Impact of a Maturation Procedure on the Morphological Dynamics of Si-Based Anodes for Li-Ion Batteries Characterized By I n-Situ Synchrotron X-Ray Tomography
Bibliographic record
Abstract
Thanks to its theoretical capacity ten times higher than graphite (3579 mAh g -1 for Li 15 Si 4 versus 372 mAh g -1 for LiC 6 ), substituting graphite by silicon as anode material in lithium-ion batteries is an attractive way to increase their energy density. However, the huge volume expansion/contraction of silicon (up to ~300%) during its lithiation/delithiation causes major morphological changes of the electrode, which severely degrade its cyclability. In this communication, the dynamics of their expansion and contraction, of their cracking in the bulk and of their debonding at the interface with the current collector are characterized by in situ synchrotron X-ray computed tomography. Two electrodes made with micrometric silicon material are compared: one fabricated according to a standard process and the other one prepared with a maturation step, which consists in storing the electrode in a humid atmosphere for a few days before drying and cell assembly [1]. Various morphological parameters are quantified and followed during the first lithiation/delithiation of the electrode, namely (i) the dimensional change of the electrode, (ii) the volume fraction, size and connectivity of the segmented solid, gas and electrolyte phases, (iii) the volume fraction, size and connectivity of the produced macrocracks, (iv) the surface area of the produced delaminated zones from the current collector and (v) the variation of the Si inter-particle distances. All morphological degradations are significantly restrained for the matured electrode, confirming the great efficiency of this maturation step to produce a more ductile and resilient electrode architecture, which is at the origin of the major improvement in their cyclability. [1] C.R. Hernandez, A. Etiemble, T. Douillard, D. Mazouzi, Z. Karkar, E. Maire, D. Guyomard, B. Lestriez, L. Roué, Adv. Energy Mat. 2017 , 8, 1701787. Figure 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".