Morphology-Tuned Porous Lithium-Rich Cathode Materials Synthesized via a Solvothermal Approach for Li-Ion Battery Application
Bibliographic record
Abstract
Lithium-rich manganese-based layered oxides (LMR) are considered one of the most promising cathode materials for the next generation of high-energy lithium-ion batteries for transportation and energy storage applications. However, the irreversible phase transition from a layered to a spinel structure coupled with the anion redox reaction leads to severe capacity degradation and voltage attenuation, hindering practical applications of LMR materials. In this work, we developed a superior LMR cathode material through a structure engineering strategy via a multisolvent solvothermal method. The resultant LMR cathode, with uniform particle size and porous structure, achieved a specific energy density of ∼933.00 Wh kg –1 (∼267.48 mAh g –1 ) at 0.2C and a capacity retention of ∼80% after 300 cycles in a voltage range of 2.0–4.8 V at 1C. We further revealed that the excellent performance of our LMR cathode is due to the abundant diffusion pathways, faster lithium-ion diffusion kinetics, and stable crystalline structure. Thus, this study is encouraging and provides an avenue for developing high-energy lithium-ion batteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".