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Record W2402023846 · doi:10.1021/acs.chemmater.5b03500

In Situ X-ray Diffraction Study of Layered Li–Ni–Mn–Co Oxides: Effect of Particle Size and Structural Stability of Core–Shell Materials

2015· article· en· W2402023846 on OpenAlexaff
Jing Li, Ramesh Shunmugasundaram, Renny Doig, J. R. Dahn

Bibliographic record

VenueChemistry of Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceDiffractionParticle sizePhase (matter)Lithium (medication)Particle (ecology)Analytical Chemistry (journal)X-ray crystallographyLithium oxideNickelElectrochemistryChemical engineeringChemistryElectrodeMetallurgyOpticsPhysicsPhysical chemistryChromatography

Abstract

fetched live from OpenAlex

Lithium-rich Li[Li x M 1– x ]O 2 (M = Ni, Mn, Co) materials have been claimed to be two phase by some researchers and to be one phase by others when all the available lithium is extracted electrochemically. To clear up this confusion, the Li-rich samples [Li[Li 0.12 (Ni 0.5 Mn 0.5 ) 0.88 ]O 2 and Li[Li 0.23 (Ni 0.2 Mn 0.8 ) 0.77 ]O 2 with different particle sizes were synthesized for in situ X-ray diffraction experiments. In situ X-ray diffraction measurements revealed two-phase behavior of 10 μm particles and one-phase behavior for samples with submicrometer particles. The phase separation in samples with large particles agrees with literature proposals of oxygen release from a surface layer and the observation of distinct surface and bulk phases. The small particle samples are so small that they are entirely composed of the surface phase found in the large particle samples. These results strongly suggest that the size of particles can significantly affect the structural evolution testing and electrochemical performance of the Li- and Mn-rich materials. It is proposed that the surface phase continuously grows during charge–discharge cycling, which leads to voltage fade in large particle samples. Meanwhile, in situ X-ray diffraction measurements were also performed for the layered Li–Ni–Mn–Co oxides with varying nickel contents, including NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ), NMC442 (LiNi 0.42 Mn 0.42 Co 0.16 O 2 ), [Li[Li 0.12 (Ni 0.5 Mn 0.5 ) 0.88 ]O 2, and Li[Li 0.23 (Ni 0.2 Mn 0.8 ) 0.77 ]O 2 . Samples with higher nickel content showed much faster contraction of unit cell volume as a function of cell voltage, which suggests that the core–shell structures with a nickel-rich core (e.g., NMC811) and a Mn-rich shell (e.g., Li 1.23 Ni 0.154 Mn 0.616 O 2 ) should not crack during charge–discharge cycling.

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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".

Quick stats

Citations174
Published2015
Admission routes1
Has abstractyes

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