To capture the reactive dynamics of ICM-102 molecules, 100 ps MD simulations were performed using the new NN potential (e.g., case 4 in Table ) with 64 ICM-102 molecules at 3000 K. The species evolution during ICM-102 decomposition predicted by NN and AIMD are compared in Fig. . It is clear that NN agrees well with the AIMD results, where ICM-102 molecules are rapidly consumed, and H2O is the main product. With the application of NN potential, the system size could be extended to thousands or even millions of atoms . Compared to the large oscillation in the predicted species evolution of AIMD, NNMD simulates an eight-times larger system, resulting in smooth species evolution. Such a large system allows studies on the macroscopic nature of a statistical ensemble, which is beyond the ability of the traditional AIMD method. In total, 5799 products are identified from the NNMD trajectories. Direct derivation of the reaction mechanism from thousands of products can be quite challenging. We propose an interactive reaction network to illustrate the detailed reaction mechanism. In Fig. , the full reaction network contains detailed pathways and intermediates. These intermediates are represented by fingerprints and clustered into eight groups using the k-means clustering algorithm . Groups 1 and 2 represent ICM-102 and molecules produced by releasing H, O and OH radicals, respectively.