Imaging Phase Segregation in Nanoscale Li x CoO 2 Single Particles.
Elliot J FullerDavid S AshbyCelia PolopElena SalagreBhuvsmita BhargavaYueming SongEnrique VascoJoshua D SugarPaul AlbertusTevfik Onur MenteşAndrea LocatelliPilar SegoviaMiguel Ángel Gonzalez-BarrioArantzazu MascaraqueEnrique G MichelA Alec TalinPublished in: ACS nano (2022)
Li x CoO 2 (LCO) is a common battery cathode material that has recently emerged as a promising material for other applications including electrocatalysis and as electrochemical random access memory (ECRAM). During charge-discharge cycling LCO exhibits phase transformations that are significantly complicated by electron correlation. While the bulk phase diagram for an ensemble of battery particles has been studied extensively, it remains unclear how these phases scale to nanometer dimensions and the effects of strain and diffusional anisotropy at the single-particle scale. Understanding these effects is critical to modeling battery performance and for predicting the scalability and performance of electrocatalysts and ECRAM. Here we investigate isolated, epitaxial LiCoO 2 islands grown by pulsed laser deposition. After electrochemical cycling of the islands, conductive atomic force microscopy (c-AFM) is used to image the spatial distribution of conductive and insulating phases. Above 20 nm island thicknesses, we observe a kinetically arrested state in which the phase boundary is perpendicular to the Li-planes; we propose a model and present image analysis results that show smaller LCO islands have a higher conductive fraction than larger area islands, and the overall conductive fraction is consistent with the lithiation state. Thinner islands (14 nm), with a larger surface to volume ratio, are found to exhibit a striping pattern, which suggests surface energy can dominate below a critical dimension. When increasing force is applied through the AFM tip to strain the LCO islands, significant shifts in current flow are observed, and underlying mechanisms for this behavior are discussed. The c-AFM images are compared with photoemission electron microscopy images, which are used to acquire statistics across hundreds of particles. The results indicate that strain and morphology become more critical to electrochemical performance as particles approach nanometer dimensions.
Keyphrases
- atomic force microscopy
- high speed
- single molecule
- reduced graphene oxide
- gold nanoparticles
- solid state
- deep learning
- ion batteries
- electron microscopy
- convolutional neural network
- high resolution
- photodynamic therapy
- ionic liquid
- molecularly imprinted
- label free
- machine learning
- multidrug resistant
- tissue engineering
- working memory
- light emitting