Aiming to bypass both the cost of PES exploration and the intuition required for template-based CRN generation, we recently developed the first method to construct and analyze electrochemical CRNs, which we used to study the formation of the solid electrolyte interphase (SEI) in lithium-ion batteries. After generating graph-based CRNs containing thousands of species and millions of reactions, we used shortest-path algorithms to identify optimal pathways to two key SEI products, lithium ethylene dicarbonate (LEDC) and lithium ethylene monocarbonate (LEMC). With this approach, we recovered known and proposed reaction mechanisms and predicted pathways that had not been previously reported.