# Analysis of the Organic Chemical Fractions of Three Coal Extracts
## 3 Results and Discussion
### Cluster Analysis of the Chemical Composition of Three Kinds of Coal Sample Extracts  
The previous analysis reveals the chemical composition of the extracts at all levels, but it is not clear at which level of extraction a certain substance is completely extracted, and it is not easy to see the similarity of the relationship between the extracts. Thus, clustering analysis is the next level of categorization of the extracts, and by plotting the cluster analysis heat map, the features that are close based on the clustering are converted into a class. The heat map is one of the most commonly used methods for data visualization. However, because of the large differences in the content of each component, the extracts were first globally standardized [25] to reduce the differences between the components, and the standardized data were greatly improved compared to the previous one, so that the clustering of the components could be seen more clearly  
Figure 9 below shows the clustering heat map for the extracts of Pingshuo coal. Figure 8: Principal component analysis plot of three coal extracts. PS-CS\({}_{2}\): Pingshuo Coal CS\({}_{2}\) Extract; PS-HEX: Pingshuo Coal Hexane Extract; PS-BEN: Pingshuo Coal Benzene Extract; PS-MET: Pingshuo Coal Methanol Extract; PS-ACE: Pingshuo Coal Acetone Extract; PS-THF: Pingshuo Coal THF Extract; PS-THF/MET: Pingshuo Coal THF mixed with Methanol Extract. DT-CS\({}_{2}\): Datong CS\({}_{2}\) Extract; DT-HEX: Datong Hexane Extract; DT-BEN: Datong Benzene Extract; DT-MET: Datong Methanol Extract; DT-ACE: Datong Acetone Extract; DT-THF: Datong THF Extract; DT-THF/MET: Datong THF and Methanol Mixed Extract. GT-CS\({}_{2}\): Getting CS\({}_{2}\) Extract; GT-HEX: Getting Hexane Extract; GT-BEN: Getting Benzene Extract; GT-MET: Getting Methanol Extract; GT-ACE: Getting Acetone Extract; GT-THF: Getting THF extract; GT-THF/MET: Getting THF/Methanol mixed Extract. From the above clustering diagram of Pingshuo coal, it can be seen that the main components in the extract are aromatic and aliphatic hydrocarbons. Additionally, from the thermogram results, it can be seen that the extraction efficiency of each solvent varies a lot, and the extraction effect of CS\({}_{2}\) is much higher compared with other solvents, which may be related to the fact that CS\({}_{2}\) acts as the first-stage solvent. After extraction by CS\({}_{2}\), the extraction efficiency of the other solvents was poor. In the clustering results, aromatic hydrocarbons were clustered into a separate class. Aliphatic hydrocarbons were also clustered into a separate class. Alcohols, ketones, and nitrogen-containing compounds with high similarity were clustered into one group. Ester substances, other compounds, and acids were clustered together due to their close similarity, and furans and phenols were clustered separately. Figure 10 below shows the heat map of the clustering of Datong coal extracts. From the above Datong coal cluster diagram, it can be seen that the main components in the extract were aliphatic hydrocarbons, aromatic hydrocarbons, and alcohols. Additionally, from the thermogram results, it can be seen that the extraction effect of CS\({}_{2}\) was the best, and CS\({}_{2}\) and n-hexane extracted nearly all the aliphatic hydrocarbons and aromatic hydrocarbons in the coal samples. CS\({}_{2}\) extracted all the furans, nitrogenous compounds, and sulfurous compounds, and the other solvents extracted a small amount of organic compounds in the coal. The other solvents extracted a small amount of organic compounds  
Figure 10: Cluster analysis plot of Datong coal extracts. Figure 9: Cluster analysis plot of Pingshuo coal extracts. from the coal. From the clustering results, the aliphatic hydrocarbons and aromatic hydrocarbons in the extracts had a high degree of similarity, so they were clustered into one group. Alcohols, esters, and ketones were clustered separately because of the large similarity gap; acids, phenols, and esters were clustered.