Probing the Influence of Counter Electrode Structure on Electrochromic‐Device Operating Potentials and Performance Using Electrochemical Impedance Spectroscopy
Bibliographic record
Abstract
Abstract The paper reports a general methodology for the rational tuning and optimization of electrochromic devices (ECDs) that are based on a monolayer of Fe (II) (4’‐(4‐pyridyl)‐2,2’:6’,2”‐terpyridine)2 complex (Fe 4’T) covalently embedded onto a screen‐printed high‐surface area indium tin oxide working electrode. We demonstrate that the nature of the counter electrode and the resulting device configuration could drastically improve the long‐term stability of the ECD. We show that the replacement of the flat ITO glass electrode with a high surface area ITO electrode or the use of symmetrical working and counter electrode architecture leads to a much longer performance of the device. We propose a methodology to determine optimal operating conditions for ECDs by fine‐tuning the lower and upper operation potentials. In addition to using traditional cyclic voltammetry (CV), we utilize electrochemical impedance spectroscopy (EIS) to study the intrinsic properties of the devices and understand the factors that define the long‐term cycling stability, which is further described through the use of equivalent circuit models. The main reasoning behind decomposition processes in ECDs and ways to suppress them are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".