Here, we proposed a descriptor encoding the polarization and conformation entropy into the atom-centered symmetry functions (ACSFs), named q -ACSFs con f , and married it with a highdimensional neural network (HDNN), as shown in Figure . (A detailed structure of HDNN could be found in Section S12) Comparing with the atomic-based or fragment-based model and molecular descriptors based model, our model features in the following three aspects: (i) bypassing the laborious jobs in dividing the whole molecules into separate fragments or atoms and constructing descriptors automatically; (ii) no need for the various descriptors which may be difficult and computationally costly to obtain; (iii) adding physically explainable elements by explicitly taking the polarization effects and conformation entropy into consideration.