Graph-Theory Algorithm for Prediction of Electrolyte Degradation Reactions in Lithium- and Sodium-Ion Batteries

The growing demand for sustainable energy storage devices requires the fabrication of novel materials for rechargeable metal-ion batteries. The stability of the materials incorporated in the electrochemical cells plays a crucial role in the specific capacity and cycling stability of energy storage devices. The processes that occur inside such systems are fairly complex; hence, the identification of unwanted side reactions affecting the electrochemical stability is not a trivial task. The present study combines cheminformatics and quantum chemistry approaches to create an algorithm that generates diverse viable side products of redox reactions that a given electrochemical system, e.g., different cathode or anode materials, electrolytes, solvents, etc., can undergo. Two case studies of electrolyte degradation are presented: namely, ethylene carbonate (EC) and diglyme (DG). The effect of the electrode surface is modeled by the dehydrogenation reactions of the electrolyte solvents. The predicted degradation products after reduction and oxidation are validated using previously reported experimental data. For EC, the predicted products are CO, CO₂, ethene, ethylene oxide, [CO₂]^•-, and [CO₂]^•+, while for DG alkoxy anions are mainly anticipated. The number of gaseous products formed upon DG degradation is significantly smaller than the number of gaseous species formed by EC fragmentation. The proposed algorithm opens new avenues for the rapid deduction of degradation products of novel electrolyte solvents for which no experimental data are available and can easily be adapted to predict the degradation of other materials.