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Record W2945663805 · doi:10.1039/c9na00084d

Vapor growth of binary and ternary phosphorus-based semiconductors into TiO<sub>2</sub> nanotube arrays and application in visible light driven water splitting

2019· article· en· W2945663805 on OpenAlexafffund
Ebru Üzer, Pawan Kumar, Ryan Kisslinger, Piyush Kar, Ujwal Kumar Thakur, Karthik Shankar, Tom Nilges

Bibliographic record

VenueNanoscale Advances · 2019
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsAlberta Hospital Edmonton
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftUniversity of AlbertaCMC Microsystems
KeywordsMaterials scienceTernary operationSemiconductorWater splittingNanotubeVisible spectrumPhotocatalysisNanofiberNanotechnologyChemical engineeringOptoelectronicsCarbon nanotubeCatalysisChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Polyphosphide–TiO <sub>2</sub> hybrid materials, like SnIP@TiO <sub>2</sub> , are used as photocatalysts for PEC-water-oxidation: SnIP a double helix semiconductor reacted as nanofibers onto and into TiO <sub>2</sub> nanotube arrays. Due to synergetic effects an enhanced water splitting performance was found.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.048
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.004
GPT teacher head0.228
Teacher spread0.224 · 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 teacher head, 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

Citations18
Published2019
Admission routes2
Has abstractyes

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