How Phase Transformations during Cooling Affect Li-Mn-Ni-O Positive Electrodes in Lithium Ion Batteries
Bibliographic record
Abstract
The Li-Mn-Ni-O system has received much attention for potential positive electrode materials in lithium ion batteries. This article is an executive summary of a large project that used combinatorial samples synthesized at over 500 compositions to determine the entire Li-Mn-Ni-O and Li-Co-Mn-O pseudo-ternary systems under various synthesis conditions. During slow cooling, the boundaries of the single phase layered region in the Li-Mn-Ni-O system move significantly making the solid-solution area smaller, while the complex co-existence region, made up of two 3-phase regions, transforms dramatically. The impact of these phase transformations on battery performance is presented here for the first time. The electrochemical data for three new materials present in the co-existence region demonstrates why efforts to design a spinel-layered composite electrode have been so difficult. Furthermore, the layered region is considerably larger than previously discussed in the literature implying that a portion of the region remains unexplored. Additionally, matching published lattice parameters with contour plots obtained from the combinatorial studies shows that the common practice of using excess lithium during synthesis may result in single phase compounds with more lithium than the target stoichiometry, which helps explain the large variation in electrochemical performance seen in the literature. This study is therefore a significant contribution toward a complete understanding of how synthesis conditions affect Li-Mn-Ni-O structures and their electrochemistry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".