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Record W4324131805 · doi:10.1002/ange.202217476

Suppressing Universal Cathode Crossover in High‐Energy Lithium Metal Batteries via a Versatile Interlayer Design**

2023· article· en· W4324131805 on OpenAlexfundno aff
Chuyi Xie, Chen Zhao, Heonjae Jeong, Tianyi Li, Luxi Li, Wenqian Xu, Zhenzhen Yang, Cong Lin, Qiang Liu, Lei Cheng, Xingkang Huang, Gui‐Liang Xu, Khalil Amine, Guohua Chen

Bibliographic record

VenueAngewandte Chemie · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersArgonne National LaboratoryBasic Energy SciencesBasic and Applied Basic Research Foundation of Guangdong ProvinceShenzhen Science and Technology Innovation ProgramOffice of ScienceGuangdong Science and Technology DepartmentUniversity of ChicagoCanada Excellence Research Chairs, Government of CanadaU.S. Department of Energy
KeywordsCathodeX-ray photoelectron spectroscopyElectrolyteMaterials scienceChemical engineeringLithium (medication)NanotechnologyElectrodeChemistry

Abstract

fetched live from OpenAlex

Abstract The universal cathode crossover such as chemical and oxygen has been significantly overlooked in lithium metal batteries using high‐energy cathodes which leads to severe capacity degradation and raises serious safety concerns. Herein, a versatile and thin (≈25 μm) interlayer composed of multifunctional active sites was developed to simultaneously regulate the Li deposition process and suppress the cathode crossover. The as‐induced dual‐gradient solid‐electrolyte interphase combined with abundant lithiophilic sites enable stable Li stripping/plating process even under high current density of 10 mA cm−2. Moreover, X‐ray photoelectron spectroscopy and synchrotron X‐ray experiments revealed that N‐rich framework and CoZn dual active sites can effectively mitigate the undesired cathode crossover, hence significantly minimizing Li corrosion. Therefore, assembled lithium metal cells using various high‐energy cathode materials including LiNi0.7Mn0.2Co0.1O2, Li1.2Co0.1Mn0.55Ni0.15O2, and sulfur demonstrate significantly improved cycling stability with high cathode loading.

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 score0.000
Threshold uncertainty score0.002

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 head0.021
GPT teacher head0.240
Teacher spread0.219 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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Same venueAngewandte ChemieSame topicAdvancements in Battery MaterialsFrench-language works237,207