Counterintuitive Isomerization of TFSI- and TFSI--Cation Correlated Isomerization: Insights into the Low Melting Points of TFSI--Based Ionic Liquids.

Abstract

Ionic liquids (ILs), particularly bis(trifluoromethane)sulfonamide (TFSI-)-based ILs, have attracted substantial attention in electrochemical energy storage, ionic gating for superconductivity, and iontronic sensing. However, underestimating TFSI- isomerization and overlooking TFSI--cation correlation make the origin of their most characteristic property, low melting points (Tm), ambiguous. Traditional static electronic structure calculations assume that C2-symmetric trans enantiomers of TFSI- easily isomerize into cis enantiomers through four symmetrically equivalent pathways over a barrier of 7.1 kJ mol-1. Herein, ab initio molecular dynamics (AIMD) simulations combined with metadynamics reveal that the unusual oscillation of the central nitrogen atom promotes TFSI- to undergo complex isomerization. Specifically, asymmetric trans-to-cis diastereomers of TFSI- experience restricted interconversion (20-52 kJ mol-1) through four distinct asymmetric pathways. The adaptive oscillation and hybridization of chiral nitrogen boost nN → σ*S-C negative hyperconjugation for stabilizing conformational structures and enlarging energy barriers. The orientational distortion of oxygen atoms' lone pairs enhances conjugation but breaks the C2-symmetry. The coexistence of both helicity and chiral nitrogen breaks the enantiomeric relationship. Furthermore, Raman characterization and AIMD simulations confirm the positive correlation between the relative stability of cis-TFSI- and its countercation's polarity. TFSI- and countercations make a mutual conformational selection instead of free isomerization. Surprisingly, Tm increases with the cation-dependent conformational rigidity of TFSI-, offering new fundamental insights into the low Tm of ILs. This descriptor encoding the dependence of thermal property on cation-anion correlated isomerization provides material design guidelines and property prediction capability.