Closely Following Equivalent Circuit Changes during Operation of Graphene Dot Light‐Emitting Electrochemical Cells
Bibliographic record
Abstract
Abstract Light‐emitting electrochemical cells (LECs) have presented themselves as an alternative to light emitting diodes (LEDs) because of the simple device design which is accompanied by a lower driving power. LECs operate by rearranging ion and electron transfers that create a p‐n junction at a sufficient voltage, permitting LEC emissions. However, this rearrangement is not well understood. Therefore, the ion and electron transfer processes of the device during ion rearrangement, operation and at excessive overpotentials must be characterized for LEC devices. This paper reports on investigation of these LEC processes using electrochemical impedance spectroscopy (EIS). All processes were successfully characterized with simple equivalent circuits. To the best of our knowledge, an inductive low frequency loop was observed in an LEC for the first time. We propose that this inductivity was due to the p‐n junction resistance to low frequency potential changes. Consistent observations and inverse proportionality between overpotential and inductance provided additional evidence for our proposal. This p‐n junction at low frequency opposition combined with LEC operational stability data can provide a basis for judging the chemical resistance to deterioration and charge storage capacity of p‐n junctions in the future. Furthermore, the techniques and equivalent circuits presented here will help to identify failure mechanisms and increase LEC operational lifetimes.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".