Deep-learning prediction of safety moiety of salen-type complex crystals towards explosive perchlorate salts

Abstract

Perchlorate compounds are well-known for their explosive and hazardous nature. Considering previously reported perchlorate crystals of salen-type manganese (III) complexes, our study aimed to identify the specific molecular/crystal structure responsible for their explosive properties. Employing deep learning, we conducted an analysis of the Hirschfeld surface for salen-type metal complexes within a crystal structure database. The results indicate that the salen-type complex site lacks distinctive structural features, attributing its explosive potential to the chemical bonding of the perchlorate ion and the surrounding intermolecular interactions.

Keywords

• Perchlorate
• Explosive
• Crystal structure
• Hirshfeld surface analysis
• Deep learning