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Record W4400422591 · doi:10.1002/adma.202407534

Reverse Hydrogen Spillover on Metal Oxides for Water‐Promoted Catalytic Oxidation Reactions

2024· article· en· W4400422591 on OpenAlexafffund
Hao Fu, Hongjie Liu, Xiyang Wang, Wenhua Zhang, Hui Zhang, Yunhong Luo, Xianwang Deng, Graham King, Ning Chen, Liwei Wang, Yimin A. Wu

Bibliographic record

VenueAdvanced Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsCanadian Light Source (Canada)University of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of ChinaDivision of Graduate EducationNatural Science Foundation of Guangxi Zhuang Autonomous Region
KeywordsCatalysisHydrogen spilloverMetalAdsorptionOxideMaterials scienceHydrogenInorganic chemistryPhotochemistryChemical engineeringChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Understanding the water‐involved mechanism on metal oxide surface and the dynamic interaction of water with active sites is crucial in solving water poisoning in catalytic reactions. Herein, this work solves this problem by designing the water‐promoted function of metal oxides in the ethanol oxidation reaction. In situ multimodal spectroscopies unveil that the competitive adsorption of water‐dissociated *OH species with O 2 at Sn active sites results in water poisoning and the sluggish proton transfer in CoO‐SnO 2 imparts water‐resistant effect. Carbon material as electron donor and proton transport channel optimizes the Co active sites and expedites the reverse hydrogen spillover from CoO to SnO 2 . The water‐promoted function arises from spillover protons facilitating O 2 activation on the SnO 2 surface, leading to crucial *OOH intermediate formation for catalyzing C‐H and C‐C cleavage. Consequently, the tailored CoO‐C‐SnO 2 showcases a remarkable 60‐fold enhancement in ethanol oxidation reaction compared to bare SnO 2 under high‐humidity conditions.

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 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)0.002
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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

Citations18
Published2024
Admission routes2
Has abstractyes

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