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Record W3088403386 · doi:10.1002/batt.202000192

Enabling High Capacity and Coulombic Efficiency for Li‐NCM811 Cells Using a Highly Concentrated Electrolyte

2020· article· en· W3088403386 on OpenAlexaff
Maria Philip, Richard T. Haasch, Jutae Kim, Jianzhong Yang, R. T. Yang, Ivan Kochetkov, Linda F. Nazar, Andrew A. Gewirth

Bibliographic record

VenueBatteries & Supercaps · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrolyteFaraday efficiencyAnodeLithium (medication)Chemical engineeringMaterials scienceConductivityThermal stabilityMetalIonic conductivityChemistryInorganic chemistryElectrodeMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Lithium metal batteries suffer from dendrite formation and the associated safety hazards of thermal runaway reactions. In this study, we report the performances of a highly concentrated electrolyte (HCE) and a dilute LiPF 6 electrolyte in lithium metal cells using LiNi 0.8 Co 0.1 Mn 0.1 O 2 . While the HCE exhibits lower bulk ionic conductivity than the dilute LiPF 6 electrolyte, the cell conductivity is higher for the HCE system, indicating higher thermodynamic stability of the electrolyte against the electrodes. Full cell cycling demonstrates higher capacity for the HCE system, which declines as a function of cycle number due to the formation of decomposition products, similar to the dilute LiPF 6 system. The origin of the enhanced performance is the higher stability of the HCE against a Li metal anode as compared to the dilute LiPF 6 electrolyte. Cycling at higher temperatures further enhances the performance of the HCE, which is more thermally stable than the dilute LiPF 6 electrolyte.

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 score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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

Citations27
Published2020
Admission routes1
Has abstractyes

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