Diazonium-Derived Aryl Films on Gold Nanoparticles: Evidence for a Carbon–Gold Covalent Bond
Bibliographic record
Abstract
Tailoring the surface chemistry of metallic nanoparticles is generally a key step for their use in a wide range of applications. There are few examples of organic films covalently bound to metal nanoparticles. We demonstrate here that aryl films are formed on gold nanoparticles from the spontaneous reduction of diazonium salts. The structure and the bonding of the film is probed with surface-enhanced Raman scattering (SERS). Extinction spectroscopy and SERS show that a nitrobenzene film forms on gold nanoparticles from the corresponding diazonium salt. Comparison of the SERS spectrum with spectra computed from density functional theory models reveals a band characteristic of a Au-C stretch. The observation of this stretch is direct evidence of a covalent bond. A similar band is observed in high-resolution electron energy loss spectra of nitrobenzene layers on planar gold. The bonding of these types of films through a covalent interaction on gold is consistent with their enhanced stability observed in other studies. These findings provide motivation for the use of diazonium-derived films on gold and other metals in applications where high stability and/or strong adsorbate-substrate coupling are required.
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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".