Dataset of TEM Images for Carbon Nanomaterial Classification

We employed a convolutional neural network (CNN) for a machine learning and computer vision approach to recognize and classify airborne CNT (carbon nanotubes) and CNF (carbon nanofibers) particles from transmission electron microscope (TEM) images. The model we developed creates a framework for the automatic detection and classification of complex carbon nanostructures, with potential applications in the automated structural classification of other nanomaterials. This dataset comprises 5,323 grayscale TEM images of various nanostructured carbon samples classified into five categories: Cluster, Fiber, Matrix, Matrix-Surface, and Non-CNT. For more information about the data collection and classification process, please refer to https://doi.org/10.1039/D0NA00634C.