Semiconductors as Selective Redox Electrodes
Bibliographic record
Abstract
Electrodes that selectively exchange charge with only certain redox couples in a mixture could improve the performance of photogalvanic and bio-photovoltaic cells described in the literature. One avenue to achieve selectivity is through the use of semiconducting rather than metallic electrodes to exploit the presence of the bandgap to control reaction rates. In this paper, Fluorine doped Tin oxide (F:SnO 2 ), Copper(II) oxide (CuO) and Nickel oxide (NiO) electrodes are investigated as a means to achieving selective redox reactions. The reactions of methyl viologen, ferricyanide/ferrocyanide and ferric/ferrous couples on the three semiconducting electrodes were studied using cyclic voltammetry and sampled current voltammetry. The rate of electron transfer between the electrodes and the redox couples depended on the difference between the semiconductor majority carrier band edge and the standard redox potential of the redox couple. Most noticeably, the rate constant of methyl viologen on F:SnO 2 was two orders of magnitude higher than that for the ferric/ferrous ion. Similar results were obtained with the NiO electrode while electrochemical instability hampered the tests of the CuO 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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.008 | 0.001 |
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.
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; both teacher heads agree on what is shown here.
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".