2 Dimensional Material

Two-dimensional (2D) materials, atomically thin layers with unique properties, are a focus of intense research driven by their potential for diverse applications. Current efforts concentrate on computationally-driven discovery of novel 2D materials using machine learning techniques like generative models (e.g., variational autoencoders and transformer networks) and on characterizing their properties through advanced microscopy and data analysis methods, including deep learning for extracting band structure parameters from experimental data. This research is crucial for advancing fundamental understanding of materials science and for developing next-generation technologies in areas such as neuromorphic computing and biosensing.