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Record W2079279575 · doi:10.1063/1.3623477

Organic photovoltaic power conversion efficiency improved by AC electric field alignment during fabrication

2011· article· en· W2079279575 on OpenAlexaff
Cindy X. Zhao, Xizu Wang, Wenjin Zeng, Zhi K. Chen, Beng S. Ong, Kewei Wang, Lulu Deng, Gu Xu

Bibliographic record

VenueApplied Physics Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFabricationEnergy conversion efficiencyMaterials sciencePhotovoltaic systemOptoelectronicsTransmission electron microscopyElectric fieldElectrical efficiencyNanotechnologyPower (physics)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

Ultra-low frequency AC field was employed to align p/n polymers during organic photovoltaic device fabrication. The resulting devices show 15% increase in power conversion efficiency and four-fold increase in parallel resistance. Supported by the transmission electron microscopy and atomic force microscopy images, the performance enhancement is attributed to the optimized morphology and enlarged p/n interface by AC field, which is more effective than DC, possibly explained by the argument of better mixing via back-and-forth shaking than a single swing.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.160
Teacher spread0.156 · 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 teacher head, not a consensus.

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

Citations28
Published2011
Admission routes1
Has abstractyes

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