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Record W2904679948 · doi:10.1002/tcr.201800158

Revisiting the Optimal Nano‐Morphology: Towards Amorphous Organic Photovoltaics

2018· review· en· W2904679948 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Chemical Record · 2018
Typereview
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsAmorphous solidMaterials scienceActive layerNanotechnologyTernary operationCrystallitePhotovoltaicsPolymerFabricationOrganic solar cellPolymer solar cellLayer (electronics)Chemical engineeringPhotovoltaic systemOrganic chemistryChemistryComposite materialComputer science

Abstract

fetched live from OpenAlex

Organic photovoltaic cells commonly use an active layer with a polycrystalline bulk heterojunction. However, for simplifying the fabrication process, it may be worthwhile to use an amorphous active layer to lessen the burden on processing to achieve optimal performance. While polymers can adopt amorphous phases, molecular glasses, small molecules that can readily form glassy phases and do not crystallize over time, offer an appealing alternative, being monodisperse species. Our group has developed a series of reactive molecular glasses that can be covalently bonded to chromophores to form glass-forming adducts, and this strategy has been used to synthesize glass-forming donor and acceptor materials. Herein, the results of devices incorporating these materials in either partially or fully amorphous active layers are summarized. Additionally, these molecular glasses can be used as ternary components in crystalline systems to enhance efficiency without perturbing the morphology.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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