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Record W2793271605 · doi:10.1039/c8sm00184g

Nonlinear chiral rheology of phospholipid monolayers

2018· article· en· W2793271605 on OpenAlexaff
KyuHan Kim, Siyoung Q. Choi, Joseph A. Zasadzinski, Todd M. Squires

Bibliographic record

VenueSoft Matter · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsKootenay Association for Science & Technology
FundersNational Heart, Lung, and Blood InstituteNational Research Foundation of KoreaNational Heart and Lung InstituteNational Science Foundation
KeywordsChirality (physics)MonolayerShearing (physics)Materials scienceDipalmitoylphosphatidylcholineNucleationRheologyCrystallographyChemical physicsComposite materialChemistryMembraneNanotechnologyPhospholipidPhysics

Abstract

fetched live from OpenAlex

Microbutton rheometry reveals that the chiral morphology of dipalmitoylphosphatidylcholine (DPPC) monolayers imparts a chiral nonlinear rheological response. The nonlinear elastic modulus and yield stress of DPPC monolayers are greater when sheared clockwise (C), against the natural winding direction of DPPC domains, than counter-clockwise (CC). Under strong CC shear strains, domains deform plastically; by contrast, domains appear to fracture under strong C shearing. After CC shearing, extended LC domains develop regular patterns of new invaginations as they recoil, which we hypothesize reflect the nucleation and growth of new defect lines across which the tilt direction undergoes a step change in orientation. The regular spacing of these twist-gradient defects is likely set by a competition between the molecular chirality and the correlation length of the DPPC lattice. The macroscopic mechanical consequences of DPPC's underlying molecular chirality are remarkable, given the single-component, non-cross-linked nature of the monolayers they form.

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 score0.017
Threshold uncertainty score0.741

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)0.0010.000

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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