Single-crystal neutron diffraction on γ-LiAlO₂: structure determination and estimation of lithium diffusion pathway

Abstract

γ-Lithium aluminum oxide is a paradigmatic example of an ultraslow lithium ion conductor. This characteristic plays a crucial role in its proposed and actual applications. Herein, we report on the outcome of singlecrystal neutron diffraction studies at ambient and high temperature. Careful evaluation confirms the commonly assumed room-temperature structure as derived by powder neutron diffraction in 1965. At 1043 K, a split of the lithium position hints at the onset of intrinsic diffusion. Analysis of the negative scattering-length density using the maximum-entropy method (MEM) indicates a preference for a strongly curved diffusion pathway traversing octahedral voids between adjacent lithium sites. These results help to understand ultraslow lithium diffusion in well-ordered ionic solids on the microscopic scale and, ultimately, to establish structure-property relationships.

Nanostructured Ceramics: Ionic Transport and Electrochemical Activity

“…[87] for recent measurements on a powder sample. The value of 0.7 eV agrees with that derived from neutron diffraction data that indicated a curved pathway connecting two adjacent Li sites in LiAlO 2 [88]. Long-range Li ion transport, on the other hand, has to be described with a higher activation energy [86,89].…”

Slow Lithium Transport in Metal Oxides on the Nanoscale

“…In this study, an activation energy of 1.1-1.2 eV between 373 and 673 K was found from the first two methods in excellent agreement (see Figure 7). From neutron diffraction data, both on the powder and independently on a single crystal [84], a strongly curved diffusion path between adjacent Li positions was deduced. A migration barrier of 0.72 eV was identified and attributed to a vacancy mechanism [78].…”

The inverse perovskite BaLiF3: single-crystal neutron diffraction and analyses of potential ion pathways

“…the neutron analogue of the electron density probed with X-ray diffraction) that we reconstructed using MEM. These methods yield the maximum variance of calculated structure factors within standard deviations of observed structure factors, in this way producing density maps, which contain less artefacts and are less prone to misinterpretation (Wiedemann et al, 2016;Wiedemann, Islam et al, 2017). These maps (see Fig.…”