In Situ Imaging of Electrode Thickness Growth and Electrolyte Depletion in Single-Crystal vs Polycrystalline LiNixMnyCozO<sub>2</sub>/Graphite Pouch Cells using Multi-Scale Computed Tomography
Bibliographic record
Abstract
Single-crystal LiNixMnyCozO2 (NMC) materials have recently garnered significant academic and commercial interest as they have been shown to provide exceptional long-term charge-discharge cycling stability in Li-ion cells. Understanding the degradation mechanisms occurring in conventional polycrystalline NMC materials in comparison to the more stable single-crystal equivalents has become a topic of great importance. In this study, we demonstrate how multi-scale, in situ computed tomography can be used to characterize important changes occurring in wound pouch cells containing polycrystalline vs single-crystal NMC. These changes include cell-level phenomena (such as deformation of the jelly roll and electrolyte depletion) as well as electrode-scale phenomena (such as electrode thickness growth and electrode cracking). Twenty-one cells were scanned in total, consisting of three different electrodes: polycrystalline NMC622, single-crystal NMC811, and single-crystal NMC532. These cell matrices were designed to characterize the effects of varying C-rate, depth of discharge, and duty cycle. This work includes a comprehensive analysis of these factors as they relate to physical changes taking place at both the cell and electrode level.
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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 | 0.000 |
| 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 | 0.000 |
| 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".