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Record W3124496379 · doi:10.1002/smll.202004539

Probing the Thermal Stability of (3‐Mercaptopropyl)‐trimethoxysilane‐Protected Au<sub>25</sub> Clusters by In Situ Transmission Electron Microscopy

2021· article· en· W3124496379 on OpenAlexafffund
V. Sudheeshkumar, Charles Soong, Stas Dogel, Robert W. J. Scott

Bibliographic record

VenueSmall · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsHitachi (Canada)University of Saskatchewan
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOstwald ripeningCatalysisMaterials scienceTransmission electron microscopyCoalescence (physics)SinteringChemical engineeringNanoparticleEconomies of agglomerationMesoporous materialThermal stabilityIn situMesoporous silicaParticle (ecology)NanotechnologyChemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract High‐surface‐area gold catalysts are promising catalysts for a number of selective oxidation and reduction reactions but typically suffer catalyst deactivation at higher temperatures. The major reason for catalyst deactivation is sintering, which can be triggered via two mechanisms: particle migration and coalescence, and Ostwald ripening. Herein, a direct method to synthesize Au 25 clusters stabilized with 3‐mercaptopropyltrimethoxysilane (MPTS) ligands is discussed. The sintering of Au 25 (MPTS) 18 clusters on mesoporous silica (SBA‐15) is monitored by using an environmental in situ transmission electron microscopy (TEM) technique. Results show that agglomeration of smaller particles is accelerated by increased mobility of particles during heat treatment, while growth of immobile particles occurs via diffusion of atomic species from smaller particles. The mobility of the Au clusters can be alleviated by fabricating overlayers of silica around the clusters. The resulting materials show tremendous sinter‐resistance at temperatures up to 650 °C as shown by in situ TEM and extended X‐ray absorption fine structure analysis.

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 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 score0.004
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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.

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

Citations15
Published2021
Admission routes2
Has abstractyes

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