Toward Practical Application of Functional Conductive Polymer Binder for a High-Energy Lithium-Ion Battery Design
Bibliographic record
Abstract
Silicon alloys have the highest specific capacity when used as anode material for lithium-ion batteries; however, the drastic volume change inherent in their use causes formidable challenges toward achieving stable cycling performance. Large quantities of binders and conductive additives are typically necessary to maintain good cell performance. In this report, only 2% (by weight) functional conductive polymer binder without any conductive additives was successfully used with a micron-size silicon monoxide (SiO) anode material, demonstrating stable and high gravimetric capacity (>1000 mAh/g) for ∼500 cycles and more than 90% capacity retention. Prelithiation of this anode using stabilized lithium metal powder (SLMP) improves the first cycle Coulombic efficiency of a SiO/NMC full cell from ∼48% to ∼90%. The combination enables good capacity retention of more than 80% after 100 cycles at C/3 in a lithium-ion full cell.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".