Reversible growth of solid electrolyte interface enhances charge capacity in cobalt sulfide-carbon nanotube anodes
Bibliographic record
Abstract
The development of high-performance anode materials for lithium-ion batteries is a critical aspect of advancing energy storage technology . This study presents a novel approach to improve the charge capacity of anodes by harnessing the reversible growth of the solid electrolyte interface (SEI). This work focuses on cobalt sulfide (Co 9 S 8 ) nanoparticles incorporated into a porous carbon nanotube (CNT) structure. Through a two-step pyrolysis process , Co 9 S 8 CNT composites, characterized by their conductive and mechanically robust CNT matrix are successfully synthesized. These Co 9 S 8 CNT anodes exhibit excellent initial charge capacity (560.5 mAh g −1 at 100 mA g −1 ) and remarkable stability, with a charge capacity of 633 mAh g −1 after 1000 cycles at 1000 mA g −1 , accompanied by a Coulombic efficiency exceeding 99 %. Notably, this investigation reveals that the growth of the SEI plays a pivotal role in enhancing the charge capacity. Through in-situ Raman spectroscopy and other analytical techniques, it is suggested that the reversible reduction of organic solvent molecules within the large polymeric SEI is responsible for the increased charge capacity. This unique phenomenon is characterized by changes in the SEI's composition, driven by the charge and discharge processes. This study is a novel attempt to report a SEI's reversible growth that results in improved charge capacity, contrasting with prior research where SEI growth typically leads to capacity loss. Understanding this stable system provides valuable insights into increasing the cycle life and charge capacity of anodes, not only for transition metal sulfides but also for broader applications in energy storage.
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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".