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Record W2506184462 · doi:10.1021/acs.langmuir.6b01482

Phase Transitions in Dipalmitoylphosphatidylcholine Monolayers

2016· article· en· W2506184462 on OpenAlexaff
Yi Y. Zuo, Rimei Chen, Xianju Wang, Jinlong Yang, Zdenka Policova, A. W. Neumann

Bibliographic record

VenueLangmuir · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Toronto
FundersNational Institute on Minority Health and Health DisparitiesDivision of Chemical, Bioengineering, Environmental, and Transport Systems
KeywordsDipalmitoylphosphatidylcholineMonolayerPhase (matter)Phase transitionChemistryMaterials scienceCrystallographyNanotechnologyPhysicsThermodynamicsOrganic chemistryPhospholipidPhosphatidylcholineMembrane

Abstract

fetched live from OpenAlex

A self-assembled phospholipid monolayer at an air-water interface is a well-defined model system for studying surface thermodynamics, membrane biophysics, thin-film materials, and colloidal soft matter. Here we report a study of two-dimensional phase transitions in the dipalmitoylphosphatidylcholine (DPPC) monolayer at the air-water interface using a newly developed methodology called constrained drop surfactometry (CDS). CDS is superior to the classical Langmuir balance in its capacity for rigorous temperature control and leak-proof environments, thus making it an ideal alternative to the Langmuir balance for studying lipid polymorphism. In addition, we have developed a novel Langmuir-Blodgett (LB) transfer technique that allows the direct transfer of lipid monolayers from the droplet surface under well-controlled conditions. This LB transfer technique permits the direct visualization of phase coexistence in the DPPC monolayer. With these technological advances, we found that the two-dimensional phase behavior of the DPPC monolayer is analogous to the three-dimensional phase transition of a pure substance. This study has implications in the fundamental understanding of surface thermodynamics as well as applications such as self-assembled monolayers and pulmonary surfactant biophysics.

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 score0.050
Threshold uncertainty score0.222

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 head0.010
GPT teacher head0.276
Teacher spread0.266 · 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

Citations58
Published2016
Admission routes1
Has abstractyes

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