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Record W4283702793 · doi:10.1002/anie.202207600

Modulating Ti<i>t</i><sub>2g</sub>Orbital Occupancy in a Cu/TiO<sub>2</sub>Composite for Selective Photocatalytic CO<sub>2</sub>Reduction to CO

2022· article· en· W4283702793 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

VenueAngewandte Chemie International Edition · 2022
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsPhotocatalysisComposite numberReduction (mathematics)OccupancyMaterials scienceNuclear chemistryChemistryCatalysisComposite materialOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

Abstract The electronic structure of composites plays a critical role in photocatalytic conversion, whereas it is challenging to modulate the orbital for an efficient catalyst. Herein, we regulated the t 2g orbital occupancy state of Ti to realize efficient CO 2 conversion by adjusting the amount of photo‐deposited Cu in the Cu/TiO 2 composite. For the optimal sample, considerable electrons transfer from the Cu d orbital to the Ti t 2g orbital, as proven by X‐ray absorption spectroscopy. The Raman spectra results also corroborate the electron enrichment on the Ti t 2g orbital. Further theoretical calculations suggested that the orbital energy of the Ti 3d orbital in TiO 2 is declined, contributing to accepting Cu 3d electrons. As a result, the Cu/TiO 2 composite exhibited an extremely high selectivity of 95.9 % for CO, and the productivity was 15.27 μmol g −1 h −1 , which is almost 6 times that of the original TiO 2 . Our work provides a strategy for designing efficient photocatalysis as a function of orbital regulation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.282
Teacher spread0.269 · 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