Understanding disorder in oxide-based electrode materials for rechargeable batteries

Abstract

Most rechargeable ion batteries employ transition metal oxides or phosphates as the positive electrode. To facilitate facile migration of the active ions (e.g. Li-or Na-ions), which to some extent governs the battery functionality, the electrodes are typically composed of crystalline materials, wherein the ions are intercalated via well-defined migration pathways. However, the electrode materials are rarely perfectly crystalline and will inherently contain some disorder, which may originate from the material preparation process or be induced by the ion-intercalation process. In some electrode materials the electrochemical performance is damaged by disorder, whereas in other cases good performance is retained even after severe order-disorder transitions. This agrees with the emergence of several ab origine disordered or amorphous oxide-based electrodes with promising electrochemical performance. The term disorder is spanning a wide variety of deviations from an ideal crystal periodicity, from classical defects such as point defects, vacancies, stacking faults etc., to the amorphous state. Disorder, beyond classical defects, in battery electrodes has previously been largely overlooked, and we know little about the nature of the disorder and how it affects the battery performance. Developments in methods for characterisation of local atomic structures now allow us to gain detailed structural knowledge on the disordered part of the electrodes and studies within this field are emerging. This perspective provides a summary of the state-of-the-art within this field and the tendencies we are beginning to see outlined. These will be illustrated through selected examples. Finally, we discuss the key research questions within the field of disorder in electrode materials and the perspectives of answering these.

An Easy‐to‐Use Custom‐Built Cell for Neutron Powder Diffraction Studies of Rechargeable Batteries

“…Using sequential Rietveld refinement, cell parameters and Na‐occupancies for NaFM could be extracted, see Figure 7. Interestingly, for this material, the material undergoes a reversible order‐disorder transition, where almost all Bragg reflections disappear near the end of charge, but reappear during the subsequent discharge [41] . Structural details from this part of the experiment can naturally not be elucidated from the NPD data as this will require use of a complementary technique.…”

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

“…10), a collaborative work between SNEM and EXELFS should expand the flexibility and richness in collecting spatially-resolved local order information in materials. Considering the richness of information SNEM provides, especially in augmentation with other spatially-resolved methods, the growing automation and autonomation efforts of in situ PDF experimentation [62,63,64], including in electron microscopes [56], we find SNEM as a strong candidate for taking the lead in data-driven exploration of local order in materials in advanced metallurgy, energy materials [54,55], and bio-mineralization [56]. In parallel, it will also allow us to ask new questions on more classical materials that are yet to be answered and relate to the local order and its evolution in time and space.…”

“…Visualizing and understanding the chemistry-structure-process relations have immediate implication on understanding formation of shear-bands in metallic glasses. The link between chemistry and structural order is an important tier to the ongoing studies in metallic glasses [34,35,36,37,38], but also in other fields, such as structure evolution in batteries [54,55], and biomineralization [56].…”

nmfMapping: a cloud-based web application for non-negative matrix factorization of powder diffraction and pair distribution function datasets

“…In this example we consider data from an experiment characterizing nanostructured and disordered cathode battery structures via PDF analysis of operando experiments. Such experiments benefit greatly from use of an NMF-type analysis because of the high complexity of the battery electrodes, with a large number of unknown chemical components under dynamic conditions, and the large numbers of datasets (Christensen & Ravnsbaek, 2021).…”