Enhanced Nucleation of LiCl during Lithium Battery Discharging with Carbon Nanotubes Supported Nitrogen-Rich Manganese Phthalocyanine Catalysts
Bibliographic record
Abstract
Large-size LiCl particles deposited on the carbon cathode of lithium thionyl chloride battery during discharge are mainly limited by the sluggish kinetics, decreasing the voltage platform and service life. In this work, the carbon nanotubes supported nano-sized nitrogen-rich manganese phthalocyanine composites (MnTAP/CNTs) were prepared by in situ solid phase synthesis as catalysts. The effect of reaction kinetics of the battery with/without catalysts on nucleation process of LiCl particles is investigated. After discharge, the surface of the carbon cathode with MnTAP/CNTs displays LiCl particles approximately 200 nm, which is only a fifth of the size without catalysts. Moreover, a large number of nano LiCl particles appear inside compared to the catalyst free. The fast reaction kinetics of SOCl 2 with MnTAP/CNTs is favorable for the nucleation of LiCl particles. Meanwhile, the electrolyte resistance, the surface film resistance and the charge transfer resistance of the battery are reduced to approximately 57%, and the discharge time and voltage platform are 15.6 min and 0.2 V higher than that without catalysts.
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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".