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Record W4404873519 · doi:10.1016/j.nanoen.2024.110531

Fast-charging all-solid-state battery cathodes with long cycle life

2024· article· en· W4404873519 on OpenAlexaff
Christopher Doerrer, Xiangwen Gao, Junfu Bu, Samuel Wheeler, Mauro Pasta, Peter G. Bruce, Patrick S. Grant

Bibliographic record

VenueNano Energy · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersEngineering and Physical Sciences Research CouncilFaraday InstitutionHenry Royce Institute
KeywordsMaterials scienceBattery (electricity)CathodeSolid-stateEngineering physicsNanotechnologyElectrical engineeringPower (physics)ThermodynamicsEngineering

Abstract

fetched live from OpenAlex

Many battery applications target fast charging to achieve an 80 % rise in state of charge (SOC) in < 15 min. However, in the case of all-solid-state batteries (SSBs), they typically take several hours to reach 80 % SOC while retaining a high specific energy of 400 W h k g cell − 1 . We specify design strategies for fast-charging SSB cathodes with long cycle life and investigate the fast-charging capability of a sulfide-based single crystal Li-Ni-Mn-Co oxide composite cathode. At 30 °C and charging at 15 mA cm − 2 , a specific capacity of 150 mA h g − 1 was achieved in ∼ 8 min, with 81 % capacity retention after 3000 cycles. Critically, a 3-electrode arrangement was used to avoid the common problem of overcharging at high current densities. By following the design strategy and optimized manufacturing, a 210 µm thick cathode was able to be charged at an extraordinary current density of 50 mA cm − 2 to reach an areal capacity of 8 mA h cm − 2 in only 10 min, suggesting practical cathodes for SSBs with 400 W h k g cell − 1 may be within reach. • Fast charging at 15 mA cm −2 and room temperature demonstrated in composite cathodes. • 80 % increase in state of charge in < 10 min revealed by a 3-electrode arrangement. • 81 % capacity retention after 3000 fast-charge cycles. • Design guidelines for fast-charging all-solid-state battery cathodes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.888

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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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 designSimulation or modeling
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

Citations9
Published2024
Admission routes1
Has abstractyes

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