Evidence map›Paper›PMID 42498262›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2026

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

Milad Masrouri, Federica Buccino, Laura Maria Vergani, Zhao Qin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Milad MasrouriDepartment of Civil and Environmental Engineering, Syracuse University, Syracuse, New York, USA.
Federica BuccinoDepartment of Mechanical Engineering (DMEC), Politecnico di Milano, Milan, Italy.
Laura Maria VerganiDepartment of Mechanical Engineering (DMEC), Politecnico di Milano, Milan, Italy.
Zhao QinDepartment of Civil and Environmental Engineering, Syracuse University, Syracuse, New York, USA.

Funding

European Union Horizon Europe research and innovation programme under the Marie Skłodowska-Curie 101120290National Science Foundation CAREER #2145392
6 · The paper itself

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,

Indexed as

generative AIhierarchical porous materialslacunar networkmicromechanicsstiffness‐density scalingtrabecular bone

Identifiers

PMID42498262
PMCPMC13569018

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.