fig4

Figure 4. Training performance of LSTM models in predicting the evolution of reduced microstructure with different training time frames. The training loss of LSTM models for predicting the top four autoencoder-reduced microstructural features of compositional field, c, using (A) 80 time frames, (B) 60 time frames, (C) 40 time frames, and (D) 20 time frames as the training dataset. The grey dashed lines indicate the starting time frame for LSTM prediction, and the dotted lines after grey dashed lines represent the LSTM-predicted feature values of reduced microstructure evolving as time frames until the last 100 time frame. LSTM: Long short-term memory.