Synthesis and Performance of Disordered Positive Electrode Materials for Lithium Ion Batteries
Bibliographic record
Abstract
Disordered rocksalt materials of the form Li1+xMy(1-x)N(1-y)(1-x)O2have been largely overlooked as a potential candidate for high performance positive electrode materials in lithium ion batteries due to the inability of lithium to percolate through the disordered structure. Recent works [1, 2] have shown these materials are able to form percolation networks if sufficient lithium and cation mixing is present in the structure. As these materials become more lithium rich, the probability of finding a network of favourable Li channels increases. However, for many transition metal choices for M and N the available redox capacity decreases. This must be considered in order to design compositions for optimal performance. This work explores these recent theories and looks to improve the design and understanding of disordered materials. Many elemental combination series are synthesized between x = 0.00 to 0.33 in Li1+xMy(1-x)N(1-y)(1-x)O2 using solid state synthesis methods with varying temperature and excess Li content to explore the role of synthesis in disordering. Choices for M and N include V, Ti, Mn, Fe, Mo, and Cr in order to investigate capacity relationships due to available redox and Li channels. Materials are characterized by X-Ray Diffraction (XRD), in-situ and ex-situ XRD, scanning electron microscopy, Mossbauer spectroscopy, induced coupled plasma optical emission spectroscopy and electrochemical testing. The structural and electrochemical data is compared with theoretical models based on available redox capacity and percolation theory. Figure 1 shows that synthesis temperature plays an important role in the disordering process. Figure 2 demonstrates a series of Li1+xTiy(1-x)Fe(1-y)(1-x)O2 (0.00 ≤ x ≤ 0.25) heated at 800 °C. Electrochemical results were found to agree with current and proposed theories of disordered materials. Discussion will include the importance of synthesis in disordered materials, as well as the performance of select series and how they compare to theoretical models. References: 1. A. Urban, J. Lee, G. Ceder, Adv. Energy Mater., 4 1400478 (2014) 2. J. Lee, A. Urban, X. Li, D. Su, G. Hautier, G. Ceder, Science, 343 519-522 (2014) Figure 1
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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".