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Record W2061629002 · doi:10.1117/12.662829

Flexible encapsulation for organic solar cells

2006· article· en· W2061629002 on OpenAlexaff
Christoph Lungenschmied, Gilles Dennler, Grzegorz Czeremuzskin, Mohamed El Hadi Latreche, Helmut Neugebauer, Niyazi Serdar Sariçiftçi

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsNova Chemicals (Canada)
Fundersnot available
KeywordsMaterials scienceOrganic solar cellOrganic semiconductorPlasma-enhanced chemical vapor depositionPhotovoltaic systemPolymerPolymer solar cellCoatingOptoelectronicsChemical vapor depositionChemical engineeringNanotechnologySolar cellComposite material

Abstract

fetched live from OpenAlex

Efficient organic photovoltaic devices show many interesting properties, but share a common drawback, namely their instability in atmosphere. We report on a shelf lifetime study of solar cells based on blends of two widely used polymeric semiconductors with 1-(3-methoxycarbonyl) propyl-1-phenyl[6,6]C61 (PCBM), encapsulated in a new flexible and transparent poly(ethylene naphthalate) (PEN)-based ultra-high barrier material. The barrier coating is entirely fabricated by plasma enhanced chemical vapor deposition (PECVD). The conjugated polymers used are poly(2-methoxy-5-(3',7'-dimethyloctyloxy)-1,4-phenylene-vinylene) (MDMO-PPV) and poly(3-hexyl)thiophene (P3HT). We have observed in this work that the encapsulation raises the shelf lifetime (50 % of the initial efficiency) from a few hours into the range beyond 3,000 hours for MDMO-PPV based devices. Using the more stable P3HT, the lifetime could be increased to approximately 6,000 hours, or more than eight months.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations19
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOrganic Electronics and PhotovoltaicsFrench-language works237,207