Conductivity spectroscopy and 7Li spin-locking NMR relaxometry reveal enhanced ion dynamics in nanocrystalline Li2O2 prepared by high-energy ball milling.

Ceramics with nm-sized dimensions are widely used in various applications such as batteries, fuel cells or sensors. Their oftentimes superior electrochemical properties as well as their capabilities to easily conduct ions are, however, not completely understood. Depending on the method chosen to prepare the materials, nanostructured ceramics may be equipped with a large area fraction of interfacial regions that exhibit structural disorder. Elucidating the relationship between microscopic disorder and ion dynamics as well as electrochemical performance is necessary to develop new functionalized materials. Here, we highlight some of the very recent studies on ion transport and electrochemical properties of nanostructured ceramics. Emphasis is put on TiO

Silicon is one of the most promising anode materials for lithium-based rechargeable batteries. Provided the volume changes during Li uptake can be brought under control, Li ion diffusivity is expected to crucially determine the performance of such next-generation energy storage systems. Therefore, studying diffusion properties in e.g. amorphous Li–Si underpins applied research that is being directed toward the development of powerful storage devices. So far, only little information is available on Li+ self-diffusion in amorphous Si. Here, we used 7Li NMR spectroscopy to precisely quantify microscopic activation energies and Li jump rates in amorphous Li–Si which is primarily formed if monocrystalline Si is lithiated electrochemically. Surprisingly, our results reveal relatively fast Li ion diffusivity with low activation energies for localized Li+ motions being in agreement with results from theory. The average activation energy for long-range ion transport is as high as ca. 0.65 eV; jump rates turn out to be in the order of 2.5 × 105 s–1 at 246 K. Our results point to complex dynamics that is most likely governed by nonexponential motional correlation functions originating from a distribution of activation energies. The data obtained might help optimizing Li-based silicon batteries whose performance critically depend on fast Li ion transport.