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Record W2261179171 · doi:10.1149/ma2014-04/2/369

Single-Phase Layered Compositions in the Li-Mn-Ni-O System Which Do Not Significantly Oxidize Electrolyte at 4.6 V Versus Li/Li<sup>+</sup>

2014· article· en· W2261179171 on OpenAlexaff
Aaron Rowe, John Camardese, Eric McCalla, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrolytePhase diagramAnalytical Chemistry (journal)Phase (matter)OxideMaterials scienceChemistryElectrodePhysical chemistryMetallurgy

Abstract

fetched live from OpenAlex

Detailed phase diagrams of the Li-Mn-Ni-O system have been determined to provide a broader understanding of how synthesis conditions affect the phase composition of Li-Mn-Ni-O positive electrode materials.1,2 Figure 1 shows the positive electrode region of the Li-Mn-Ni-O pseudoternary phase diagram for samples quenched from 900oC. The phase diagram is labeled with various individual compositions, single-phase regions, tie-lines, and multi-phase co-existence regions all elucidated through extensive crystallographic analysis,3 introducing many opportunities for characterization of new positive electrode materials. In order to develop Li-ion batteries with high energy densities and long cycle lives, ideal novel materials would not react with carbonate-based electrolytes at high potentials (≥ 4.6 V vs. Li/Li+). In this study, three single-phase layered compositions in the Li-Mn-Ni-O system, labeled as A, B and C in Figure 1, were studied by ICP-OES, XRD, and ultra high precision coulometry (UHPC), a technique which uses precise measurement of coulombic efficiency (CE) and charge endpoint capacity slippage to detect electrolyte oxidation. Sample A was determined to be Li[Li0.157Ni0.122Mn0.650□0.071]O2, a Li-deficient, Mn-rich material containing 3.5% metal site vacancies.4 Sample B was Li[Li0.117Ni0.325Mn0.558]O2, an essentially Ni-rich member of the Li-rich oxide solid solution series (dashed orange line in Figure 1), while sample C was determined to be Li[Li0.148Ni0.480Mn0.471]O2, an approximate Li-rich analogue of Li[Ni0.5Mn0.5]O2. Figure 2 shows the CE, discharge capacity, and normalized charge endpoint capacity for cycle 10 onwards for samples A, B, and C cycled to 4.6 V and 4.8 V, and for Li[Ni1/3Mn1/3Co1/3]O2 cycled to 4.2 V, 4.4 V, and 4.6 V. In general, cycling to 4.6 V yielded better CE and lower slippage of the Li-Mn-Ni-O materials compared to cycling to 4.8 V, which produced more slippage due to electrolyte oxidation. The performance of the Li-deficient Li[Li0.157Ni0.122Mn0.650□0.071]O2 material cycled to 4.6 V was striking, as it maintained a substantially higher CE and a lower charge endpoint capacity slippage per cycle than Li[Li0.117Ni0.325Mn0.558]O2, Li[Li0.148Ni0.480Mn0.471]O2, and industry standard Li[Ni1/3Mn1/3Co1/3]O2 (cycled to only 4.2 V) while maintaining a reversible capacity of 225 mAh/g after 50 cycles. These results highlight the inherent “inertness” of Li[Li0.157Ni0.122Mn0.650□0.071]O2 and its suitability as a thin protective shell in a core-shell particle configuration. References 1. E. McCalla, A. W. Rowe, R. Shunmugasundaram, and J. R. Dahn, Chem. Mater., 25, 989–999 (2013). 2. E. McCalla, A. W. Rowe, C. R. Brown, L. R. P. Hacquebard, and J. R. Dahn, J. Electrochem. Soc., 160, A1134–A1138 (2013). 3. E. McCalla and J. R. Dahn, Solid State Ion., 242, 1–9 (2013). 4. E. McCalla, A. W. Rowe, J. Camardese, and J. R. Dahn, Chem. Mater., 25, 2716–2721 (2013).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.250
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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