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This work demonstrates enhanced lithium storage in silicon anodes through self-adaptive nanoporous structures, suggesting innovative material optimization approaches.
Realizing next‐generation, high‐energy‐density lithium storage relies critically on overcoming the fundamental structural instabilities of high‐capacity silicon anodes. While nanoscale silicon (Si NPs) successfully circumvents severe pulverization, practical application remains bottlenecked by rapid capacity fading. Historically, materials design has relied on a restrictive paradigm: forcefully suppressing spontaneous Si NP agglomeration and inward solid electrolyte interphase (SEI) permeation, which otherwise yields an electrochemically inert SEI/Si composite (“dead Si”). Herein, a fundamental paradigm shift is introduced: harnessing—rather than conventionally suppressing—nanoscale agglomeration to trigger a beneficial structural self‐adaptive activation. To realize this, a highly scalable, synergistic Si/graphite/amorphous carbon (nSi/Gr/C) architecture is constructed. Initially, a robust dual‐carbon framework mechanically isolates the internal structure from severe SEI infiltration while securing continuous, redundant electron‐transfer pathways. Shielded within this stable conductive network, primary Si NPs undergo a modulated agglomeration. Driven by the drastic volume contraction during subsequent delithiation, these domains autonomously evolve into a highly active, metastable nanoporous “silicon sponge” characterized by ultra‐small ligaments (<10 nm). This dynamically generated sub‐10 nm architecture intrinsically buffers massive volume fluctuations and significantly accelerates lithium‐ion and electron mass transfer kinetics, yielding exceptionally stable lithium storage and remarkable full‐cell commercial viability. By converting a historically deleterious degradation mechanism into a driving force for nanoscale structural optimization, this work establishes a highly viable pathway to unlock the full potential of next‐generation Si‐based anodes.
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Zhang et al. (2026) studied this question.
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