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Record W2153226463 · doi:10.1039/c3sm50742d

Elasticity of flexible polymers under cylindrical confinement: appreciating the blob scaling regime in computer simulations

2013· article· en· W2153226463 on OpenAlexaff
Juin Kim, Chanil Jeon, Hawoong Jeong, Youngkyun Jung, Bae‐Yeun Ha

Bibliographic record

VenueSoft Matter · 2013
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScalingExponentCrossoverElasticity (physics)PolymerStatistical physicsChain (unit)Nonlinear systemNonlinear elasticityRelaxation (psychology)PhysicsParameter spaceMonomerMathematicsThermodynamicsGeometryComputer scienceQuantum mechanicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

Despite much renewed interest in cylindrically confined polymers with linear or nonlinear topology, often considered as model chromosomes, their scaling predictions, especially on chain elasticity and relaxation, have not been reconciled with numerical data. Of particular interest is their “effective spring constant” given in the scaling form of keff ∼ N−αD−γ, where N is the number of monomers and D the diameter of the cylindrical space. If the blob-scaling approach produces α = 1 and γ = 2 − 1/ν = 1/3 with ν = 3/5 the Flory exponent, a series of numerical studies indicate α ≈ 0.75 and unexpectedly large γ ≈ 0.9. Using computer simulations, we show that there exists a crossover from the formerly called unexpected to blob-scaling regime at a certain value of D ≈ 10 (in units of monomer sizes) for sufficiently large N (>Ncr). Our results suggest that Ncr ≈ 1000, if the farthermost distance is used as the chain size: a quantity relevant in single-chain manipulations or for ring polymers (e.g., bacterial chromosomes). Accordingly, chain relaxation dynamics is expected to show a similar crossover. Our results imply that the applicability of the blob scaling approach depends on how confined chains are characterized.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.952

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 head0.010
GPT teacher head0.206
Teacher spread0.195 · 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 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

Citations22
Published2013
Admission routes1
Has abstractyes

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