Identification of a Highly Luminescent Au<sub>22</sub>(SG)<sub>18</sub> Nanocluster
Bibliographic record
Abstract
The luminescence property of thiolated gold nanoclusters (Au NCs) is thought to involve the Au(I)-thiolate motifs on the NC surface; however, this hypothesis remains largely unexplored because of the lack of precise molecular composition and structural information of highly luminescent Au NCs. Here we report a new red-emitting thiolated Au NC, which has a precise molecular formula of Au22(SR)18 and exhibits intense luminescence. Interestingly, this new Au22(SR)18 species shows distinctively different absorption and emission features from the previously reported Au22(SR)16, Au22(SR)17, and Au25(SR)18. In stark contrast, Au22(SR)18 luminesces intensely at ∼665 nm with a high quantum yield of ∼8%, while the other three Au NCs show very weak luminescence. Our results indicate that the luminescence of Au22(SR)18 originates from the long Au(I)-thiolate motifs on the NC surface via the aggregation-induced emission pathway. Structure prediction by density functional theory suggests that Au22(SR)18 has two RS-[Au-SR]3 and two RS-[Au-SR]4 motifs, interlocked and capping on a prolate Au8 core. This predicted structure is further verified experimentally by Au L3-edge X-ray absorption fine structure analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".