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Record W3039497964 · doi:10.1002/adma.202002550

Temperature‐Dependent Chemical and Physical Microstructure of Li Metal Anodes Revealed through Synchrotron‐Based Imaging Techniques

2020· article· en· W3039497964 on OpenAlexafffund
Keegan R. Adair, Mohammad Norouzi Banis, Yang Zhao, Toby Bond, Ruying Li, Xueliang Sun

Bibliographic record

VenueAdvanced Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanadian Light Source (Canada)Western University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Saskatchewan
KeywordsMaterials scienceAnodeElectrolyteElectrochemistrySynchrotronCharacterization (materials science)MicrostructureMetalFaraday efficiencyElectrodeChemical engineeringAlloyAnalytical Chemistry (journal)NanotechnologyMetallurgyPhysical chemistryOpticsChemistry

Abstract

fetched live from OpenAlex

) and low electrochemical potential (-3.04 V vs the standard hydrogen electrode). Nevertheless, the behavior of Li metal in different environments has been scarcely reported. Herein, the temperature-dependent behavior of Li metal anodes in carbonate electrolyte from the micro- to macroscales are explored with advanced synchrotron-based characterization techniques such as X-ray computed tomography and energy-dependent X-ray fluorescence mapping. The importance of testing methodology is exemplified, and the electrochemical behavior and failure modes of Li anodes cycled at different temperatures are discussed. Moreover, the origin of cycling performance at different temperatures is identified through analysis of Coulombic efficiencies, surface morphology, and the chemical composition of the solid electrolyte interphase in quasi-3D space with energy-dependent X-ray fluorescence mappings coupled with micro-X-ray absorption near edge structure. This work provides new characterization methods for Li metal anodes and serves as an important basis toward the understanding of their electrochemical behavior in carbonate electrolytes at different temperatures.

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)
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 score0.030
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)0.0000.000

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations74
Published2020
Admission routes2
Has abstractyes

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