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Record W4414243200 · doi:10.1021/acs.jpcb.5c05224

Aggregation Analysis of Simulated Electric Field Poled Poly(methyl methacrylate) Doped with Tricyanopyrroline Chromophores

2025· article· en· W4414243200 on OpenAlexaff
Nils M. Denda, Erik Rohloff, Peter Behrens, Andreas Schneider

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsInnovation Cluster (Canada)
FundersDeutsche Forschungsgemeinschaft
KeywordsChromophorePolingElectric fieldPolymerRelaxation (psychology)Aggregate (composite)Phase (matter)Dipole

Abstract

fetched live from OpenAlex

Dipolar chromophore molecules embedded with noncentrosymmetric alignment in a polymer matrix may exhibit nonlinear electro-optical (EO) activity. The polymer matrix serves as a host, stabilizing the alignment of chromophores and conserving the EO activity in the glass state. However, at high chromophore number densities and/or elevated temperatures, aggregation may occur, resulting in a loss or at least altered EO response. Here, we present a novel and general Python-based tool for the analysis of aggregation and phase behavior. Our method provides frequency distributions of aggregate size (i.e., number of involved molecules) and aggregate types (i.e., the mutual molecular arrangement). The aggregation analysis is illustrated for the molecular dynamics simulation of electric field poling and relaxation (i.e., the analysis of the phase behavior). The analysis method helps to identify and visualize the process of aggregation and can be adapted to various models (e.g., liquid crystalline materials) if the shape of the molecule of interest is properly considered.

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 score0.003
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.007
GPT teacher head0.277
Teacher spread0.269 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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