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Record W7067251199

Mechanics of interfaces within biological and biomimetic materials

2014· dissertation· en· W7067251199 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2014
Typedissertation
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsnot available
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesRéseau de Recherche en Santé Buccodentaire et OsseuseNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsToughnessFracture mechanicsFracture toughnessFracture (geology)MicromechanicsDeformation (meteorology)Composite number
DOInot available

Abstract

fetched live from OpenAlex

Nature, through millions of years, has evolved mechanically superior materials which have recently become a rich source of inspiration. Virtually all hard biological materials are composites where stiff, elongated inclusions are bound together through a soft polymeric “glue”. In some of these composites such as nacre and bone, the stiff component is a hard and stiff minerals (aragonite in nacre and hydroxyapatite in bone) forming mineral-polymer composite while for others, such as tendon and plant cell wall, a stiff and strong polymer (collagen in tendon and cellulose in plant cell wall) constitutes the inclusion part of the polymer-polymer composite. These building blocks are bonded by softer organic materials, and the overall properties of these natural materials are highly dependent on the properties of these “weaker” interfaces. While the mechanical properties and the role of inclusions are well studied and understood, there is far less work reported in literature on the mechanics and properties of weak biological interfaces, and their composition, structure and mechanics are poorly understood. In this study the mechanical properties of weak biological interfaces in mollusk nacre are measured and their mechanics of deformation and fracture is characterized. To this end, first, the fracture toughness of interfaces within three different types of nacre (namely top shell, pearl oyster, and red abalone) is, for the first time, determined through combing the result of chevron notch fracture test, micrographs obtained from scanning electron microscope, and linear elastic fracture mechanics concept. The results revealed that fracture toughness of polymeric interfaces within nacre is indeed extremely low, in the order of the toughness of the mineral inclusions. A novel experimental method called Rigid Double Cantilever Beam (RDCB) is developed to measure the fracture toughness of very soft polymeric and biological interfaces. The method not only determines the fracture toughness of interfaces but also yields their cohesive strength, extensibility and stiffness. The method is successfully implemented on three engineering adhesives, and their fracture toughness and cohesive law are reported. The RDCB test is also used to study the effect of substrate, and chemical treatment on the interfacial fracture toughness and cohesive properties of a biological adhesive fibrin network. An eight-chain based model is then proposed to elucidate the bell-shaped cohesive law of fibrin interfaces. The new method can be used to characterize the cohesive behavior of other important proteins such as bone osteopontin. Finally, an improved fracture mechanics based criterion is developed to predict the failure of biological and engineered staggered composites. The model captures the nonuniform distribution of shear stresses along the interfaces, and the resulting stress fields within the inclusions. The criterion can be applied for a wide array of material behavior at the interface and will lead to optimal designs for the interfaces, in order to harness the full potential of bio-inspired composites.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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