Cathode materials with mixed phases of orthorhombic MoO<sub>3</sub> and Li<sub>0.042</sub>MoO<sub>3</sub> for lithium-ion batteries
Bibliographic record
Abstract
MoO3 is a promising cathode candidate for lithium-ion batteries and its electronic conductivity is usually improved by MoO3lithiation via reaction of MoO3 with LiCl solutions. However, this process might increase the manufacturing complexity and result in surface breakage of MoO3 cathodes. In this paper, by introducing lithium source into MoO3 synthesis, MoO3 can be lithiated through introduction of the Li0.042MoO3 phase into the MoO3 structure. XRD and ICP results indicate that the phase composition and lithium content can be regulated by changing the amount of lithium source in the reaction solutions. FESEM and specific surface area measurements show that the particle size becomes more uniform and the surface area is increased when the degree of MoO3 lithiation is higher. The lithiated MoO3 sample shows better cycling performance than that of pristine MoO3, which is mainly due to the enhanced conductivity and increased surface area of the lithiated MoO3.
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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".