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Record W4313431585 · doi:10.1002/anie.202218016

2D Transition Metal Dichalcogenides for Photocatalysis

2023· review· en· W4313431585 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

VenueAngewandte Chemie International Edition · 2023
Typereview
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Calgary
FundersShenzhen Science and Technology Innovation ProgramNatural Sciences and Engineering Research Council of CanadaUniversity Grants CommitteeJapan Society for the Promotion of Science London
KeywordsPhotocatalysisTransition metalMaterials scienceNanotechnologyChemistryCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Two-dimensional (2D) transition metal dichalcogenides (TMDs), a rising star in the post-graphene era, are fundamentally and technologically intriguing for photocatalysis. Their extraordinary electronic, optical, and chemical properties endow them as promising materials for effectively harvesting light and catalyzing the redox reaction in photocatalysis. Here, we present a tutorial-style review of the field of 2D TMDs for photocatalysis to educate researchers (especially the new-comers), which begins with a brief introduction of the fundamentals of 2D TMDs and photocatalysis along with the synthesis of this type of material, then look deeply into the merits of 2D TMDs as co-catalysts and active photocatalysts, followed by an overview of the challenges and corresponding strategies of 2D TMDs for photocatalysis, and finally look ahead this topic.

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 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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.001

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 head0.073
GPT teacher head0.354
Teacher spread0.281 · 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