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Record W2138013789 · doi:10.5539/jmsr.v3n1p57

A Study on the Development of Organic Thin Film Solar Cell Devicewith Optimized Hole Transfer Layer of PEDOT:PSS

2013· article· en· W2138013789 on OpenAlexvenueno aff
Paik-Kyun Shin, Kumar Palanisamy, Abhirami Kumar, Katsuhiko Kato, Shizuyasu Ochiai

Bibliographic record

VenueJournal of Materials Science Research · 2013
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsnot available
Fundersnot available
KeywordsPEDOT:PSSMaterials scienceOrganic solar cellOLEDOptoelectronicsAnodeThin filmActive layerOrganic semiconductorSolar cellSolution processEnergy conversion efficiencyCathodeLayer (electronics)FabricationElectrodePolymerNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Organic thin film solar cells show generally lower power conversion efficiencies than those of the solar cells based on inorganic active materials. To solve the problem diverse research works have been tried: development of new organic semiconductors; modification of internal structure of active layers by means of organic solvent; design and fabrication of vertical device structure; introduction of buffer layer on the side of cathode electrode. Nevertheless, the buffer layer on the side of anode has not been fully optimized. This study is focused on the representative anode-side-buffer layer of Poly(3,4-ethylenedioxythiophene)(PEDOT): poly(styrenesulfonate) (PSS). PEDOT:PSS is an excellent conducting polymer material with favorably high optical transparency for almost entire range of visible wavelength, which is widely used for organic thin film solar cells as well as for other organic material based electronic devices such as organic light emitting diodes. Aiming for further performance enhancement of organic thin film solar cell device, an optimized condition was studied on the PEDOT:PSS by means of the thickness control and modification of the internal structure via addition of different organic solvents in mixture solution for thin film process.

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)0.008
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 score0.008
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.304
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2013
Admission routes1
Has abstractyes

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