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Record W2882247332 · doi:10.1002/slct.201800762

Low‐Bandgap Terpolymers for High‐Gain Photodiodes with High Detectivity and Responsivity from 300 nm to 1600 nm

2018· article· en· W2882247332 on OpenAlexaff
Jinfeng Han, Dezhi Yang, Liuyong Hu, Dongge Ma, Wenqiang Qiao, Zhi Yuan Wang

Bibliographic record

VenueChemistrySelect · 2018
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsCarleton University
FundersNational Natural Science Foundation of China
KeywordsResponsivityPhotodiodePhotocurrentOptoelectronicsMaterials sciencePhotodetectorSpecific detectivityActive layerDark currentBand gapLayer (electronics)OpticsNanotechnologyPhysicsThin-film transistor

Abstract

fetched live from OpenAlex

Abstract Three strong electron‐withdrawing monomers and one electron‐donating monomer were chosen by design to impart some desirable properties to the target terpolymers (P1‐P3) for use in the photodiodes, such as strong donor‐acceptor charge transfer, low bandgap, high mobility and good film morphology. Photodiodes with a device structure of ITO/ZnO/active layer/BCP/Al exhibited a significant increase of EQE only under forward bias. In particular, the P2‐based device had the specific detectivity greater than 10 13 Jones from 330 nm to 1060 nm and 10 11 Jones from 300 nm to 1600 nm under 0.5 V and linear dynamic range over 100 dB under 2.0 V. In comparison, after the UV light treatment to the ZnO layer, the P2‐based photodiodes exhibited a high gain in photocurrent under both forward and reverse bias and had specific detectivity above 10 13 Jones at 320–1140 nm, 10 12 Jones at 300–1460 nm and 10 11 Jones at 300–1600 nm under 0.5 V. Our work has firstly demonstrated that high gain and high detectivity in polymer photodetector could be readily achieved under forward bias without the UV light treatment.

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 score0.002
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 head0.189
Teacher spread0.185 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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