Ultra‐Fast Charging High‐voltage Spinel LiNi <sub>0.5</sub> Mn <sub>1.5</sub> O <sub>4</sub> Batteries Enabled by Mn─O Bond Regulating Strategy to Defeat Jahn─Teller Distortion
Bibliographic record
Abstract
Abstract The high‐voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) is a promising cathode material for lithium‐ion batteries due to its high energy and power densities, excellent thermal stability, low cost, and environmental benignity. However, the presence of Mn 3+ induces Jahn─Teller (J─T) distortion, leading to Mn─O bond elongation, lattice stress, and degradation of both structural and electrochemical stability during cycling. To address this,a bond‐length engineering strategy is proposed by co‐doping Fe at the Mn 16d sites and Sb at the vacant 16c positions to suppress the J─T effect and stabilize the crystal structure. Electron paramagnetic resonance (EPR), in situ X‐ray diffraction (XRD), and density functional theory (DFT) calculations confirm that the Mn─O bond regulation strategy effectively mitigates MnO 6 octahedral distortion, reduces phase transitions, and enhances structural robustness. Moreover, Sb incorporation expands the lattice, facilitating Li + diffusion. As a result, the optimized FeSb‐LNMO delivers remarkable electrochemical performance, retaining 98% of its initial capacity after 200 cycles at 1C, and achieving 85.6% capacity retention over 1000 cycles at 5C. This work introduces a novel bond‐length engineering approach via multi‐site doping to overcome degradation in high‐voltage LNMO, enabling ultra‐fast charging and long‐term cycling stability.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".