MétaCan
Menu
Back to cohort
Record W4395014341 · doi:10.1149/1945-7111/ad3aa9

All-Dry Synthesis of NMC from [Ni,Mn,Co]<sub>3</sub>O<sub>4</sub> Spinel Precursors

2024· article· en· W4395014341 on OpenAlexafffund
Ido Ben-Barak, M. N. Obrovac

Bibliographic record

VenueJournal of The Electrochemical Society · 2024
Typearticle
Languageen
FieldEngineering
TopicElectrical and Thermal Properties of Materials
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpinelManganeseMaterials scienceChemistryNuclear chemistryMetallurgy

Abstract

fetched live from OpenAlex

Oxides in the Ni x Mn0.5-x/2Co0.5-x/2-O system were investigated as precursors in the all-dry synthesis of NMC622 (LiNi0.6Mn0.2Co0.2O2). Single-phase spinel precursors in this system were found to have the highest compositional homogeneity. To synthesize NMC, Ni x Mn0.5-x/2Co0.5-x/2-O precursors were heated with Li2CO3 and NiO (to attain the correct NMC stoichiometry) in air or oxygen. This represents a different strategy in NMC synthesis compared to conventional hydroxide precursors that have the same composition as the final NMC. The most homogeneous and best performing NMC (171.9 mAh g−1 with 90% after 183 cycles) were obtained by using precursors that were essentially single-phase cubic spinel (0.070 ≤ x ≤ 0.091 in Ni x Mn0.5-x/2Co0.5-x/2-O) even though such precursors had compositions that had significantly less Ni content than the target NMC622 composition. These findings demonstrate an alternate route for obtaining compositional homogeneity in NMC all-dry synthesis.

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 head0.008
GPT teacher head0.198
Teacher spread0.191 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicElectrical and Thermal Properties of MaterialsFrench-language works237,207