Data-driven exploration of AB 2 X 4 (X = O, S, Se, Te) spinel chemical space

Key Points

• The study aims to identify undiscovered spinels using machine learning techniques applied to chemical space.
• Applied machine learning algorithms to analyze spinel crystal structures.
• Surveyed known materials within the spinel category.
• Explored potential undiscovered spinels based on structural data.
• Identified multiple potential spinels that are not yet documented.
• Revealed significant gaps in the known spinel chemical space.
• Projected new areas for further material discovery.

Abstract