Accelerated Development of High Voltage Li‐Ion Cathodes
Bibliographic record
Abstract
Abstract High voltage cathodes are attractive for high energy density Li‐ion batteries. However, candidates such as LiCoPO4 have presented numerous challenges stemming from poor electronic/ionic conductivities such that typical solutions involving nanosizing result in extremely poor cycling performance. Here, high‐throughput methods are applied to develop near‐micron sized carbon‐coated LiCoPO4 with improved energy density and capacity retention. In total, 1300 materials with 46 different substituents are synthesized and characterized. A number of substituents show greatly improved capacity (e.g., 160 mAh g−1 for 1% indium (In) substitution vs 95 mAh g−1 for the pristine). However, co‐doping is required to improve extended cycling. Li1–3xCo1–2xInxMoxPO4 is found to be particularly effective with dramatically improved cycling (as high as 100% after 10 cycles, vs ≈50% in unsubstituted). While In improves the electronic conductivity of the carbon‐coated materials, molybdenum (Mo) co‐doping gives larger particles. DFT calculations show that Mo impedes the formation of Li/Co antisite defects.
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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) | 0.002 | 0.001 |
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".