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Lithium metal has been considered an ideal anode for high-energy rechargeable Li batteries, although its nucleation and growth process remains mysterious, especially at the nanoscale. Here, cryogenic transmission electron microscopy was used to reveal the evolving nanostructure of Li metal deposits at various transient states in the nucleation and growth process, in which a disorder-order phase transition was observed as a function of current density and deposition time. The atomic interaction over wide spatial and temporal scales was depicted by reactive molecular dynamics simulations to assist in understanding the kinetics. Compared to crystalline Li, glassy Li outperforms in electrochemical reversibility, and it has a desired structure for high-energy rechargeable Li batteries. Our findings correlate the crystallinity of the nuclei with the subsequent growth of the nanostructure and morphology, and provide strategies to control and shape the mesostructure of Li metal to achieve high performance in rechargeable Li batteries.

The elastic contact between two computer generated isotropic rough surfaces is studied. First the surface topography parameters including the asperity density, mean summit radius, and standard deviation of asperity heights of the equivalent rough surface are determined using an 8-nearest neighbor summit identification scheme. Second, many cross sections of the equivalent rough surface are traced and their individual topography parameters are determined from their corresponding spectral moments. The topography parameters are also obtained from the average spectral moments of all cross sections. The asperity density is found to be the main difference between the summit identification scheme and the spectral moments method. The contact parameters such as the number of contacting asperities, real area of contact, and contact load for any given separation between the equivalent rough surface and a rigid flat are calculated by summing the contributions of all the contacting asperities using the summit identification model. These contact parameters are also obtained with the Greenwood-Williamson (GW) model using the topography parameters from each individual cross section and from the average spectral moments of all cross sections. Three different surfaces and three different sampling intervals were used to study how the method to determine topography parameters affects the resulting contact parameters. The contact parameters are found to vary significantly based on the method used to determine the topography parameters, and as a function of the autocorrelation length of the surface, as well as the sampling interval. Using a summit identification model or the GW model based on topography parameters obtained from a summit identification scheme is perhaps the most reliable approach.

In the electrode/electrolyte interface of a typical lithium-ion battery, a solid electrolyte interphase layer is formed as a result of electrolyte decomposition during the initial charge/discharge cycles. Electron leakage from the anode to the electrolyte reduces the Li+-ion and makes it more reactive, resulting in decomposition of the organic electrolyte. To study the Li-electrolyte solvation, solvent exchange, and subsequent solvent decomposition reactions at the anode/electrolyte interface, we have extended the existing ReaxFF reactive force field parameter sets to organic electrolyte species, such as ethylene carbonate, ethyl methyl carbonate, vinylene carbonate, and LiPF6 salt. Density Functional Theory (DFT) data describing Li-associated initiation reactions for the organic electrolytes and binding energies of Li-electrolyte solvation structures were generated and added to the existing ReaxFF training data, and subsequently, we trained the ReaxFF parameters with the aim of finding the optimal reproduction of the DFT data. In order to discern the characteristics of the Li neutral and cation, we have introduced a second Li parameter set to describe the Li+-ion. ReaxFF is trained for Li-neutral and Li+-cation to have similar solvation energies, but unlike the neutral Li, Li+ will not induce reactivity in the organic electrolyte. Solvent decomposition reactions are presumed to happen once Li+-ions are reduced to Li-atoms, which can be simulated using a Monte Carlo type atom modification within ReaxFF. This newly developed force field is capable of distinguishing between a Li-atom and a Li+-ion properly. Moreover, it is found that the solvent decomposition reaction barrier is a function of the number of ethylene carbonate molecules solvating the Li-atom.

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