Ultraflat, Pristine, and Robust Carbon Electrode for Fast Electron-Transfer Kinetics
Bibliographic record
Abstract
Electron-beam (e-beam) deposition of carbon on a gold substrate yields a very flat (0.43 nm of root-mean-square roughness), amorphous carbon film consisting of a mixture of sp 2 - and sp 3 -hybridized carbon with sufficient conductivity to avoid ohmic potential error. E-beam carbon (eC) has attractive properties for conventional electrochemistry, including low background current and sufficient transparency for optical spectroscopy. A layer of KCl deposited by e-beam to the eC surface without breaking vacuum protects the surface from the environment after fabrication until dissolved by an ultrapure electrolyte solution. Nanogap voltammetry using scanning electrochemical microscopy (SECM) permits measurement of heterogeneous standard electron-transfer rate constants ( k °) in a clean environment without exposure of the electrode surface to ambient air. The ultraflat eC surface permitted nanogap voltammetry with very thin electrode-to-substrate gaps, thus increasing the diffusion limit for k ° measurement to >14 cm/s for a gap of 44 nm. Ferrocene trimethylammonium as the redox mediator exhibited a diffusion-limited k ° for the previously KCl-protected eC surface, while k ° was 1.45 cm/s for unprotected eC. The k ° for Ru(NH 3 ) 6 3+/2+ increased from 1.7 cm/s for unprotected eC to above the measurable limit of 6.9 cm/s for a KCl-protected eC electrode.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".