(2) (Figure , left) looks quite similar to the heuristic analysis of Figure . However, at the same time, this new one is significantly better. First, this is a completely "bottom-up" analysis, where the distinction between the clusters are automatically identified from the data (i.e., from the CG-MD trajectories). Second, it provides a deterministic rationale to group, for example, blue and yellow micro-clusters into a macro-cluster of ordered monomers in the fibers based on the similarity and proximity between the micro-states. Third, it is more complete, as for example we automatically capture the difference between orange and green monomers, which was neglected in Figure . The latter is far from being a trivial consideration. In fact, orange and green states are drastically different, as the orange diffusing monomers are not exactly part of the core stacking in the supramolecular polymer, but they are rather monomers having high mobility, which are separated from the stack of cores and are absorbed on the fiber surface. The ability to distinguish automatically the difference between such states is crucial. In fact, for example, the spontaneous surface diffusion of such orange (or red) absorbed monomers was recently demonstrated to be key in controlling the dynamics and dynamic adaptive properties of the skin of fiber (2). It is worth noting that this comparison has not only a structural meaning -e.g. showing that fiber (2) has more defects (green) than fiber (3) -but also a very important dynamical meaning.