable roles in nanoscience and nanotechnology research, as they provide rich information about material processes and properties. However, the interpretation of imaging data heavily relies on the “intuition” of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, the optical characterization of 2D materials is used as a case study, and a neural‐network‐based algorithm is demonstrated for the material and thickness identification of 2D materials with high prediction accuracy and real‐time processing capability. Further analysis shows that the trained network can extract deep graphical features such as contrast, color, edges, shapes, flake sizes, and their distributions, based on which an ensemble approach is developed to predict the most relevant physical properties of 2D materials. Finally, a transfer learning technique is applied to adapt the pretrained network to other optical identification applications. This artificial‐intelligence‐based material characterization approach is a powerful tool that would speed up the preparation, initial characterization of 2D materials and other nanomaterials, and potentially accelerate new material discoveries.