The main purpose of this step is to create an initial dataset to trigger the concurrent learning process. Firstly, 1ps reactive MD simulation with the DFTB+ software was performed starting from the initial reactants in part A and part B, respectively. The NVT ensemble was employed and the non-self-consistent DFTB (NSCC-DFTB) parameter set "matsci" (55) was used to describe the interatomic interaction. Berendsen thermostat (46) was used to control the temperature at 1750K and 2000 K, respectively. Then, a molecular cluster was created for each atom (defined as the center atom) in the trajectory, which contains the center atom and any molecular species within a 5 Å distance cutoff from it. After this step one might obtain tens of thousands of molecular clusters, which have heavy redundancy. These clusters were first classified according to the bond-type of the center atom and then the k-means clustering algorithm was used to remove the redundancy. Details of relevant methods can be found in our previous study . Finally, an initial dataset containing 1000 molecular clusters was obtained.