In Situ Deagglomeration of Cathode Particles in Electrode Slurries
Bibliographic record
Abstract
Synthesis of single-crystal cathode materials for lithium-ion batteries usually results in secondary particles consisting of agglomerations of single crystal primary particles. Deagglomeration is required to obtain good electrochemical performance. Here a deagglomeration method is described where the secondary cathode particles are deagglomerated in situ during the electrode slurry making process. By this in situ slurry milling (ISM) method, the electrode slurry was dispersed while single-crystal lithium nickel manganese cobalt oxide (NMC) cathode particles were simultaneously fully deagglomerated by wet milling in NMP. Compared to dry milling methods, ISM was the most efficient at deagglomerating single-crystal NMC particles while inducing the least lattice microstrain. This resulted in ISM-processed NMC having improved electrochemical performance compared to NMC processed by dry methods. These results show the importance of particle deagglomeration and maintaining low lattice strain in obtaining good cathode cycling performance and that the described ISM method is effective for producing high performance deagglomerated cathode materials.
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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 | 0.001 |
| 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".