Carbon Nanotube

Carbon nanotubes (CNTs) are a focus of intense research due to their unique mechanical and structural properties, with current efforts concentrating on accurately characterizing their complex hierarchical structures and predicting their mechanical behavior. Advanced computational methods, including novel deep learning architectures (like ResNeXt-based models) and physics-informed generative language models (like MeLM), are being developed to analyze microscopy images, simulate CNT behavior, and even design new CNT-based materials. These advancements are crucial for optimizing CNT applications across diverse fields, from materials science and engineering to nanotechnology and beyond, by enabling more precise control over their synthesis and performance.