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Record W4417064964 · doi:10.1016/j.mattod.2025.12.001

Self-confining-pressure structures double the compressive strength of metamaterials by applying lessons from nature and architecture

2025· article· en· W4417064964 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials Today · 2025
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMetamaterialCompressive strengthArchitectureMechanical strength

Abstract

fetched live from OpenAlex

Metallic materials with high strength-to-weight ratios, or specific strengths, have been sought after for centuries, from aircraft and automobiles to electronic devices and biomedical implants. Inspired by tube-in-tube structures in nature and architecture, we fabricate metallic metamaterials with self-confining-pressure structures (SCPS), achieving exceptional compressive yield strength up to 1272 MPa (a specific strength of 379.7 kN∙m/kg) in AlSi7Mg-Ti6Al4V (Al-Ti) metamaterials. Such metamaterials—exceeding that of its constituents, while maintaining an asymmetrical tensile yield strength up to 696 MPa. This remarkable strength amplification originates from the induced triaxial stress state within the SCPS architecture and confining-pressure-induced dislocation multiplications. We propose a mechanical model that quantitatively captures the strengthening effect of SCPS. The design strategy of SCPS significantly enhances the compressive strength ceilings of existing structural materials without sacrificing their tensile strength and ductility, enabling anisotropic mechanical performance for demanding aerospace, automotive, and a wide range of engineering applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.221
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it