Cell Design and Materials: Alternative Chemistries

Zinc-ion Batteries Research in 2025 continues to push zinc-ion batteries ZIBs toward greater durability, manufacturability, and commercial relevance. Basic Chemistry

Academic Work

Zinc-ion batteries are being developed using both near neutral and basic electrolytes. These batteries have a pathway to $50/kWh cell cost level due to the low cost of materials and existing supply chain for the primary battery market. With the theoretical max specific capacity of 308 mAh/g, a lot of up and coming companies and research is being performed to advance zinc-ion batteries to solve manganese dioxide dissolution and improve rechargeability.

Cathode research remains the dominant focus, especially around Mn-based materials to improve cycle life, stability and scalability. This includes:

Novel cathode materials & hybrid designs (CuO2, iPOPs, Polyaniline)

Thinner and more scalable cathodes

Carbon coating processes and structural tuning (β-MnO2, α-MnO2)

Doping strategies (Ni, Bi, K, Fe, Zn) to improve stability and conductivity

Adhesion improvements, titanium dioxide surface interfaces, and dissolution shielding approaches Carboxyl-CNTs, PNMnO2)

Hydrothermal synthesis(high valence, polymorphs) and ion-exchange processes adapted for manufacturability

Vanadium sulfide fundamental studies for alternative chemistries

Dry-electrode and other manufacturing capabilities Electrolyte development continues to minimize dendrites and extend lifetime

Electrolyte additives for suppression of side reactions (Al2SO4)3, Mannitol)

Hydrogel electrolytes (Polyanionic, Salt-Concentrated) to improve safety and Zn interface stability

Engineering of cathode–electrolyte interfaces to reduce degradation Supporting improvements indicate the field is transitioning beyond core chemistry:

Current collector enhancements

Separator advancements for ion selectivity and safety Development of characterization and data-driven approaches:

Characterization of failure modes (in situ, modeling)

Mechanistic fundamentals to correlate structure and performance

Incorporating machine learning for material optimization

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