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Record W4296240050 · doi:10.1002/aesr.202200106

Gold Decorated Hydroxyapatite–CeO<sub>2</sub> Enabled Surface Frustrated Lewis Pairs for CO Oxidation

2022· article· en· W4296240050 on OpenAlexaff
Jiuli Guo, Rui Song, Zehao Li, Donghui Pan, Haijiao Xie, Yantao Ba, Ming Xie, Shijiao Fan, Xuedong Yang, Haibo Zhang, Huanhuan Yu, Shoumin Zhang, Jimin Du, Le He, Lu Wang

Bibliographic record

VenueAdvanced Energy and Sustainability Research · 2022
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsLewis acids and basesCarbon monoxideChemistryFrustrated Lewis pairMoleculeDiffuse reflectance infrared fourier transformPhotochemistryInfrared spectroscopyOxygenElectron paramagnetic resonanceCatalysisInorganic chemistryPhotocatalysisOrganic chemistryNuclear magnetic resonance

Abstract

fetched live from OpenAlex

The activation of molecular oxygen (O2) holds the fundamental step for reaction mechanism of carbon monoxide oxidation. Surface frustrated Lewis pairs (SFLPs) with sterically hindered Lewis acid–base pairs are proven to activate small molecules, such as hydrogen. However, the activation of molecular O2 on SFLPs remains unexplored. Herein, the construction of SFLPs in Au decorated hydroxyapatite (HAP)–CeO2 heterojunction is reported. The coordinately unsaturated Lewis acidic Ce3+ and the Lewis basic OH− group in HAP enable the activation of O2 molecules to –Ce3+ species for carbon monoxide (CO) oxidation. The active site is identified based on the comprehensive in situ electron paramagnetic resonance, in situ diffuse reflectance infrared Fourier transform spectroscopy, X‐Ray absorption spectroscopy, and theoretical simulation. The results provide a new strategy to construct SFLPs sites for O2 molecule activation and the subsequent CO oxidation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.323
Teacher spread0.302 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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