MétaCan
Menu
Back to cohort
Record W2031103543 · doi:10.1063/1.4748059

Optimizing the photovoltage of polymer/zinc oxide hybrid solar cells by calcium doping

2012· article· en· W2031103543 on OpenAlexaff
Mingqing Wang, Jon‐Paul Sun, Sandy Suei, Ian G. Hill

Bibliographic record

VenueJournal of Applied Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBand gapHybrid solar cellAcceptorMaterials scienceDopingHOMO/LUMOSolar cellElectron acceptorPolymer solar cellOrganic solar cellOptoelectronicsZincChemistryAnalytical Chemistry (journal)PhotochemistryPolymerCondensed matter physics

Abstract

fetched live from OpenAlex

The voltage produced by an excitonic solar cell, such as an organic or a hybrid organic/inorganic solar cell is limited by the difference in potential energy between the state occupied by the electron in the acceptor (conduction band minimum (CBM)/lowest unoccupied molecular orbital) and that occupied by the hole in the donor (valence band maximum/highest occupied molecular orbital). Calcium doping of sol-gel ZnO has been used to change the electron affinity of the ZnO acceptor in ZnO/poly(3-hexyl thiophene) hybrid solar cells. The band gap of the mixed oxide system increases with Ca fraction, with most of this attributable to movement of the conduction band minimum toward the vacuum, as determined by UV-vis spectroscopy and Kelvin probe. In planar bilayer cells using Zn0.9Ca0.1O as the acceptor, the open circuit voltage can be increased by 0.24 V, and the efficiency doubled compared to devices using pure ZnO.

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 score0.002

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 communication0.0010.000
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 head0.008
GPT teacher head0.200
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

Citations9
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied PhysicsSame topicOrganic Electronics and PhotovoltaicsFrench-language works237,207