Giant Redox Entropy in the Intercalation Chemistry of MOF Nanocrystals with Confined Pores

06 December 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Redox intercalation involves coupled ion-electron motion within host materials, finding extensive application in energy storage, electrocatalysis, sensing, and optoelectronics. While metal-organic frameworks (MOFs) comprise a diverse class of porous electrochemical materials, the intercalation redox chemistry of MOFs remains poorly understood due to the presence of redox sites at the exterior of MOF particles and in the internal pores. Here, we report that Fe(1,2,3-triazolate)2 possesses an intercalation-based redox process shifted ca. 1.2 V from redox at the particle surface. Such distinct chemical environments do not appear in idealized MOF crystal structures but become magnified in MOF nanoparticles. Quartz crystal microbalance and time-of-flight secondary ion mass spectrometry combined with electrochemical studies identify the existence of a distinct and highly reversible Fe2+/Fe3+ redox event occurring within the MOF interior. Systematic manipulation of experimental parameters (e.g., film thickness, electrolyte species, solvent, and reaction temperature) reveals that this feature arises from the nanoconfined (4.54 Å) pores gating the entry of charge-compensating anions. Due to the requirement for full desolvation and reorganization of electrolyte outside the MOF particle, the anion-coupled oxidation of internal Fe2+ sites involves a giant redox entropy change (i.e., 164 J K-1 mol-1). Taken together, this study establishes a microscopic picture of ion intercalation redox chemistry in nanoconfined environments and demonstrates the synthetic possibility of tuning electrode potentials by over a volt, with profound implications for energy capture and storage technologies.


metal-organic frameworks
energy storage

Supplementary materials

Supporting Information
Additional synthetic and experimental details and characterization data.


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