Highly Potent and Low-Volume Concentration Additives for Durable Aqueous Zinc Batteries: Machine Learning-Enabled Performance Rationalization.

Abstract

The essential virtues of aqueous zinc battery chemistry stem from the energy-dense zinc metal anode and mild aqueous electrolytes. Yet, their incompatibility - as exposed by zinc's corrosion and associated dendrite problem - poses a challenge to achieving improved cycle life under practically relevant parameters. While electrolyte additives are a scalable strategy, additives that can function at low volume concentrations remain elusive. Here, through screening alkanol and alkanediol chemistries, 1,2-butanediol and pentanediol are unveiled as highly potent additives, which operate at a practical 1 volume% concentration owing to their ability to furnish dynamic solid-electrolyte interphase through pronounced interfacial filming. This unique mechanistic action renders effective corrosion and dendrite mitigation, resulting in up to five to twenty-fold zinc cyclability enhancement with a high Coulombic efficiency (up to 99.9%) and improved full-cell performance under demanding conditions, including at elevated temperatures. A machine learning-based analysis is presented to rationalize the additive performance relative to critical physicochemical descriptors, which can pave the way for a rational approach to efficient additive discoveries.