Analysis of battery-like and pseudocapacitive ion intercalation kinetics via distribution of relaxation times
Bibliographic record
Abstract
Improving the kinetics of electrochemical ion intercalation processes is of interest for realizing high-power electrochemical energy storage. This includes classical battery-like intercalation and pseudocapacitive intercalation processes with a capacitor-like electrochemical signature. Electrochemical methods are needed to probe the kinetics of such complex multistep processes in detail. Here, we present the use of the Distribution of Relaxation Times (DRT) analysis of electrochemical impedance data to identify the kinetic limits of intercalation reactions. We study the lithium intercalation reaction in TiS2 from organic and aqueous electrolytes as a model system. The material can exhibit both battery-like and pseudocapacitive intercalation regimes depending on the potential range, variable diffusion lengths by adjusting its particle size, and a tunable degree of solvent cointercalation by choosing the electrolyte solvent. Using DRT, we can distinguish between the kinetic limitations imposed by solid-state ion diffusion, interfacial ion adsorption and transport, and ion desolvation processes. Thus, DRT analysis can complement existing methods, such as voltammetry or 3D-Bode analysis, to better understand the kinetics of intercalation reactions.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".