AI‐Revealed Transition From Density‐ to Connectivity‐Controlled Mechanics in Hierarchical Porous Materials

ABSTRACT Hierarchical porous architectures enable lightweight, damage‐tolerant materials, yet their performance depends on how mechanical properties scale with density. Classical cellular‐solid theory captures the density‐controlled scaling law, but it remains unclear whether microscale defect topology drives its breakdown. Here, in situ synchrotron tomography, diffusion‐based generative modeling, and micromechanical simulations are combined to reveal an AI‐enabled, scale‐dependent transition in stiffness‐density scaling in trabecular bone with hierarchical porous structures. At the millimeter scale, the effective Young's modulus follows cellular‐solid behavior, , where is defined as bone volume divided by total volume. At the lacunar (microscale) level, simulations on thousands of lacunar microstructures, augmented by statistically faithful AI‐generated ensembles, exhibit a markedly steeper dependence, . This hypersensitivity arises from long‐range interactions between void‐induced stress fields that merge into system‐spanning weak corridors, shifting load transfer from porosity control to matrix connectivity and promoting guided crack initiation and propagation. By preserving higher‐order morphology while expanding microstructural sampling, AI generation enables ensemble‐level quantification of this connectivity‐controlled regime under data‐limited imaging. These results establish a mechanism by which microscale defect topology can dominate stiffness in hierarchical porous materials.