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Record W2085803154 · doi:10.1021/jp072587a

Structural Properties of Ionic Detergent Aggregates:  A Large-Scale Molecular Dynamics Study of Sodium Dodecyl Sulfate

2007· article· en· W2085803154 on OpenAlexaff
Maria Sammalkorpi, Mikko Karttunen, Mikko Haataja

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2007
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsWestern University
FundersNational Science Foundation
KeywordsSodium dodecyl sulfatePulmonary surfactantChemistryMolecular dynamicsKineticsMicelleIonic bondingSolventChemical physicsChemical engineeringMoleculePhysical chemistryComputational chemistryChromatographyOrganic chemistryIonAqueous solution

Abstract

fetched live from OpenAlex

The properties of sodium dodecyl sulfate (SDS) aggregates were studied through extensive molecular dynamics simulations with explicit solvent. First, we provide a parametrization of the model within Gromacs. Then, we probe the kinetics of aggregation by starting from a random solution of SDS molecules and letting the system explore its kinetic pathway during the aggregation of multiple units. We observe a structural transition for the surfactant aggregates brought upon by a change in temperature. Specifically, at low temperatures, the surfactants form crystalline aggregates, whereas at elevated temperatures, they form micelles. We also investigate the dependence of aggregation kinetics on surfactant concentration and report on the molecular level structural changes involved in the transition.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 head0.230
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations195
Published2007
Admission routes1
Has abstractyes

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