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Record W3094154906 · doi:10.1149/2162-8777/abc3cd

Review—State-of-the-Art Organic Solar Cells based on Carbon Nanotubes and Graphene

2020· article· en· W3094154906 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon nanotubeMaterials scienceOrganic solar cellGrapheneNanotechnologyCommercializationPhotovoltaic systemNanomaterialsRenewable energyEnergy conversion efficiencyEnergy transformationOptoelectronicsComposite materialBusinessElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

In the 21st century, photovoltaic (PV) is an emerging renewable energy source. According to its low production cost, organic solar cells (OSCs) exhibit huge potential in the commercialization market. Low-dimensional carbon nanomaterials with superb electronic, optical, mechanical properties have been proposed to serve as different functions in organic solar cells. In this paper, we systematically summarize the progress of carbon nanotube (CNT)- and graphene-based OSCs, including the photoactive, electrode and interfacial layers. It concludes that CNTs and graphene can play a crucial role in OSCs. Also, this review provides a summary and outlook on improving the performance of OSCs. At present, the device is in the direction of the hybrid system, high power conversion efficiency (PCE) and long lifetimes.

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)0.000
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 score0.010
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.198
Teacher spread0.193 · 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