Models of impurity trapping during rapid solidification

Probing the Ni(OH)2 Precursor for LiNiO2 at the Atomic Scale: Insights into the Origin of Structural Defect in a Layered Cathode Active Material

In lithium ion batteries (LIBs), the layered cathode materials of composition LiNi_{1- x - y} Co_x Mn_y O₂  are critical for achieving high energy densities. A high nickel content (>80%) provides an attractive balance between high energy density, long lifetime, and low cost. Consequently, Ni-rich layered oxides cathode active materials (CAMs) are in high demand, and the importance of LiNiO₂ (LNO) as limiting case, is hence paramount. However, achieving perfect stoichiometry is a challenge resulting in various structural issues, which successively impact physicochemical properties and result in the capacity fade of LIBs. To better understand defect formation in LNO, the role of the Ni(OH)₂  precursor morphology in the synthesis of LNO requires in-depth investigation. By employing aberration-corrected scanning transmission electron microscopy, electron energy loss spectroscopy, and precession electron diffraction, a direct observation of defects in the Ni(OH)₂  precursor preparedis reported and the ex situ structural evolution from the precursor to the end product is monitored. During synthesis, the layered Ni(OH)₂  structure transforms to partially lithiated (non-layered) NiO and finally to layered LNO. The results suggest that the defects observed in commercially relevant CAMs originate to a large extent from the precursors, hence care must be taken in tuning the co-precipitation parameters to synthesize defect-free Ni-rich layered oxides CAMs.

Oscillations in the nucleation preexponential

Oscillations in the preexponential of the nucleation rate are due to the discrete nature of small nuclei. An accurate elementary expression to describe such oscillations is derived in the limit of a high nucleation barrier. The result is applied to the standard Becker-Döring equation in two and three dimensions, and to the lowest-energy nucleation path in a cold lattice gas with Glauber and Metropolis dynamics (equivalent to an Ising model on a square lattice) where oscillation effects can be more pronounced.

Understanding the mechanisms of solid-water reactions through analysis of surface topography

The topography of a reactive surface contains information about the reactions that form or modify the surface and, therefore, it should be possible to characterize reactivity using topography parameters such as surface area, roughness, or fractal dimension. As a test of this idea, we consider a two-dimensional (2D) lattice model for crystal dissolution and examine a suite of topography parameters to determine which may be useful for predicting rates and mechanisms of dissolution. The model is based on the assumption that the reactivity of a surface site decreases with the number of nearest neighbors. We show that the steady-state surface topography in our model system is a function of, at most, two variables: the ratio of the rate of loss of sites with two neighbors versus three neighbors (d(2)/d(3)) and the ratio of the rate of loss of sites with one neighbor versus three neighbors (d(1)/d(3)). This means that relative rates can be determined from two parameters characterizing the topography of a surface provided that the two parameters are independent of one another. It also means that absolute rates cannot be determined from measurements of surface topography alone. To identify independent sets of topography parameters, we simulated surfaces from a broad range of d(1)/d(3) and d(2)/d(3) and computed a suite of common topography parameters for each surface. Our results indicate that the fractal dimension D and the average spacing between steps, E[s], can serve to uniquely determine d(1)/d(3) and d(2)/d(3) provided that sufficiently strong correlations exist between the steps. Sufficiently strong correlations exist in our model system when D>1.5 (which corresponds to D>2.5 for real 3D reactive surfaces). When steps are uncorrelated, surface topography becomes independent of step retreat rate and D is equal to 1.5. Under these conditions, measures of surface topography are not independent and any single topography parameter contains all of the available mechanistic information about the surface. Our results also indicate that root-mean-square roughness cannot be used to reliably characterize the surface topography of fractal surfaces because it is an inherently noisy parameter for such surfaces with the scale of the noise being independent of length scale.