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Record W4388937464 · doi:10.1002/solr.202300677

Solar Fuel Generation by 2D Self‐Assembled g‐C<sub>3</sub>N<sub>4</sub>/BiVO<sub>4</sub> Z‐Scheme

2023· article· en· W4388937464 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.

Bibliographic record

VenueSolar RRL · 2023
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBismuth vanadateHeterojunctionPhotocatalysisMaterials scienceGraphitic carbon nitrideGrapheneOxideElectron mobilityCharge carrierSolar fuelBand gapNanotechnologyOptoelectronicsChemical physicsChemistry

Abstract

fetched live from OpenAlex

Graphitic carbon nitride (g‐CN) is a promising photocatalyst for solar fuel generation due to its medium band gap and facile synthesis from earth‐abundant materials. However, low charge carrier mobility and high charge recombination have hampered the observed rate of H 2 evolution and CO 2 reduction. Herein, an electrostatically self‐assembled 2D Z‐scheme heterojunction between g‐CN and bismuth vanadate (BiVO 4 ) is investigated with and without reduced graphene oxide (rGO) acting as an electron transfer mediator to speed charge carrier mobility and hamper charge recombination. Protonation of the g‐CN surface allow for self‐assembly between 2D sheets of g‐CN, rGO, and BiVO 4 . The mass ratio between g‐CN and BiVO 4 is incrementally adjusted to optimize synergistic charge transportation effects versus shadowing effects of multicomponent photocatalysts. Further, a selectivity effect is observed across mass ratios of photocatalyst constituents, allowing tuning of photocatalyst yield.

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)0.001
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 categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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