Temperature Dependent EIS Studies Separating Charge Transfer Impedance from Contact Impedance in Lithium-Ion Symmetric Cells
Bibliographic record
Abstract
Measuring electrochemical impedance spectra of lithium-ion symmetric cells at low temperatures allows for unambiguous separation of charge transfer impedance contributions from other cell impedance features. Electrodes from dry Li[Ni 0.5 Mn 0.3 Co 0.2 ]O 2 (NMC 532)/artificial graphite (AG) pouch cells were used to make blocking electrode configuration symmetric cells and blocking electrode full coin cells. NMC532/AG cells with 1.2M LiPF 6 in EC:DMC 3:7 (w:w) electrolyte also underwent the formation process before the electrodes were used to make non-blocking configuration symmetric and full coin cells. Through the use of temperature dependent measurements on blocking and non-blocking cells, the impedance contribution due to faradaic, charge transfer interactions can be distinguished from non-faradaic, high frequency impedance contributions. Fitting the EIS spectra allowed both the charge transfer resistances and the related capacitances to be determined for the solid electrolyte interphase layers on the negative and positive electrodes. The charge transfer resistances were strongly temperature dependent while the capacitances were not. The temperature dependence of the charge transfer resistance was used to determine the activation energies for lithium transport through the solid electrolyte interphase layers on the negative and positive electrodes. Surprisingly, the activation energies were approximately 0.6 eV for both positive and negative electrodes extracted from cells after formation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".