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Record W3200291514 · doi:10.1002/chem.202102926

Efficient Near‐Infrared Electrochemiluminescence from Au<sub>18</sub> Nanoclusters

2021· article· en· W3200291514 on OpenAlexafffund
Mahdi Hesari, Zhifeng Ding

Bibliographic record

VenueChemistry - A European Journal · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrochemiluminescenceNanoclustersPhotoluminescenceMaterials scienceNanotechnologyInfraredInfrared spectroscopyOptoelectronicsChemistryElectrodePhysicsPhysical chemistryOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Bright, near‐infrared electrochemiluminescence (NIR–ECL) of Au 18 nanoclusters is reported herein. Spooling ECL and photoluminescence spectroscopy were used to track and link NIR emissions at 832 and 848 nm to three emissive species, Au 18 0 *, Au 18 1+ * and Au 18 2+ *, with a considerably high ECL efficiency of 5.5 relative to that of the gold standard Ru(bpy) 3 2+ /TPrA (with 5–6 % reported ECL efficiency). The unprecedentedly high efficiency is due to the overlapped oxidation potentials of Au 18 0 and tri‐ n ‐propylamine as co‐reactant, the exposed facets of Au 18 0 gold core, and electrocatalytic loops. These discoveries will add a new member to the efficient NIR‐ECL gold nanoclusters family and bring more potential applications.

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), Insufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.207
Teacher spread0.196 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

Explore more

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