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Record W2275813958 · doi:10.1149/ma2015-01/18/1272

(Invited) Development of Printed Flexible Organic Solar Panels, Field Effect Transistors, and Logic Circuits on PET Substrates

2015· article· en· W2275813958 on OpenAlexaff
Salima Alem, Ta‐Ya Chu, Jianping Lu, Terho Kololuoma, Ye Tao

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsPMOS logicMaterials scienceFabricationNanotechnologyOptoelectronicsOrganic electronicsTransistorPrinted electronicsOrganic solar cellElectrical engineeringInkwellEngineeringComposite materialPolymer

Abstract

fetched live from OpenAlex

In this talk, I will introduce the research activities on the development of printed flexible organic solar panels, field effect transistors, and pMOS based logic circuits under NRC’s Printable Electronics Flagship Program. I will report the development of polycarbazole-based, printed organic solar panels and the application of a printable, air-stable, and annealing-free zinc oxide nanoparticle (ZnO NP) solution in the fabrication of inverted bulk heterojunction solar cells. The as-coated ZnO thin films are insoluble in organic solvents and can be directly used as an electron extraction layer in solar cells. The process is R2R compatible. Our non-encapsulated inverted solar cells are highly stable with their PCEs remaining unchanged after being stored in air for more than 50 days. The development of inkjet-printed pMOS inverters and logic gates on flexible substrates will be also presented. The fabrication of inkjet-printed OTFTs has achieved a yield of 97%. Different types of logic gates, inverters, and ring oscillators have been successfully fabricated by using these basic pMOS devices.

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 score0.007
Threshold uncertainty score0.024

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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