Isothermal Microcalorimetry: Insight into the Impact of Crystallite Size and Agglomeration on the Lithiation of Magnetite, Fe3O4.
Matthew M HuieDavid C BockAndrea M BruckKillian R TallmanLisa M HouselLei WangJuergen ThiemeKenneth J TakeuchiEsther S TakeuchiAmy C MarshilokPublished in: ACS applied materials & interfaces (2019)
Magnetite, Fe3O4, holds significant interest as a Li-ion anode material because of its high theoretical capacity (926 mAh/g) associated with multiple electron transfers per cation center. Notably, both crystallite size and agglomeration influence ion transport. This report probes the effects of crystallite size (12 and 29 nm) and agglomeration on the reactions involved with the formation of the surface electrolyte interphase on Fe3O4. Isothermal microcalorimetry (IMC) was used to determine the parasitic heat evolved during lithiation by considering the total heat measured, cell polarization, and entropic contributions. Interestingly, the 29 nm Fe3O4-based electrodes produced more parasitic heat than the 12 nm samples (1346 vs 1155 J/g). This observation was explored using scanning electron microscopy (SEM) and X-ray fluorescence (XRF) mapping in conjunction with spatially resolved X-ray absorption spectroscopy (XAS). SEM imaging of the electrodes revealed more agglomerates for the 12 nm material, affirmed by XRF maps. Further, XAS results suggest that Li+ transport is more restricted for the smaller crystallite size (12 nm) material, attributed to its greater degree of agglomeration. These results rationalize the IMC data, where agglomerates of the 12 nm material limit solid electrolyte interphase formation and parasitic heat generation during lithiation of Fe3O4.
Keyphrases
- electron microscopy
- high resolution
- photodynamic therapy
- ion batteries
- solid state
- heat stress
- ionic liquid
- single cell
- single molecule
- light emitting
- fluorescence imaging
- small molecule
- reduced graphene oxide
- magnetic resonance imaging
- mesenchymal stem cells
- computed tomography
- nucleic acid
- electronic health record
- machine learning
- mass spectrometry
- magnetic resonance
- quantum dots
- big data
- carbon nanotubes
- gold nanoparticles