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Record W271177833 · doi:10.1007/0-306-47015-2_49

Monte Carlo Studies of the Self-Assembly of Amphiphilic Molecules

2005· book-chapter· en· W271177833 on OpenAlexafffund
Martin Kenward, M. D. Whitmore

Bibliographic record

VenueKluwer Academic Publishers eBooks · 2005
Typebook-chapter
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsMicelleMonte Carlo methodAmphiphilic moleculeAmphiphileMoleculeSelf-assemblySolventChemical physicsPulmonary surfactantMaterials scienceMolecular dynamicsStatistical physicsChemistryComputational chemistryPhysicsNanotechnologyPhysical chemistryThermodynamicsOrganic chemistryCopolymerAqueous solutionMathematicsPolymer

Abstract

fetched live from OpenAlex

Theoretical studies can provide useful insight into the self-assembly and aggregation of amphiphilic molecules in good solvent. In this paper, we report on Monte Carlo simulations of such systems in which the molecules form approximately spherical micelles. We carry out a systematic study of the aggregate sizes and size distributions, as well as the onset of micelle formation as functions of surfactant molecular weight, composition and solvent quality. The simulations use a 3-dimensional cubic lattice and a coarse grained model of the molecules. At each step of the simulation, we monitor various relaxation times in order to ensure that equilibrium is attained. The problem is computationally challenging because of the high molecular weight, chain-like structure of the molecules, the required minimum system size, and the very high energy barriers associated with inter-micelle movement of the chains.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.002
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 head0.027
GPT teacher head0.251
Teacher spread0.224 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes2
Has abstractyes

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