The DEZAIN project is targeted at identification of electrolyte additives for rechargeable aqueous Zn-air battery by coupling artificial intelligence with high-throughput experimental testing method. Zn-air battery is promising technology for large-scale electricity grids due to high safety, environmental regulation compatibility and low cost.
The main drawback is degradation of the Zn electrode during cycling. The electrolyte additives directly address the electrode-electrolyte interface and influence the reactivity of Zn. A main objective is to identify effective electrolyte additives or their mixture that prevent dendrite formation, and contribute to uniform redeposition of Zn with less hydrogen evolution. The obtained results will be used as the training set for machine learning for prediction of new electrolyte compositions.
The advances in robotics and machine learning (ML) will allow to identify new chemicals that efficiently control the Zn interface. The designing of aqueous electrolyte for Zn-based aqueous batteries will be achieved by means of interactive learning and synergistic knowledge exchange between Helmholtz-Zentrum Hereon (Germany) and Technion (Israel).
Department of Electrochemistry and Big Data
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