The Improved Electrochemistry of Single-Phase Layered Li-Mn-Ni-O Materials over That of Layered-Layered Nano-Composites
Notice bibliographique
Résumé
The Li-Mn-Ni-O system has received much attention for potential positive electrode materials in lithium ion batteries. In recent work [1-4], the entire phase diagram has been mapped out. Using the phase diagram as a guide, it is possible to select compositions near the boundary of the layered region. These materials can either be single phase layered if prepared by quenching from high temperature or layered-layered nano-composites if cooled more slowly. Work presented here will compare the electrochemistry of materials made under various synthesis conditions at such compositions. Here, two compositions near LiNi0.5Mn0.5O2are studied under various oxygen partial pressures and cooling rates. Figure 1 (top) shows the phase diagram with the two compositions studied, A and B (B is slightly lithium rich compared to A). XRD patterns and peak width analysis will be used to show that the materials made at B are single-phase while the only material made at A that was single-phase was made in 2% oxygen and quenched. The samples made in air showed peak broadening attributed to phase separation and the non-quenched sample in 2% oxygen showed the smallest signs of phase separation (high angle peak broadening only). Figure 1 (bottom) shows that the capacities of the single-phase materials are all higher than those that show phase separation and the cycling stability is comparable. The poor performance of the layered-layered composites is attributed to the compositions of the two phases: they are not Li2MnO3 and LiNi0.5Mn0.5O2 as promoted in the literature [5]. Instead, the end-members both contain some nickel and one contains a high proportion of nickel on the lithium layer (as high as 30% depending on synthesis conditions). Interestingly, the sample that showed the smallest sign of phase separation in the XRD (2% O2, RC) had the largest drop in capacity (140 to 100 mAh/g) compared to the quenched sample. The dramatic decrease in capacity in the sample showing the first signs of forming a layered-layered nano-composite suggests that layered-layered nano-composities should be avoided in the Li-Mn-Ni-O system. The approach often used in research experiments of adding a small amount of excess lithium then serves to help keep the material single phase which improves the electrochemistry. Figure 1: Top: a partial Li-Mn-Ni-O phase diagram showing how the upper layered boundary moves with temperature, synthesis condition (Q is quench, RC is regular cooling at a rate of 5°C/min) and atmosphere (air versus 2% O2). For all conditions, the lower layered boundary is the curved solid line joining Li2MnO3 to LiNiO2. The red lines indicate the a lattice parameter contour plots (the corresponding cones will be shown also) while the blue dotted line is a rocksalt to layered phase transition. Bottom: capacity vs. cycle number for materials made at compositions A and B in the top panel. References: [1] E. McCalla and J.R. Dahn, Solid State Ionics 242, 1 (2013). [2] E. McCalla, A.W. Rowe, R. Shunmugasundaram, and J.R. Dahn, Chem. Mater. 25, 989 (2013). [3] E. McCalla, A.W. Rowe, C.R. Brown, L.R.P. Hacquebard and J.R. Dahn, J. Electrochem. Soc. 160, A1134 (2013). [4] E. McCalla, A.W. Rowe, J. Camardese and J.R. Dahn, Chem. Mater. 25, 2716 (2013). [5] M. M. Thackeray, C. S. Johnson, J. T. Vaughey and S. A. Hackney, J. Mater. Chem. 15, 2257 (2005).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».