Analysis of the Relationships between Synthesis Conditions and Structures of Zeolites Using Machine Learning

The relationships between synthesis conditions and obtained structures of SDA-free aluminosilicate zeolites were analyzed using machine learning.Topology prediction indicated that misclassified topologies often shared a common composite building unit (CBU) with the actual topology.Binary classification characterized whether a specific CBU was observed in the products and visualized the distribution trends using t-SNE.The analysis results imply that zeolites containing mor or sod as CBUs in the framework are more likely to crystallize through these CBUs than zeolites containing can or d6r.