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Record W3111341483 · doi:10.1039/d0dt03809a

Fast and high-yield synthesis of thiolate Ag<sub>44</sub> and Au<sub>12</sub>Ag<sub>32</sub> nanoclusters <i>via</i> the CTAB reverse micelle method

2020· article· en· W3111341483 on OpenAlexaff
Lubing Qin, Feng Zhang, Xiaoshuang Ma, Yun Tang, Guanyu Ma, Zhenghua Tang

Bibliographic record

VenueDalton Transactions · 2020
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsPetro-Canada
FundersGuangzhou Municipal Science and Technology ProjectNatural Science Foundation of Guangdong Province
KeywordsNanoclustersYield (engineering)MicelleMaterials scienceChemistryNanotechnologyCrystallographyPhysical chemistryAqueous solutionMetallurgy

Abstract

fetched live from OpenAlex

in a short time (15 min and 5 min), with a high yield of ∼83% and ∼85%, respectively. Furthermore, the mechanism regarding the reverse micelle method has been clearly elucidated. Through characterizing the reaction system by Raman spectroscopy and NMR spectroscopy techniques, it can be revealed that employing CTAB to form reverse micelles to construct a sealed chemical environment is critical for realizing the fast and high-yield synthesis.

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 score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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