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Record W4417063233 · doi:10.1016/j.solmat.2025.114087

Electrochromic materials based on surface-confined terpyridine assemblies prepared via click chemistry

2025· article· en· W4417063233 on OpenAlexafffund
Marjan Saedi, Yelyzaveta V. Antsybora, Vittoria‐Ann DiPalo, Iraklii I. Ebralidze, E. Bradley Easton, Olena V. Zenkina

Bibliographic record

VenueSolar Energy Materials and Solar Cells · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Ontario Institute of Technology
KeywordsClick chemistryElectrochromismSiloxaneIndium tin oxideElectrochromic devicesLayer (electronics)Molecule

Abstract

fetched live from OpenAlex

In this work, we propose a methodology to create electrochromic materials (ECMs) using an on-surface click chemistry approach. We demonstrate that the click reaction between azide-terminated on-surface siloxane template ((4-azidophenyl)- or (4-(azidomethyl)phenyl)- siloxane layers) and the electrochromic (EC) molecular unit bearing accessible triple bonds, (bis-4'-(4-ethynyl-phenyl)-2,2':6′,2″-terpyridine) iron (II) complex), allows for an effective covalent embedding of well-defined molecular EC units into the porous conductive indium tin oxide (ITO) support. We show that minor structural modifications of the molecular moieties of the templating layer result in notable changes in the packing densities of the molecules on the surface of the support and significantly affect the performance and stability of the resulting EC materials. In more detail, the presence of only one additional CH 2 unit in the templating layer results in higher packing density on the surface. Resulting EC devices demonstrate rapid switching times on par with ED devices that utilize similar terpyridine-based EC moieties attached to the templating layer via N-alkylation and overall better long-term cycling durability. The click approach enables the construction of diverse EC molecular architectures, facilitating precise structural design and property tuning. We believe that the presented methodology holds significant promise for developing a broad range of novel EC materials.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.001

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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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