Impact of Cr Doping on the Voltage Fade of Li-Rich Mn-Rich Li<sub>1.11</sub>Ni<sub>0.33</sub>Mn<sub>0.56</sub>O<sub>2</sub> and Li<sub>1.2</sub>Ni<sub>0.2</sub>Mn<sub>0.6</sub>O<sub>2</sub> Positive Electrode Materials
Bibliographic record
Abstract
Voltage fade during charge-discharge cycling in Layered Li-rich Mn-rich positive electrode materials needs to be overcome for the development of high-energy low cost Li-ion batteries. Several cation dopants have been introduced into the bulk lattice to mitigate voltage decay by limiting transition metal (TM) migration, inhibiting phase transformation, or reducing the extent of oxygen release. Here, a series of electrochemically active Cr substituted (2.5, 5.0, and 10 mol%) Co-free Li1.11Ni0.33Mn0.56O2 and Li1.2Ni0.2Mn0.6O2 compositions were synthesized via dry particle fusion followed by heat treatment with Li2CO3. Cr doping improves specific capacity and capacity retention via multiple electron transfer of Cr3+/Cr6+ as well as mitigates voltage fading to a certain extent. The impact of Cr on voltage decay was studied by careful measurements of dQ/dV vs V on Cr-doped and undoped samples before and after cycle testing.
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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".