Dimensional Nanostructures

Dimensional nanostructures are being intensely investigated to understand their unique properties and functionalities, driven by the need for advanced materials in various applications. Current research focuses on developing sophisticated computational methods, including machine learning algorithms like transformers and random forests, and advanced image analysis techniques (e.g., computer vision models) to characterize these structures accurately from microscopy and scattering data. These efforts aim to improve the efficiency and accuracy of nanomaterial analysis, enabling better design and optimization of devices and materials across diverse fields, from electronics to biomedicine. The development of physics-informed reduced-order models is also a key area, allowing for faster and more efficient simulations of complex nanostructures.