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Record W4298326530 · doi:10.1002/anie.202211626

Surface Degradation of Single‐crystalline Ni‐rich Cathode and Regulation Mechanism by Atomic Layer Deposition in Solid‐State Lithium Batteries

2022· article· en· W4298326530 on OpenAlexaff
Huijuan Guo, Yipeng Sun, Yang Zhao, Gui‐Xian Liu, Yuexian Song, Jing Wan, Kecheng Jiang, Yu‐Guo Guo, Xueliang Sun, Rui Wen

Bibliographic record

VenueAngewandte Chemie International Edition · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsWestern University
FundersNational Key Research and Development Program of China
KeywordsLithium (medication)Materials scienceAtomic layer depositionDegradation (telecommunications)ElectrolyteCathodeAmorphous solidChemical engineeringLayer (electronics)Deposition (geology)Surface layerBattery (electricity)NanotechnologyChemistryCrystallographyElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Single‐crystalline Ni‐rich cathode (SC‐NCM) has attracted increasing interest owing to its greater capacity retention in advanced solid‐state lithium batteries (SSLBs), while suffers from severe interfacial instability during cycling. Here, via atomic layer deposition, Li 3 PO 4 is introduced to coat SC‐NCM (L‐NCM), to suppress undesired side reaction and enhance interfacial stability. The dynamic degradation and surface regulation of SC‐NCM are investigated inside a working SSLB by in situ atomic force microscopy (AFM). We directly observe the uneven cathode electrolyte interphase (CEI) and surface defects on pristine SC‐NCM particle. Remarkably, the formed amorphous LiF‐rich CEI on L‐NCM maintains its initial structure upon cycling, and thus endows the battery with improved cycling stability and excellent rate capability. Such on‐site tracking provides deep insights into surface mechanism and structure–reactivity correlation of SC‐NCM, and thus benefits the optimizations of SSLBs.

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)0.0000.000

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 head0.013
GPT teacher head0.241
Teacher spread0.227 · 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

Citations66
Published2022
Admission routes1
Has abstractyes

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