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Record W4399331612 · doi:10.1002/adfm.202405008

Nacreous Glass Composites with Superior Performance Engineered through Mechanical Vibration and Silanization

2024· article· en· W4399331612 on OpenAlexafffund
Ali Amini, Pouria Tirgar, Aram Bahmani, Maziar Jafari, Mohamed Siaj, François Barthelat, Allen J. Ehrlicher

Bibliographic record

VenueAdvanced Functional Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsUniversité du Québec à MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSilanizationMaterials scienceComposite materialMechanical vibrationVibrationAcoustics

Abstract

fetched live from OpenAlex

Abstract Bioinspiration offers alternative solutions to overcome the inherent drawbacks of glass, such as low fracture toughness, strength, and impact resistance. Synthetic composites inspired by natural materials, such as nacre, have been recently introduced as an alternative to glasses. However, these have all suffered from trade‐offs between rigidity, optical clarity, fabrication scalability, and complexity. Here, two wave‐based fabrication techniques are presented to create a nacreous structure from glass flakes and polymethyl methacrylate. The glass's surface energy is controlled by adjusting the silane coverage on the glass surface, enabling high levels of structural compactness, mechanical properties, and optical clarity. The scalable glass composite, with a ≈60% glass volume fraction, possesses strength, fracture toughness, and impact resistance values, outperforming annealed glass by 4300%, 350%, and 400%, respectively. It also has a haze level of ≈18%, almost 60% less than that of the similar centrifuged‐based glass composite. This composite is proposed as a potential glass alternative in diverse 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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
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 score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2024
Admission routes2
Has abstractyes

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