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Record W2322460977 · doi:10.1021/jz401818c

Unique Bonding Properties of the Au<sub>36</sub>(SR)<sub>24</sub> Nanocluster with FCC-Like Core

2013· article· en· W2322460977 on OpenAlexaff
Daniel M. Chevrier, A. Chatt, Peng Zhang, Chenjie Zeng, Rongchao Jin

Bibliographic record

VenueThe Journal of Physical Chemistry Letters · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCore (optical fiber)Materials scienceCrystallographyChemistryComposite material

Abstract

fetched live from OpenAlex

The recent discovery on the total structure of Au36(SR)24, which was converted from biicosahedral Au38(SR)24, represents a surprising finding of a face-centered cubic (FCC)-like core structure in small gold-thiolate nanoclusters. Prior to this finding, the FCC feature was only expected for larger (nano)crystalline gold. Herein, we report results on the unique bonding properties of Au36(SR)24 that are associated with its FCC-like core structure. Temperature-dependent X-ray absorption spectroscopy (XAS) measurements at the Au L3-edge, in association with ab initio calculations, show that the local structure and electronic behavior of Au36(SR)24 are of more molecule-like nature, whereas its icosahedral counterparts such as Au38(SR)24 and Au25(SR)18 are more metal-like. Moreover, site-specific S K-edge XAS studies indicate that the bridging motif for Au36(SR)24 has different bonding behavior from the staple motif from Au38(SR)24. Our findings highlight the important role of "pseudo"-Au4 units within the FCC-like Au28 core in interpreting the bonding properties of Au36(SR)24 and suggest that FCC-like structure in gold thiolate nanoclusters should be treated differently from its bulk counterpart.

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 score0.004

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 head0.014
GPT teacher head0.198
Teacher spread0.185 · 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

Citations45
Published2013
Admission routes1
Has abstractyes

Explore more

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