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Record W2110959060 · doi:10.1039/c2cs35019j

Nano-architecture and material designs for water splitting photoelectrodes

2012· review· en· W2110959060 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

VenueChemical Society Reviews · 2012
Typereview
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of British ColumbiaBC Innovation Council
Fundersnot available
KeywordsWater splittingNanotechnologyFabricationMaterials scienceNano-HydrogenProcess engineeringComputer sciencePhotocatalysisChemistryEngineeringCatalysis

Abstract

fetched live from OpenAlex

This review concerns the efficient conversion of sunlight into chemical fuels through the photoelectrochemical splitting of water, which has the potential to generate sustainable hydrogen fuel. In this review, we discuss various photoelectrode materials and relative design strategies with their associated fabrication for solar water splitting. Factors affecting photoelectrochemical performance of these materials and designs are also described. The most recent progress in the research and development of new materials as well as their corresponding photoelectrodes is also summarized in this review. Finally, the research strategies and future directions for water splitting are discussed with recommendations to facilitate the further exploration of new photoelectrode materials and their associated technologies.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.069
GPT teacher head0.342
Teacher spread0.272 · 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