Frequency Response of the Graphene Electrode with Finite Conductivity in Electrochemical Systems
Bibliographic record
Abstract
We investigate the frequency-dependent electrochemical behavior of a finite-sized graphene disk electrode (GE) in contact with an electrolyte under a three-dimensional cylindrical configuration. The study is performed by modeling the GE with a finite conductivity derived from its intrinsic quantum-mechanical properties to derive an analytical expression for its quantum surface impedance and then examine the charge relaxation dynamics in both the frequency and time domains. The analysis reveals a transition from Warburg-type impedance in the high-frequency regime to RC-circuit behavior at low frequencies, governed by the quantum capacitance and conductivity of graphene. Next, to interface the GE with the electrolyte, the three-dimensional problem is reduced to a one-dimensional problem by introducing the surface averaging of the variables using the application of the Hankel transform. This enables us to generalize the impedance modeling of our recent work [ J. Electroanal. Chem. 2023, 946, 117711] where GE was idealized as a uniformly charged capacitor. The results are discussed under the influence of ion concentration, electrode radius, and external circuitry both in the regime where the electrochemical impedance spectroscopy (EIS) and the electrochemical capacitive spectroscopy (ECS) are applicable and beyond.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".