Devolatilization predicting model based on coal heterogeneous chemical structure from micro-Raman spectroscopy with neural network
This study proposes a novel devolatilization model based on a convolutional neural network (CNN), employing quantified coal chemical structure features as input. Initially, a reliable method was developed to quantify the average/heterogeneous properties of coal structures using high-resolution micro-Raman spectroscopy. The evolution of chemical structure with increasing coal rank was investigated