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Record W4388941568 · doi:10.1002/adma.202302647

Precise Tailoring of Lithium‐Ion Transport for Ultralong‐Cycling Dendrite‐Free All‐Solid‐State Lithium Metal Batteries

2023· article· en· W4388941568 on OpenAlexafffund
Weihan Li, James A. Quirk, Minsi Li, Wei Xia, Lucy M. Morgan, Wen Yin, Matthew Zheng, Leighanne C. Gallington, Yang Ren, Ning Zhu, Graham King, Renfei Feng, Ruying Li, James A. Dawson, Tsun‐Kong Sham, Xueliang Sun

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanadian Light Source (Canada)Western University
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationWestern UniversityNewcastle UniversityUniversity of Saskatchewan
KeywordsMaterials scienceLithium metalLithium (medication)Solid-stateCyclingDendrite (mathematics)NanotechnologyMetalIonChemical engineeringElectrodeEngineering physicsMetallurgyAnodeOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract All‐solid‐state lithium metal batteries can address crucial challenges regarding insufficient battery cycling life and energy density. The demonstration of long‐cycling dendrite‐free all‐solid‐state lithium metal batteries requires precise tailoring of lithium‐ion transport of solid‐state electrolytes (SSEs). In this work, a proof of concept is reported for precise tailoring of lithium‐ion transport of a halide SSE, Li 3 InCl 6 , including intragranular (within grains) but also intergranular (between grains) lithium‐ion transport. Lithium‐ion migration tailoring mechanism in crystals is developed by unexpected enhanced Li, In, and Cl vacancy populations and lower energy barrier for hopping. The lithium‐ion transport tailoring mechanism between the grains is determined by the elimination of voids between grains and the formation of unexpected supersonic conducting grain boundaries, boosting the lithium dendrite suppression ability of SSE. Due to boosted lithium‐ion conduction and dendrite‐suppression ability, the all‐solid‐state lithium metal batteries coupled with Ni‐rich LiNi 0.83 Co 0.12 Mn 0.05 O 2 cathodes and lithium metal anodes demonstrate breakthroughs in electrochemical performance by achieving extremely long cycling life at a high current density of 0.5 C (2000 cycles, 93.7% capacity retention). This concept of precise tailoring of lithium‐ion transport provides a cost, time, and energy efficient solution to conquer the remaining challenges in all‐solid‐state lithium‐metal batteries for fast developing electric vehicle markets.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.278
Teacher spread0.256 · 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

Citations62
Published2023
Admission routes2
Has abstractyes

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