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Record W4283072929 · doi:10.1002/aenm.202200682

Surface‐to‐Bulk Synergistic Modification of Single Crystal Cathode Enables Stable Cycling of Sulfide‐Based All‐Solid‐State Batteries at 4.4 V

2022· article· en· W4283072929 on OpenAlexafffund
Nan Sun, Yajie Song, Qingsong Liu, Wei Zhao, Fang Zhang, Liping Ren, Ming Chen, Zinan Zhou, Zihan Xu, Shuaifeng Lou, Fanpeng Kong, Jian Wang, Yujin Tong

Bibliographic record

VenueAdvanced Energy Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of ChinaCanadian Institutes of Health ResearchNational Research CouncilHeilongjiang Youth Development FoundationUniversity of SaskatchewanCanadian Light Source
KeywordsMaterials scienceSulfideSurface modificationCathodeElectrolyteElectrochemistryChemical engineeringOxidizing agentOxideCoatingNanotechnologyElectrodeMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract The interfacial stability between sulfide solid‐state electrolytes (SSEs) and high voltage Ni‐rich oxide cathodes is critical to the electrochemical performances of all‐solid‐state batteries (ASSBs), yet it is challenging to solve the interface issues by surface coating modification. Here, a surface‐to‐bulk synergistic modification is proposed to achieve a highly stable interface through the combination of TiNb 2 O 7 ‐coated and Ti‐doped LiNi 0.6 Mn 0.2 Co 0.2 O 2 single crystals (DC‐TNO@SCNCM). The TiNb 2 O 7 coating layer with thermodynamic/electrochemical stability and electronic insulation avoids the decomposition of SSEs. The strong TiO bond in SCNCM achieved by Ti doping can stabilize lattice oxygen and avoid further electrochemically oxidizing sulfide electrolytes to form oxygenated sulfurous and phosphorous species. The modified DC‐TNO@SCNCM cathode exhibits excellent long‐cycle stability with a capacity retention rate of 92.2% after 140 cycles at a high cut‐off voltage of 4.4 V. This surface‐to‐bulk synergistic modification strategy provides a new perspective for the design of high‐voltage sulfide‐based ASSBs.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.257
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.

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

Citations81
Published2022
Admission routes2
Has abstractyes

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