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Record W2767706661 · doi:10.1038/s41598-017-15745-3

Dye-sensitized solar cells based on a push-pull zinc phthalocyanine bearing diphenylamine donor groups: computational predictions face experimental reality

2017· article· en· W2767706661 on OpenAlexaff
R. Milan, Gurpreet Singh Selopal, Marco Cavazzini, Simonetta Orlandi, Rita Boaretto, Stefano Caramori, Isabella Concina, Gianluca Pozzi

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsInstitut National de la Recherche Scientifique
FundersRegione LombardiaVINNOVA
KeywordsDiphenylamineZincBearing (navigation)PhthalocyanineFace (sociological concept)Zinc fingerChemistryComputer scienceMaterials sciencePhotochemistryBiochemistryOrganic chemistryArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Computational studies have suggested that the integration of secondary amine as donor groups in the structure of unsymmetrical zinc phthalocyanine (ZnPc) should have positive effects on photovoltaic performance, once the molecule is integrated as light harvester in dye sensitized solar cells (DSSCs). Aiming at obtaining experimental confirmation, we synthesized a peripherally substituted push-pull ZnPc bearing three electron donating diphenylamine substituents and a carboxylic acid anchoring group and integrated it as sensitizer in TiO2-based DSSCs. Detailed functional characterization of solar energy converting devices resulted in ruling out the original hypothesis. The causes of this discrepancy have been highlighted, leading to a better understanding of the conditions for an effective design of push-pull diarylamino substituted ZnPcs for DSSCs.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.269
Teacher spread0.244 · 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 designSimulation or modeling
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

Citations25
Published2017
Admission routes1
Has abstractyes

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