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Record W3164682354 · doi:10.3390/electronicmat2020012

Pyrimidine-Based Push–Pull Systems with a New Anchoring Amide Group for Dye-Sensitized Solar Cells

2021· article· en· W3164682354 on OpenAlexaff
Egor V. Verbitskiy, Alexander S. Steparuk, Ekaterina F. Zhilina, В. В. Емец, Vitaly A. Grinberg, Ekaterina V. Krivogina, S. A. Kozyukhin, Ekaterina V. Belova, Petr Lazarenko, Gennady L. Rusinov, A. R. Tameev, Jean‐Michel Nunzi, Valery N. Charushin

Bibliographic record

VenueElectronic Materials · 2021
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsQueen's University
FundersMinistry of Science and Higher Education of the Russian FederationRussian Foundation for Basic Research
KeywordsMoietyDye-sensitized solar cellLinkerEnergy conversion efficiencyAmideAcceptorMaterials sciencePhotovoltaic systemPhotochemistryPyrimidineHalogenationPolymer chemistryChemistryOrganic chemistryOptoelectronicsStereochemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

New donor–π–acceptor pyrimidine-based dyes comprising an amide moiety as an anchoring group have been designed. The dyes were synthesized by sequential procedures based on the microwave-assisted Suzuki cross-coupling and bromination reactions. The influence of the dye structure and length of π-linker on the photophysical and electrochemical properties and on the photovoltaic effectiveness of dye-sensitized solar cells was investigated. An increase in efficiency with a decrease in the length of π-linker was revealed. The D1 dye with only one 2,5-thienylene-linker provided the highest power conversion efficiency among the fabricated dye sensitized solar cells.

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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