Comparison of Diazonium Salt Derived and Thiol Derived Nitrobenzene Layers on Gold
Bibliographic record
Abstract
The reduction of diazonium salts to produce aryl films on surfaces has expanded in application from carbon electrodes to a variety of conducting materials. The increasing interest in this method for modifying gold surfaces has motivated us to directly compare the structure and stability of nitrobenzene films derived from diazonium salts with monolayers formed from the corresponding thiol. We employ spectroscopic and microscopic techniques to characterize the structure and thickness of the as-formed layers. As a means of assessing stability, the nitrobenzene films were subjected to rigorous sonication, refluxing solvents, and chemical displacement by octadecanethiol. Infrared reflection-absorption spectroscopy and electrochemical blocking were used to assess the stabilities of the films generated by the two methods. Sonication and refluxing both remove more material from the diazonium-derived film relative to the thiol monolayer. However, a significant amount of each layer remains bonded to the surface following these treatments. Immersion in octadecanethiol solution results in complete displacement of the thiol derived nitrobenzene monolayer. Importantly, a significant fraction of the diazonium derived films cannot be displaced by octadecanethiol. These findings show that under certain conditions aryl films formed from the reduction of diazonium salts are more strongly bonded to gold surfaces compared to the thiol analogue.
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 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".