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Record W4324132444 · doi:10.1002/ange.202300962

One‐Step Calcination Synthesis of Bulk‐Doped Surface‐Modified Ni‐Rich Cathodes with Superlattice for Long‐Cycling Li‐Ion Batteries

2023· article· en· W4324132444 on OpenAlexaff
Yongjiang Sun, Changhong Wang, Wenjin Huang, Genfu Zhao, Lingyan Duan, Qing Liu, Shimin Wang, Adam Fraser, Hong Guo, Xueliang Sun

Bibliographic record

VenueAngewandte Chemie · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsWestern University
FundersYunnan UniversityNational Natural Science Foundation of China
KeywordsMaterials scienceCalcinationCathodeElectrochemistryChemical engineeringDopingSuperlatticeBattery (electricity)NickelNanotechnologyMetallurgyElectrodeCatalysisOptoelectronicsPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Nickel‐rich (Ni≥90 %) layered cathodes are critical materials for achieving higher‐energy‐density and lower‐cost next‐generation Li‐ion batteries (LIBs). However, their bulk and interface structural instabilities significantly impair their electrochemical performance, thus hindering their widespread adoption in commercial LIBs. Exploiting Ti and Mo diffusion chemistry, we report one‐step calcination to synthesize bulk‐to‐surface modified LiNi 0.9 Co 0.09 Mo 0.01 O 2 (NCMo90) featuring a 5 nm Li 2 TiO 3 coating on the surface, a Mo‐rich Li + /Ni 2+ superlattice at the sub‐surface, and Ti‐doping in the bulk. Such a multi‐functional structure effectively maintains its structural integrity upon cycling. As a result, such NCMo90 exhibits a high initial capacity of 221 mAh g −1 at 0.1 C, excellent rate performance (184 mAh g −1 at 5 C), and high capacity retention of 94.0 % after 500 cycles. This work opens a new avenue to developing industry‐applicable Ni‐rich cathodes for next‐generation LIBs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.034
GPT teacher head0.268
Teacher spread0.234 · 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 teacher head, 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

Citations35
Published2023
Admission routes1
Has abstractyes

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