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Record W2025229137 · doi:10.1021/ma202596j

Diffusion Resonance of Nanoconfined Polymers

2012· article· fr· W2025229137 on OpenAlexafffund
Alexander Klotz, Hugo B. Brandão, Walter Reisner

Bibliographic record

VenueMacromolecules · 2012
Typearticle
Languagefr
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal diffusivityPolymerChemical physicsDiffusionConfined spaceLattice (music)MoleculeResonance (particle physics)ChemistryEnergy landscapeNanotechnologyMaterials scienceThermodynamicsPhysicsAtomic physics

Abstract

fetched live from OpenAlex

We examine the diffusive behavior of single polymers under spatially varying entropic confinement. A nanofluidic slit embedded with a lattice of pits was used to constrain single DNA molecules to discrete conformational states. Diffusion was characterized by dwelling in specific conformations followed by transitions to neighboring states. In contrast to studies involving simple 2D (nanoslit) and 1D (nanochannel) geometries, the diffusivity showed nonmonotonic dependence with respect to the parameters of confinement. In particular, the nanopit array allows us to fine-tune the diffusivity of a single polymer to a local resonance minimum. Moreover, we show that energetically favorable states dominate over higher energy states and that a single state can be stable over a wide range of parameter space. These stable states correspond to resonances in the diffusion.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.213
Teacher spread0.203 · 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 designObservational
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

Citations15
Published2012
Admission routes2
Has abstractyes

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