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Record W4403378779 · doi:10.1002/adma.202412570

Embedding Reverse Electron Transfer Between Stably Bare Cu Nanoparticles and Cation‐Vacancy CuWO <sub>4</sub>

2024· article· en· W4403378779 on OpenAlexafffund
Xiyang Wang, Zhen Li, Xinbo Li, Chuan Gao, Yinghui Pu, Xia Zhong, Jingyu Qian, Minli Zeng, Xuefeng Chu, Zuolong Chen, Carl Redshaw, Hua Zhou, Cheng‐Jun Sun, Tom Regier, Graham King, James J. Dynes, Bingsen Zhang, Yanqiu Zhu, Guangshe Li, Yue Peng, Nannan 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
FundersArgonne National LaboratoryEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaOffice of ScienceNational Synchrotron Radiation LaboratoryNational Natural Science Foundation of ChinaCanadian Light SourceHefei Science Center, Chinese Academy of SciencesNatural Science Foundation of Guangxi Zhuang Autonomous RegionU.S. Department of Energy
KeywordsMaterials scienceVacancy defectNanoparticleCatalysisElectron transferChemical engineeringPassivationAdsorptionChemical physicsNanotechnologyPhotochemistryLayer (electronics)Physical chemistryChemistryCrystallography

Abstract

fetched live from OpenAlex

Abstract Cu nanoparticles (NPs) have attracted widespread attention in electronics, energy, and catalysis. However, conventionally synthesized Cu NPs face some challenges such as surface passivation and agglomeration in applications, which impairs their functionalities in the physicochemical properties. Here, the issues above by engineering an embedded interface of stably bare Cu NPs on the cation‐vacancy CuWO 4 support is addressed, which induces the strong metal‐support interactions and reverse electron transfer. Various atomic‐scale analyses directly demonstrate the unique electronic structure of the embedded Cu NPs with negative charge and anion oxygen protective layer, which mitigates the typical degradation pathways such as oxidation in ambient air, high‐temperature agglomeration, and CO poisoning adsorption. Kinetics and in situ spectroscopic studies unveil that the embedded electron‐enriched Cu NPs follow the typical Eley‐Rideal mechanism in CO oxidation, contrasting the Langmuir‐Hinshelwood mechanism on the traditional Cu NPs. This mechanistic shift is driven by the Coulombic repulsion in anion oxygen layer, enabling its direct reaction with gaseous CO to form the easily desorbed monodentate carbonate.

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)0.001
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.273
Teacher spread0.264 · 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 teacher head, not a consensus.

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

Citations26
Published2024
Admission routes2
Has abstractyes

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