Substrate Selection for Fundamental Studies of Electrocatalysts and Photoelectrodes: Inert Potential Windows in Acidic, Neutral, and Basic Electrolyte
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The selection of an appropriate substrate is an important initial step for many studies of electrochemically active materials. In order to help researchers with the substrate selection process, we employ a consistent experimental methodology to evaluate the electrochemical reactivity and stability of seven potential substrate materials for electrocatalyst and photoelectrode evaluation. Using cyclic voltammetry with a progressively increased scan range, we characterize three transparent conducting oxides (indium tin oxide, fluorine-doped tin oxide, and aluminum-doped zinc oxide) and four opaque conductors (gold, stainless steel 304, glassy carbon, and highly oriented pyrolytic graphite) in three different electrolytes (sulfuric acid, sodium acetate, and sodium hydroxide). We determine the inert potential window for each substrate/electrolyte combination and make recommendations about which materials may be most suitable for application under different experimental conditions. Furthermore, the testing methodology provides a framework for other researchers to evaluate and report the baseline activity of other substrates of interest to the broader community.
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.
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) | 0.000 | 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 it