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Record W4413003134 · doi:10.1002/cplu.202500178

Covalent Attachment Strategies of Molecular Electrochromes for Enhancing Electrochromic Performance

2025· article· en· W4413003134 on OpenAlexafffund
A. Mohan Raj, Heorhii V. Humeniuk, W. G. Skene

Bibliographic record

VenueChemPlusChem · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrochromismPhysisorptionNanotechnologyCovalent bondMaterials scienceElectrochromic devicesMolecular switchElectrodeMoleculeChemistryOrganic chemistryAdsorption

Abstract

fetched live from OpenAlex

Electrochromes are emerging materials for enabling sustainable energy devices such as smart windows and low power-consuming displays along with automotive mirrors. This is owing to their electrochemical activity that results in unique optical transmission, modulating with applied potential. The molecular design rules of electrochromes are well established, consisting of electroactive components such as viologens, rhodamines, and transition metal complexes. While molecular electrochromes offer the advantage of establishing accurate structure/property relationships for tuning the optical transmission contingent on molecular structure, their physisorption on the electrodes limits the performance of electrochromic devices. Indeed, molecular electrochromes suffer from poor performance compared to their polymer counterparts in operating electrochromic devices. This perspective presents approaches to overcome these challenges. Focus is given to various strategies of covalently attaching molecular electrochromes to the device electrode for improving key electrochromic properties of contrast ratio and coloration efficiency. These operating device metrics are improved compared with the physisorption of molecular electrochromes via noncovalent interactions. The overarching goal is to provide useful insight that can be leveraged for the rational design of molecular electrochromes for their covalent attachment to electrodes toward matching device metrics of their polymer counterparts.

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 score0.023
Threshold uncertainty score0.485

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 head0.010
GPT teacher head0.290
Teacher spread0.280 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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