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Record W4309818349 · doi:10.1149/ma2022-0272616mtgabs

(Digital Presentation) Particle Size and Transition-Metal Chemistry Determine the Impact of Li-Excess on Disordered Rock-Salt Li-Ion Cathode Materials

2022· article· en· W4309818349 on OpenAlexaff
Jinhyuk Lee

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsCathodeRedoxIonMaterials scienceParticle sizeDiffusionParticle (ecology)ChemistryInorganic chemistryThermodynamicsPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

The development of Co-free Li-excess disordered rock-salt (DRX) cathodes (e.g., Li1.2Mn0.4Ti0.4O2) for Li-ion batteries and interpretation through the percolation theory of Li diffusion have directed researchers to consider “Li-excess” (x > 1.1 in Li x TM 2-x O 2 ; TM = transition metal) as being essential to achieving high performance [1]. While the percolation theory provided an important insight into Li-transport in DRX materials, it leaves a critical impression that those DRXs without Li-excess will not deliver high capacity and thus are unsuitable as Li-ion cathode materials. However, the majority of DRX materials are made into pulverized nanoparticles whose small particle sizes (diameter < 150 nm) should render Li transport easy to achieve even with slow intrinsic Li diffusivity, making us question if Li-excess is necessary for designing DRX cathodes [2]. Moreover, the introduction of Li-excess requires a high degree of oxygen redox (along with TM-redox) in the materials to store electrons during cycling, leading to various O-redox-related side reactions (e.g., O-loss) that trigger fast capacity/voltage loss. In this presentation, we show that Li-excess is not necessary for some DRX-cathodes demonstrated by Li1.05Mn0.90Nb0.05O2 (M90) and Li1.20Mn0.60Nb0.20O2 (M60), which both deliver high capacity (>250 mAh/g) regardless of their Li-excess level [3]. By contextualizing this finding within the broader space of DRX materials and confirming with DFT calculations, we reveal that the percolation effect is not crucial at the nanoparticle scale, which most DRX materials developed so far have assumed by having the pulverized nanoparticle morphology [2]. Instead, Li-excess is required to decrease the charging voltage of certain DRX cathodes, which otherwise would experience difficulties in charging due to their very high TM-redox potential. Our findings show the double roles of Li-excess – modifying the cathode voltage and improving Li diffusion – that must be simultaneously considered to understand the necessity of Li-excess for high-capacity DRX cathodes. [1] J. Lee & G. Ceder et al., Science 343, 519-522 (2014) [2] H. Li & J. Lee et al., Joule 6, 53-91 (2022) [3] J. Lee & J. Li et al., Adv. Energy Mater., 2100204 (2021)

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: none
Teacher disagreement score0.279
Threshold uncertainty score0.935

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2790.036

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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
Published2022
Admission routes1
Has abstractyes

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