Ring Stacking Analysis. Ring stacking interactions are the driving force behind many collective phenomena ranging from DNA base pairing, protein-drug binding, and through-space charge transfer in conjugated polymers. A class to identify ring-ring interactions has been developed for PySoftK v1.0. ProLIF 29 can also calculate ring stacking interactions, but only in protein-ligand systems. The approach implemented in PySoftK v1.0. has been specifically engineered for large soft matter systems, where ring-stacking interactions across more than two molecules can be calculated. PySoftK's ring-ring interaction algorithm consists of three stages; firstly, all atoms belonging to aromatic (conjugated) rings within the chosen molecules (or parts of molecules) are detected. Secondly, pairs of molecules within the system are screened using a cutoff to define molecules (or parts of molecules) in close contact. Finally, those molecules (or parts of molecules) which are found to be in contact are selected to have the necessary geometrical properties between their aromatic units calculated. The algorithm is explained in detail in the SI. The RSA class allows users to identify ring stacking patterns within a simulation and calculate the network formed by the stacking interactions and their evolution over time. This tool implemented in PySoftK 1.0 enables the user to perform this analysis based on minimal input parameters. These input parameters are: the maximum distance cutoff between two rings for which the ring stacking is calculated, the angle cutoff used to determine the range for which two rings are considered to be stacked, the frames on which to run the analysis and the output file name. Default values adopted are a distance cutoff of 10 Å and an angular cutoff of 20 • . This algorithm has been tested on amorphous F8BT (see Figure (a)) and the protein-potein interaction complex formed between TREM2 and DAP12 (see Figure ).