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Record W2074804883 · doi:10.1117/12.2004601

Zinc oxide nanowire arrays for photovoltaic and light-emitting devices

2013· article· en· W2074804883 on OpenAlexaff
Bita Janfeshan, Bahareh Sadeghimakki, Navid M. S. Jahed, Siva Sivoththaman

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
Typearticle
Languageen
FieldMaterials Science
TopicZnO doping and properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceOptoelectronicsNanowireQuantum dotWaferPhotoluminescenceSpontaneous emissionWide-bandgap semiconductorPhotovoltaic systemExcited stateNanotechnologyOpticsLaser

Abstract

fetched live from OpenAlex

Knowledge of carrier transfer, in quantum dot sensitized solar cells, is the key to engineering the device structure and architecture optimization. In this work, Zinc oxide (ZnO) nanowire (NW) arrays were synthesized on glass wafers and on GaN thin films for application in photovoltaic and light-emitting devices. The nanowires grown on glass wafers were incorporated with CdSe/ZnS quantum dots (QD) and their steady state and lifetime photoluminescence (PL) were studied to investigate the feasibility of electron transfer from excited QDs to ZnO NWs. The results provide an indication that the injected electrons, from excited high quantum efficiency QDs, live longer and hence facilitate electron transport without undergoing non-radiative recombination at surface trap states. Morphology and optical properties of the ZnO nanowires on GaN film were also studied for application in light-emitting 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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicZnO doping and propertiesFrench-language works237,207