Alternating Silicon and Carbon Multilayer-Structured Anodes Suppress Formation of the c-Li<sub>3.75</sub>Si Phase
Bibliographic record
Abstract
Silicon-based anodes for Li-ion batteries have been gaining a great deal of attention due to their high theoretical gravimetric energy density. Approaches for overcoming the challenge of pulverization associated with Si-based electrodes are required for efficient, reversible, and stable operation of such high energy batteries. This study focuses on addressing the source of pulverization of amorphous silicon films upon cycling, which is typically attributed to the formation of the c-Li 3.75 Si phase. Cross-sectional samples prepared by focused-ion beam milling revealed fractured sponge-like silicon structures after 150 cycles at a lithiation cutoff voltage of 5 mV Li, at which the c-Li 3.75 Si phase forms. Cycling at a higher lithiation cutoff voltage, 50 mV Li, however, resulted in a film with a higher degree of integrity, along with the absence of the c-Li 3.75 Si phase. These results clearly verify and underscore the deleterious effects of the c-Li 3.75 Si phase. Alternating carbon and silicon layers results in suppression of the formation of the c-Li 3.75 Si phase to a degree dependent upon the relative thicknesses of both the silicon and carbon layers. Best results were observed for multilayers of 8 nm Si/4 nm C, with which no evidence for the c-Li 3.75 Si phase up to 149 cycles was observed. Carbon interlayers were also found to beneficially lower the relative irreversible capacity loss due to solid-electrolyte interphase formation and associated electrical disconnection.
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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".