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Record W4282574513 · doi:10.1002/aesr.202200032

Composite Cathodes for Solid‐State Lithium Batteries: “Catholytes” the Underrated Giants

2022· article· en· W4282574513 on OpenAlex
Hilal Al-Salih, Mohamed S.E. Houache, Elena A. Baranova, Yaser Abu‐Lebdeh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Energy and Sustainability Research · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersOffice of Energy Research and DevelopmentNatural Resources Canada
KeywordsElectrolyteMaterials scienceLithium (medication)CathodeComposite numberNanotechnologyEnergy densityFabricationResistive touchscreenElectrochemistryFast ion conductorGravimetric analysisProcess engineeringElectrodeEngineering physicsElectrical engineeringComposite materialEngineeringChemistry

Abstract

fetched live from OpenAlex

To expedite the large‐scale adoption of electric vehicles (EVs), increasing the gravimetric energy density of batteries to at least 250 Wh kg −1 while sustaining a maximum cost of $120 kWh −1 is of utmost importance. Solid‐state lithium batteries are broadly accepted as promising candidates for application in the next generation of EVs as they promise safer and higher‐energy‐density batteries. Nonetheless, their development is impeded by many challenges, including the resistive electrode–electrolyte interface originating from the removal of the liquid electrolyte that normally permeates through the porous cathode and insures efficient ionic conductivity through the cell. One way to tackle this challenge is by formulating composite cathodes (CCs) that employ solid ionic conductors as “catholytes” in their structure. Herein, it is attempted to shed light on this less studied and poorly understood approach. The different classes of catholytes that have been reported in literature alongside the most common fabrication techniques used to prepare CCs are presented. Next, the interplay between the microstructure and design parameters of CCs with the electrochemical performance of solid‐state batteries (SSBs) and the techniques used to measure their transport properties is well documented. Finally, general guidelines surrounding CC research are outlined.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.028
GPT teacher head0.339
Teacher spread0.311 · 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