FTIR Spectroelectrochemistry: Optimization of Experimental Setup
Bibliographic record
Abstract
The combination of FT-IR spectroscopy with electrochemistry offers insight in the molecular change during electrochemical reactions in an addition to the electrochemical response of the studied media. This method can be applied for investigations of electrolytes or reactions at electrode surfaces. New accessories for the spectroelectrochemical studies will be presented. Accessories can be configured for the reflection-absorption or for the attenuated total reflectance (ATR) measurements. IR reflection-absorbance spectroscopy (IRRAS) set-up is used for the studies of the electrolyte and the electrode surface while ATR configuration is used to analyze the electrode surface without strong influence of the electrolyte. Optimization of spectroelectrochemical setup and details of communication between the potentiostat and the FTIR spectrometer will be discussed. Example of applications will include electro oxidation of metal-organic complexes, alcohols, and glycerol.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".