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Record W3039268792 · doi:10.1002/aenm.202001497

Understanding the Reactivity of a Thin Li<sub>1.5</sub>Al<sub>0.5</sub>Ge<sub>1.5</sub>(PO<sub>4</sub>)<sub>3</sub> Solid‐State Electrolyte toward Metallic Lithium Anode

2020· article· en· W3039268792 on OpenAlexafffund
Andrea Paolella, Wen Zhu, Gui‐Liang Xu, Andrea La Monaca, Sylvio Savoie, Gabriel Girard, Ashok K. Vijh, Hendrix Demers, Alexis Péréa, Nicolas Delaporte, Abdelbast Guerfi, Xiang Liu, Yang Ren, Cheng‐Jun Sun, Jun Lü, Khalil Amine, Karim Zaghib

Bibliographic record

VenueAdvanced Energy Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-Québec
FundersArgonne National LaboratoryHydro-QuébecBasic Energy SciencesOffice of ScienceVehicle Technologies OfficeUniversité LavalU.S. Department of Energy
KeywordsMaterials scienceLithium (medication)Reactivity (psychology)ElectrolyteX-ray photoelectron spectroscopyFast ion conductorLithium batteryMetalMetastabilityAnalytical Chemistry (journal)Chemical engineeringPhysical chemistryElectrodeIonIonic bondingMetallurgy

Abstract

fetched live from OpenAlex

Abstract The thickness of solid‐state electrolytes (SSEs) significantly affects the energy density and safety performance of all‐solid‐state lithium batteries. However, a sufficient understanding of the reactivity toward lithium metal of ultrathin SSEs (&lt;100 µm) based on NASICON remains lacking. Herein, for the first time, a self‐standing and ultrathin (70 µm) NASICON‐type Li 1.5 Al 0.5 Ge 1.5 (PO 4 ) 3 (LAGP) electrolyte via a scalable solution process is developed, and X‐ray photoelectron spectroscopy reveals that changes in LAGP at the metastable Li–LAGP interface during battery operation is temperature dependent. Severe germanium reduction and decrease in LAGP particle size are detected at the Li–LAGP interface at elevated temperature. Oriented plating of lithium metal on its preferred (110) face occurs during in situ X‐ray diffraction cycling.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.057
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.235
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

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

Citations71
Published2020
Admission routes2
Has abstractyes

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