When 10:30 AM - 11:30 AM Dec 14, 2018
Where 1571 G.G. Brown
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Multiscale Simulations of the Thin Passivation Layers --- for Aluminum Forming and Lithium-Ion Battery Durability


Yue Qi
Chemical Engineering and Materials Science, Michigan State University

Spontaneously formed passivation layers, as thin as nanometers, can kinetically hinder reactions and enable many important applications, such as stainless steel, aluminum boil kettle, and titanium ship in seawater. The more active lithium metal surface is also covered by a passivation layer (called solid electrolyte interphase, SEI) due to electrolyte reduction in a battery cell. Their formation, growth, diffusion, deformation intertwined with the underlining metal and the outside environment pose great challenges to solving chemical-mechanical and electrochemical-mechanical coupled problems. Several important examples and approaches will be discussed in this talk. 

Molecular dynamics with the reactive force field (ReaxFF) can simultaneously track the chemical, structural, and mechanical evolution of nanostructures during oxidation, lithiation, delithiation etc. As an example, we show how dynamic oxidation alters the tensile deformation of single crystal aluminum nanowires. Surprisingly, the oxidation enhances the aluminum nanowire ductility, and the oxide shell exhibits superplastic behavior assisted by reaction and diffusion. The interplay between the strain rate and oxidation rate is captured by a simple analytical model, which can be extended to macro-scale.

To capture the electrochemical reactions at a passivated interface, a new half-cell model is created and Density Functional Theory and tight binding were used to compute the energy landscape for the fundamental charge transfer reaction  at a complex Li/Li2CO3/liquid-EC-electrolyte interface. For the first time, it is clearly demonstrated that the charge transfer occurs underneath the perfect SEI. The desolvation energy barrier, the double layer structure, and the Li+ transport through the SEI under the applied electric potential were predicted. These predicted energetics is used to inform phase field models in order to capture the Li-dendrite growth process at meso-scale.

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