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Record W4414064511 · doi:10.1063/5.0289397

Models for polymer dynamics from dimensionality reduction techniques

2025· article· en· W4414064511 on OpenAlexafffund
Phillip Bement, Jörg Rottler

Bibliographic record

VenueThe Journal of Chemical Physics · 2025
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCurse of dimensionalityNon-equilibrium thermodynamicsDimensionality reductionFourier transformSpinodal decompositionPrincipal component analysisDynamics (music)Field (mathematics)Spinodal

Abstract

fetched live from OpenAlex

Polymer dynamics is analyzed through the lens of linear dimensionality reduction methods, in particular principal and time-lagged independent component analysis (tICA). For a polymer undergoing ideal Rouse dynamics, the slow modes identified by these transformations coincide with the conventional Rouse modes. When applied to the Fourier modes of the segment density, we show that tICA generates dynamics equivalent to dynamic self-consistent field theory (D-SCFT) with a wavevector-dependent Onsager coefficient and a free energy functional subject to the random phase approximation. We then introduce a hidden variable method and a time-local approach to include temporal memory in the tICA-generated dynamics and generalize it to construct continuum models for the nonequilibrium case of spinodal decomposition of a symmetric diblock copolymer melt.

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 score0.214
Threshold uncertainty score0.315

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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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