Inductive Heating for Research in Electrocatalysis: Theory, Practical Considerations, and Examples
Bibliographic record
Abstract
Inductive heating in neutral or slightly reducing gaseous atmosphere has become one of the most effective methods to thermally pretreat oxygen-sensitive monocrystalline electrodes for interfacial electrochemistry and electrocatalytic research. In this contribution, we discuss the principles and theory of inductive heating, and we explain how an alternating current passing through a coil induces a resistive current inside a conductive sample. The thermodynamics and heat transport phenomena of how the thermal energy propagates and heats the sample are then discussed. Practical considerations with examples are given about how to best utilize this technique and avoid sample damage by controlling the gaseous atmosphere surrounding the sample being treated. Finally, a Ni(111) electrode is used to demonstrate the applicability of the method to interfacial electrochemistry and electrocatalysis research. The post-thermal treatment demonstrates the effect of the presence of small amounts of oxygen in the gaseous atmosphere on cyclic voltammetry profiles acquired in aqueous alkaline media.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".