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Record W2762314299 · doi:10.1515/pac-2017-0711

Water splitting catalyzed by titanium dioxide decorated with plasmonic nanoparticles

2017· article· en· W2762314299 on OpenAlex
Alexandra Gellé, Audrey Moores

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.

Bibliographic record

VenuePure and Applied Chemistry · 2017
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsPlasmonVisible spectrumPhotocatalysisChemistryWater splittingNanoparticleCatalysisTitanium dioxideNanotechnologyPhotochemistryUltravioletUltraviolet lightCharge carrierNanostructureOptoelectronicsChemical engineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract The development of active, cheap, efficient and visible-light-driven water splitting catalysts is currently the center of intense research efforts. Amongst the most promising avenues, the design of titania and plasmonic nanoparticle hybrids is particularly appealing. Titania has been known for long to be an active photocatalyst, able to perform water splitting under light irradiation. However, this activity is limited to the ultraviolet spectrum and suffers from too rapid charge carrier recombination. The addition of plasmonic nanostructures enables to push absorption properties to the visible region and prevent unwanted charge recombination. In this review, we explain the principles behind the activity of such nanohybrids towards visible light water splitting and detail the recent research developments relying on plasmonic metals, namely Au, Ag and Cu.

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)0.000
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 score0.014
Threshold uncertainty score0.621

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 communication0.0000.000
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 head0.006
GPT teacher head0.218
Teacher spread0.213 · 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