In Situ XRD Studies During Synthesis of Single-Crystal LiNiO<sub>2</sub>, LiNi<sub>0.975</sub>Mg<sub>0.025</sub>O<sub>2</sub>, and LiNi<sub>0.95</sub>Al<sub>0.05</sub>O<sub>2</sub> Cathode Materials
Bibliographic record
Abstract
High-nickel, cobalt-free, single-crystal positive electrode materials could provide the ultimate intersection of high-specific capacity, low cost, and long-lifetime in lithium-ion batteries. In this work, the synthesis of LiNiO2, LiNi0.975Mg0.025O2, and LiNi0.95Al0.05O2 is studied by dynamic XRD during heating, in order to guide improvements in synthesis procedures. A comparison of Li2CO3 and LiOH·H2O lithium sources shows that either can be used to prepare these materials, but Li2CO3 requires a higher temperature. Mg doping is shown to be beneficial in lowering the temperature required to get fully lithiated, crystalline material. Additional experiments show that synthesis with a 480 °C preheat step, or synthesis directly from individual metal hydroxides (without a precursor), could be used as potentially viable alternative synthesis methods.
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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 | 0.000 |
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".