Investigation of Transverse Relaxation Rate Distribution via Magnetic Resonance Imaging: Impact of Electrode Formation
Bibliographic record
Abstract
The impact of electrode formation is studied by the spatially and time‐resolved distribution of transverse relaxation. In situ 7Li nuclear magnetic resonance experiments are performed on an experimental lithium‐ion battery cell to study the impact of electrode passivation via imaging and transverse relaxation in the interelectrode volume. The electrolyte in the battery, using technically relevant electrode material, i.e., graphite and lithium–nickel–cobalt–manganese–oxide, is studied by 2D magnetic resonance imaging. The electrolyte is 1 mol L−1 lithium hexafluorophosphate dissolved in a binary mixture of ethylene carbonate and dimethyl carbonate. 1D profiles are acquired and related to 7Li concentration during passivation and during a constant current/constant voltage cycle. The transverse relaxation rate R2(z,t) measured by multiecho profiles revealed changes within the electrolyte volume. The ongoing process changes the relaxation distribution. Indications for a defective electrode passivation are deduced from the data. During one charging cycle with constant current/constant voltage, the lithium concentration is measured spatially resolved, and the data are modeled by the Nernst–Planck equation.
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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) | 0.001 | 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".