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Record W2488258811 · doi:10.1063/1.4958964

An In0.5Ga0.5N nanowire photoanode for harvesting deep visible light photons

2016· article· en· W2488258811 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAPL Materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicGa2O3 and related materials
Canadian institutionsMcMaster UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaClimate Change and Emissions Management CorporationMcMaster University
KeywordsPhotocurrentMaterials scienceNanowireOptoelectronicsIndiumMolecular beam epitaxySemiconductorPhotonOxideNanotechnologyEpitaxyOpticsLayer (electronics)

Abstract

fetched live from OpenAlex

III-nitride semiconductors hold tremendous promise for realizing high efficiency photoelectrodes. However, previously reported InGaN photoelectrodes generally exhibit very low photocurrent densities, due to the presence of extensive defects, dislocations, and indium phase separation. Here, we show that In0.5Ga0.5N nanowires with nearly homogeneous indium distribution can be achieved by plasma-assisted molecular beam epitaxy. Under AM1.5G one sun illumination, the InGaN nanowire photoanode exhibits a photocurrent density of 7.3 mA/cm2 at 1.2 V (vs. NHE) in 1M HBr. The incident-photon-to-current efficiency is above 10% at 650 nm, which is significantly higher than previously reported values of metal oxide photoelectrodes.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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