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Nucleation and Growth of Lithium Peroxide in the Li/O_{2} Cell

_{2}Cell

_{2}O

_{2}discharge product is an electronic insulator, but SEM images of discharged cathodes show particles of Li

_{2}O

_{2}much larger than what electron conduction and tunneling would allow. In addition, the shape of the discharge curves does not match the expected exponential resistance rise of a cell limited by electron tunneling.

In order to bridge Li_{2}O_{2} properties with experimental observations, we developed a model in which Li_{2}O_{2} forms as discrete particles on the cathode surface by using a combination of Kolmogorov’s statistical phase transformation theory and the atomistic nucleation theory. Nucleation rate was modeled according to a two-step process involving formation of a LiO_{2} intermediate. Despite its relative simplicity, the proposed model provides a near-quantitative description of empirically observed discharge curves (Figure 1). We find that the sudden potential drop at the end of discharge is caused by the reduction in active surface area as Li_{2}O_{2} covers the cathode surface. Thus, the extra overpotential gained during discharge is the kinetic overpotential of the ORR rather than an ohmic overpotential through the Li_{2}O_{2} bulk.

This model can be used as a guide for cathode and electrolyte design, by maximizing the amount of Li_{2}O_{2} that can be collected for a given amount of electrochemically active surface area. One strategy is to promote the growth of larger Li_{2}O_{2} particles. For cathodes, this means reducing the rate of nucleation by having a higher nucleation energy barrier or a lower concentration of active sites. For electrolytes, this means solvating the LiO_{2} intermediate to promote the superoxide disproportionation pathway. In principle, the general form of this model is applicable to any electrochemical cell that produces a solid passivation layer.

Figure 1: (a) Empirically observed discharge curves (symbols), compared with fit of the nucleation and growth model (lines). (b) Analysis of model parameters shows that they are independent of operating conditions.