Li Plating on Carbon Electrode Surface Probed by Low-Field Dynamic Nuclear Polarization 7Li NMR

Lithium deposition on graphite electrode not only reduces fast-charging capability of lithium ion batteries but also causes safety trouble. Here, a low-field 7Li dynamic nuclear polarization (DNP) is used to probe Li plating on the surfaces of three types of carbon electrodes: hard carbon, soft carbon and graphite. Owing to the strong Fermi contact interaction between 7Li and conduction electrons, the 7Li nuclear-magnetic-resonance (NMR) signal of Li metal deposited on electrode surface could be selectively enhanced by DNP. It is suggested that low-field 7Li DNP spectroscopy is a sensitive tool for investigating Li deposition on electrodes during charging/discharging processes.

Effects of Non-Stoichiometry on the Ground State of the Frustrated System Li0.8Ni0.6Sb0.4O2

The non-stoichiometric system Li0.8Ni0.6Sb0.4O2 is a Li-deficient derivative of the zigzag honeycomb antiferromagnet Li3Ni2SbO6. Structural and magnetic properties of Li0.8Ni0.6Sb0.4O2 were studied by means of X-ray diffraction, magnetic susceptibility, specific heat, and nuclear magnetic resonance measurements. Powder X-ray diffraction data shows the formation of a new phase, which is Sb-enriched and Li-deficient with respect to the structurally honeycomb-ordered Li3Ni2SbO6. This structural modification manifests in a drastic change of the magnetic properties in comparison to the stoichiometric partner. Bulk static (dc) magnetic susceptibility measurements show an overall antiferromagnetic interaction (Θ = −4 K) between Ni2+ spins (S = 1), while dynamic (ac) susceptibility reveals a transition into a spin glass state at a freezing temperature TSG ~ 8 K. These results were supported by the absence of the λ-anomaly in the specific heat Cp(T) down to 2 K. Moreover, combination of the bulk static susceptibility, heat capacity and 7Li NMR studies indicates a complicated temperature transformation of the magnetic system. We observe a development of a cluster spin glass, where the Ising-like Ni2+ magnetic moments demonstrate a 2D correlated slow short-range dynamics already at 12 K, whereas the formation of 3D short range static ordered clusters occurs far below the spin-glass freezing temperature at T ~ 4 K as it can be seen from the 7Li NMR spectrum.

Independent component analysis combined with Laplace inversion of spectrally resolved spin-alignment echo/T1 3D 7Li NMR of superionic Li10GeP2S12

The use of independent component analysis (ICA) for the analysis of two-dimensional (2D) spin-alignment echo--T1 7Li NMR correlation data with transient echo detection as a third dimension is demonstrated for the superionic conductor Li10GeP2S12 (LGPS). ICA was combined with Laplace inversion, or discrete inverse Laplace transform (ILT), to obtain spectrally resolved 2D correlation maps. Robust results were obtained with the spectra as well as the vectorized correlation maps as independent components. It was also shown that the order of ICA and ILT steps can be swapped. While performing the ILT step before ICA provided better contrast, a substantial data compression can be achieved if ICA is executed first. Thereby the overall computation time could be reduced by one to two orders of magnitude, since the number of computationally expensive ILT steps is limited to the number of retained independent components. For LGPS, it was demonstrated that physically meaningful independent components and mixing matrices are obtained, which could be correlated with previously investigated material properties yet provided a clearer, better separation of features in the data. LGPS from two different batches was investigated, which showed substantial differences in their spectral and relaxation behavior. While in both cases this could be attributed to ionic mobility, the presented analysis may also clear the way for a more in-depth theoretical analysis based on numerical simulations. The presented method appears to be particularly suitable for samples with at least partially resolved static quadrupolar spectra, such as alkali metal ions in superionic conductors. The good stability of the ICA analysis makes this a prospect algorithm for preprocessing of data for a subsequent automatized analysis using machine learning concepts.