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S2− −416.8 kJ · mol−1 4 S2− −432.2 kJ · mol−1 6 S2− −441.9 kJ · mol−1 8 S8(ds) 19.0 kJ · mol−1 Reactions, forward rate constants 3.0·10−4 mol·m−2 ·s−1 4.0·1014 mol·m−2 ·s−1 4.0·1014 mol·m−2 ·s−1 4.0·1014 mol·m−2 ·s−1 4.0·1011 mol·m−2 ·s−1 4.0·1014 mol·m−2 ·s−1 3.2·1012 mol·m−2 ·s−1 2.12 · 10−7 mol · l−1 7.16 · 10−4 mol · l−1 2.92 · 10−1 mol · l−1 9.38 mol · l−1 S8(s) S8(ds) 1/2 S + e− 1/2 S2− 8(ds) 3/2 S2− + e− 2 S2− 8 86 S2− + e− 3/2 S2− 64 1/2 S2− + e− S2− 42 1/2 S2− + e− S2− 2 2Li++S2−Li2S(s) Molar Gibbs free energy g0 of Li2S: −429.7 kJ · mol−1 Density of the liquid electrolyte ρelyte including dissolved species: 1535 kg · m−3 Diffusion constant Dn (for all dissolved species): 1.0 · 10−11 m2 · s−1 5.4 Multi-step model – validation attempts Having determined all parameters of the model, an attempt is made to perform an ini- tial validation. This measure is not to be confused with a regression model validation used e.g. for equivalent circuit models. A rigorous stochastic validation is not possible in this case for two reasons: First, practically, the data base available for validation is not sufficient to achieve a reasonable significance: Only experimental data not previ- ously used for the parametrization may be employed for the validation. Also, neither the very best (or worst) performing cells, nor the first few cycles of any cell are used for the validation, since they are believed to be less representative. Second, fundamen- tally, the need to evaluate both the correctness of the assumed reaction mechanism and the set of parameters at the same time, poses fundamental limits to a mathematically sound validation. Instead, simulation results are visually compared to corresponding experimental data and checked for plausibility, taking into account the considerations on model accuracy outlined in section 4.3.3. 116PDF Image | Lithium-Sulfur Battery: Design, Characterization, and Physically-based Modeling
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