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Record W2008401841 · doi:10.1063/1.481820

The ground-state phase behavior of model Langmuir monolayers

2000· article· en· W2008401841 on OpenAlexaff
Sheldon B. Opps, B. G. Nickel, C.G. Gray, D. E. Sullivan

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGround stateTilt (camera)MonolayerScalingChemistryLattice (music)RodMolecular physicsPhase transitionPhase (matter)PhysicsCondensed matter physicsAtomic physicsGeometry

Abstract

fetched live from OpenAlex

A coarse-grained model for surfactant molecules adsorbed at a water surface is studied at zero temperature to elucidate ground-state tilt ordering. The surfactants are modeled as rigid rods composed of head and tail segments, where the tails consist of effective monomers representing methylene CH2 groups. These rigid rods interact via site–site Lennard-Jones potentials with different interaction parameters for the tail–tail, head–tail, and head–head interactions. In this work, we study the effects due to variations in both the head diameter and bond length on transitions from untilted to tilted structures and from nearest-neighbor (NN) to next-nearest-neighbor (NNN) tilting. Coupling between tilt ordering and lattice distortion is also considered. We provide a molecular derivation of a scaling relation between tilt angles and distortion obtained previously by phenomenological arguments. Due to the discrete site–site nature of the model interactions, the predicted ground-state phase behavior is much richer than evidenced by models employing cylindrical rods. In particular, we have found transitions between different phases (i.e., NN–NN′ and NNN–NNN′) of similar symmetry, which may have experimental support. We have also examined the sensitivity of the transitions to details of the model, such as replacing Lennard-Jones head–head and head–tail potentials by purely repulsive interactions.

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 score0.028
Threshold uncertainty score0.241

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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

Citations7
Published2000
Admission routes1
Has abstractyes

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