Characterizing the structures, interactions, and dynamics of molecules in their native liquid state is a long-existing challenge in chemistry, molecular science, and biophysics with profound scientific significance. Advanced transmission electron microscopy (TEM)-based imaging techniques with the use of graphene emerged as promising tools, mainly due to their performance on spatial and temporal resolution. This review focuses on the various approaches to achieving high-resolution imaging of individual molecules and their transient interactions. We highlight the crucial role of graphene grids in cryogenic electron microscopy for achieving Ångstrom-level resolution for resolving molecular structures and the importance of graphene liquid cells in liquid-phase TEM for directly observing dynamics with subnanometer resolution at a frame rate of several frames per second, as well as the cross-talks of the two imaging modes. To understand the chemistry and physics encoded in these molecular movies, incorporating machine learning algorithms for image analysis provides a promising approach that further bolsters the resolution adventure. Besides reviewing the recent advances and methodologies in TEM imaging of individual molecules using graphene, this review also outlines future directions to improve these techniques and envision problems in molecular science, chemistry, and biology that could benefit from these experiments.
Keywords: Cryogenic electron microscopy; Graphene EM grid; Graphene liquid cell; Image processing; Liquid-phase transmission electron microscopy; Machine learning; Macromolecules; Nucleic acids; Protein.