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An image dataset of 10 different size molecules, where each molecule has2,000 structural variants, is generated from the 2D cross-sectional projectionof Molecular Dynamics trajectories. The purpose of this dataset is to provide abenchmark dataset for the increasing need of machine learning, deep learningand image processing on the study of scattering, imaging and microscopy.

A Molecular-MNIST Dataset for Machine Learning Study on Diffraction Imaging and Microscopy