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Record W2952053244 · doi:10.1002/ejoc.200400623

High‐Content Photochromic Polymers Based on Dithienylethenes

2005· article· en· W2952053244 on OpenAlexaff
Tony J. Wigglesworth, Andrew J. Myles, Neil R. Branda

Bibliographic record

VenueEuropean Journal of Organic Chemistry · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPhotochromismChemistryPolymerSolid-stateNanotechnologySolubilityState of artChemical engineeringOrganic chemistryBiochemical engineeringMaterials sciencePhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Dithienylethenes (DTEs) are one of the most promising classes of photochromic compounds for use in optoelectronic devices such as waveguides, memory media and sensors. The development of DTE based polymers that contain a high mass‐content of the photoactive DTE component, that maintain their photochromic activity in the solid‐state and that are easily processed into thin‐films under a variety of conditions is critical for the implementation of the materials into useful applications. This Microreview provides an overview of the current approaches for preparing DTE‐based polymers and discusses some of the problems associated with the resulting materials such as poor solubility, low DTE content and poor photochromic activity. We present specific examples from our own research, which highlight our research group’s contributions. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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 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

Citations79
Published2005
Admission routes1
Has abstractyes

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