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Self-Regulating Sodium-Ion Battery Materials: From Phase Reconstruction to Functional Activation
Hong Gao1, Dingyi Zhang1, Chao Wang1
1Joint International Laboratory on Environmental and Energy Frontier Materials, School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China.
This review presents a self-regulation framework for durable sodium-ion batteries. It unifies insights on material, interface, and electrolyte evolution for reliable electrochemical transport and long-term performance.
Area of Science:
- Materials Science
- Electrochemistry
- Energy Storage
Background:
- Sodium-ion batteries (SIBs) are nearing practical use, but long-term durability remains a challenge.
- Durability depends on complex interactions within the battery, not just static material properties.
- Existing mechanistic insights into these interactions are fragmented.
Purpose of the Study:
- To introduce a unified self-regulation framework for understanding and improving SIB durability.
- To consolidate dispersed mechanistic insights into a cohesive understanding of battery operation.
- To provide design rules for developing programmable and durable SIBs.
Main Methods:
- Review and synthesis of existing research on SIBs.
- Organization of evidence along three key axes: lattice evolution, interphase chemistry, and electrolyte-materials coupling.
- Analysis of layered oxides, self-buffering anodes, and electrolyte design.
Main Results:
- A self-regulation framework is proposed where structural and chemical changes are confined, reversible, and support electrochemical transport.
- Specific mechanisms are detailed for layered oxides (e.g., controlled slab glide, Na-vacancy ordering) and interphases (e.g., inorganic-rich, self-renewing architectures).
- Electrolyte properties are shown to actively steer interphase reconstruction and near-surface transport.
Conclusions:
- The framework highlights how lattice, interface, and electrolyte work together to ensure SIB durability.
- Design rules are distilled, linking operando signatures to material composition and processing.
- Opportunities for model-guided optimization and data-driven discovery in SIB development are identified.
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