Electron Transport in Electrodes Modified With Synthetic Clays Containing Electrochemically Active Transition Metal Sites
Bibliographic record
Abstract
Abstract Clay-modified electrodes (CMEs) are one type of chemically modified electrode. They are prepared by depositing thin films of clays on conductive substrates ( Macha and Fitch 1998; Baker and Senaratne 1993; Bard and Mallouk 1992; Fitch 1990). The aim is to make use of the physical and chemical properties of the clay coatings to control the electron transfer processes occurring at the electrode solution interface. Clay minerals have many desirable properties as electrode surface modifiers: high thermal and chemical stabilities, well defined layered structures with large surface area, wide adsorption capabilities and potential as catalysts and/or catalyst supports ( Newman and Brown 1987). CMEs have been used in selective analysis ( Zen et al. 1996a; Zen and Chen 1997), in catalysis ( Oyama and Anson 1986; Ouyang and Wang 1998) or as support matrices for catalysts ( Ghosh et al. 1984; Gobi and Ramaraj 1998), in the fabrication of electrochemical ( Rong and Mallouk 1993) and photoelectrochemical devices ( Gobi and Ramaraj 1994; Shyu and Wang 1997) etc. CMEs are also useful devices for the study of mass transport in clay films. For example, Fitch and coworkers ( Stein and Fitch 1996) have discussed the use of CMEs for the study of the diffusion of pollutants through clay beds. Since the clay films used in CMEs are very thin, transport of probe species through the films occurs on a
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".