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Record W3192750118 · doi:10.1098/rsta.2020.0338

From vesicles to materials: bioinspired strategies for fabricating hierarchically structured soft matter

2021· article· en· W3192750118 on OpenAlexafffund
Esther Amstad, Matthew J. Harrington

Bibliographic record

VenuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2021
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsMcGill University
FundersNational Centre of Competence in Research RoboticsCanada Research Chairs
KeywordsNanotechnologyByssusSoft materialsBiomimetic materialsMaterials scienceSoft matterLiquid crystallineBiochemical engineeringComputer scienceEngineeringMusselPolymerBiologyChemical engineeringEcologyComposite material

Abstract

fetched live from OpenAlex

Certain organisms including species of mollusks, polychaetes, onychophorans and arthropods produce exceptional polymeric materials outside their bodies under ambient conditions using concentrated fluid protein precursors. While much is understood about the structure-function relationships that define the properties of such materials, comparatively less is understood about how such materials are fabricated and specifically, how their defining hierarchical structures are achieved via bottom-up assembly. Yet this information holds great potential for inspiring sustainable manufacture of advanced polymeric materials with controlled multi-scale structure. In the present perspective, we first examine recent work elucidating the formation of the tough adhesive fibres of the mussel byssus via secretion of vesicles filled with condensed liquid protein phases (coacervates and liquid crystals)-highlighting which design principles are relevant for bio-inspiration. In the second part of the perspective, we examine the potential of recent advances in drops and additive manufacturing as a bioinspired platform for mimicking such processes to produce hierarchically structured materials. This article is part of the theme issue 'Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 1)'.

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 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 score0.434
Threshold uncertainty score0.460

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 communication0.0000.000
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 head0.023
GPT teacher head0.250
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2021
Admission routes2
Has abstractyes

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Same venuePhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesSame topicSurface Modification and SuperhydrophobicityFrench-language works237,207