Notice:

Users can explore three curated databases by selecting the cards above. Each database provides access to comprehensive IL-related data.

• Cation Database: Comprises quantum‐chemical properties for 3,774 distinct cation species.
• Anion Database: Comprises quantum‐chemical properties for 2,220 distinct anion species.
• Generated IL Database: Contains machine‐learning–predicted conductivity, melting point, and electrochemical window for 100,000 in silico–generated ionic liquids.
• Experimental IL Database: Contains experimentally measured or quantum‐chemistry–computed conductivity, melting point, and electrochemical window for approximately 3,600 real ionic liquids.

References:

1. Wang, J.; Wang, Y. Strategies to Improve the Quantum Computation Accuracy for Electrochemical Windows of Ionic Liquids. J. Phys. Chem. B 2024, 128, 1943-1952.
2. Li, K.; Wang, J.; Song, Y.; Wang, Y. Machine learning-guided discovery of ionic polymer electrolytes for lithium metal batteries. Nat. Commun. 2023, 14, 2789.