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Record W4391312013 · doi:10.1021/jacs.3c07343

Amorphous Oxyhalide Matters for Achieving Lithium Superionic Conduction

2024· article· en· W4391312013 on OpenAlexafffund
Shumin Zhang, Feipeng Zhao, Lo‐Yueh Chang, Yu‐Chun Chuang, Zhen Zhang, Yuanmin Zhu, Xiaoge Hao, Jiamin Fu, Jiatang Chen, Jing Luo, Minsi Li, Yingjie Gao, Yining Huang, Tsun‐Kong Sham, Meng Gu, Yuanpeng Zhang, Graham King, Xueliang Sun

Bibliographic record

VenueJournal of the American Chemical Society · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchOntario Research FoundationCanada Foundation for InnovationWestern UniversityCanada Research ChairsCanadian Light Source
KeywordsReverse Monte CarloChemistryIonic conductivityAmorphous solidHalideIonic bondingPair distribution functionElectrolyteFast ion conductorConductivityElectrochemistryChemical physicsIonInorganic chemistryPhysical chemistryCrystallographyCrystal structureElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

The recently surged halide-based solid electrolytes (SEs) are great candidates for high-performance all-solid-state batteries (ASSBs), due to their decent ionic conductivity, wide electrochemical stability window, and good compatibility with high-voltage oxide cathodes. In contrast to the crystalline phases in halide SEs, amorphous components are rarely understood but play an important role in Li-ion conduction. Here, we reveal that the presence of amorphous component is common in halide-based SEs that are prepared via mechanochemical method. The fast Li-ion migration is found to be associated with the local chemistry of the amorphous proportion. Taking Zr-based halide SEs as an example, the amorphization process can be regulated by incorporating O, resulting in the formation of corner-sharing Zr–O/Cl polyhedrons. This structural configuration has been confirmed through X-ray absorption spectroscopy, pair distribution function analyses, and Reverse Monte Carlo modeling. The unique structure significantly reduces the energy barriers for Li-ion transport. As a result, an enhanced ionic conductivity of (1.35 ± 0.07) × 10 –3 S cm –1 at 25 °C can be achieved for amorphous Li 3 ZrCl 4 O 1.5 . In addition to the improved ionic conductivity, amorphization of Zr-based halide SEs via incorporation of O leads to good mechanical deformability and promising electrochemical performance. These findings provide deep insights into the rational design of desirable halide SEs for high-performance 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 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 score0.010
Threshold uncertainty score0.266

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 head0.010
GPT teacher head0.237
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 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

Citations152
Published2024
Admission routes2
Has abstractyes

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