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Record W4414193728 · doi:10.1139/cjc-2025-0168

Exploring the functionalization of Ag <sub>20</sub> nanoclusters through cluster surface tetrazine ligation

2025· article· en· W4414193728 on OpenAlexafffundvenue
Carolina Vega Verduga, Zhiqiang Wang, Tsun‐Kong Sham, John F. Corrigan, Mark S. Workentin

Bibliographic record

VenueCanadian Journal of Chemistry · 2025
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsUniversity of WaterlooWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanoclustersSurface modificationTetrazineCluster (spacecraft)NorborneneClick chemistryCharacterization (materials science)Single crystal

Abstract

fetched live from OpenAlex

Controlled synthesis of atomically precise silver nanoclusters (AgNC) exhibits some challenges due to inferior stability and limited solubility of silver precursors, which impacts their applications. Generating strategies for post-synthesis cluster modification can help expand the current applications and promote the production of hybrid nanomaterials. This approach has recently been explored using Cluster-Surface (CS)-click chemistry; however, the types of CS-click reactions have been limited, mostly to alkyne-azide cycloaddition. The aim of this study is to expand the scope of post-synthesis cluster-surface click chemistries for AgNC by incorporating the inverse electron demand Diels–Alder reaction (IEDDA) as a strategy for cluster surface functionalization. Here, the synthesis and characterization of a carbonate templated Ag 20 NC, [(CO 3 )@Ag 20 (S t Bu) 10 ( exo-C 7 H 9 COO) 8 (DMF) 4 ] (1- n), which bears a norbornene moiety susceptible to functionalization through IEDDA is reported. This study shows the structure of the nanocluster obtained through single crystal X-ray diffraction and characterization of the clicked product after reaction with a model s-tetrazine. This work highlights the versatility of click chemistry and offers a new path for cluster-surface modification.

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)0.000
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 score0.009
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.027
GPT teacher head0.222
Teacher spread0.195 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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