Data‐Driven Host Microstructure Design Toward Efficient and Durable Room‐Temperature Sodium–Sulfur Batteries

ABSTRACT Porous carbon materials are critical hosts for chalcogen‐ and halogen‐based conversion‐type cathodes, as they govern the activity and durability of electrochemical reactions. Understanding how their microstructures regulate electrolyte‐electrode interactions remains challenging given multiple coupling factors and dynamic changes during electrochemical cycling. Herein, machine learning was first used to screen three pore structure parameter windows relevant to electrochemical features from a large experimental dataset (23 carbon hosts and 1055 specific‐capacity data points). Based on these screened windows, three representative carbon hosts, namely micropore‐rich carbon, balanced carbon, and meso/macropore‐rich carbon, were synthesized as model systems. We reveal that pore structure governs sulfur species evolution, thereby dictating the competition between polysulfide‐mediated reactions and solvent self‐decomposition. The resulting spatial‐compositional differences of the cathode–electrolyte interphase (CEI) were found to profoundly impact energy efficiency, reversibility, and rate performance. The balanced carbon cathode with optimized inorganic‐organic distribution delivers an initial capacity of 1249.4 mAh g −1 and retains a capacity of 784.8 mAh g −1 after 500 cycles. This work not only proposes a data‐driven strategy for identifying CEI‐relevant pore structure windows, but also provides mechanistic insight into how physical metrics of porous carbon modulate multi‐step complex reactions and ultimately influence electrochemical performance.