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Record W4313364901 · doi:10.1149/1945-7111/acaf44

Identification of Redox Shuttle Generated in LFP/Graphite and NMC811/Graphite Cells

2022· article· en· W4313364901 on OpenAlexaff
Sebastian Buechele, Anu Adamson, Ahmed Eldesoky, Tom Boetticher, Louis Hartmann, Thomas Boulanger, Saad Azam, Michel B. Johnson, Tina Taskovic, E. R. Logan, Michael Metzger

Bibliographic record

VenueJournal of The Electrochemical Society · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversité de SherbrookeDalhousie University
Fundersnot available
KeywordsElectrolyteRedoxCyclic voltammetryChemistryDimethyl carbonateLithium (medication)GraphitePolyethylene terephthalateElectrochemistryInorganic chemistryChemical engineeringElectrodeMaterials scienceCatalysisOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Unwanted self-discharge of LFP/AG and NMC811/AG cells can be caused by in situ generation of a redox shuttle molecule after formation at elevated temperature with common alkyl carbonate electrolyte. This study investigates the redox shuttle generation for several electrolyte additives, e.g., vinylene carbonate and lithium difluorophosphate, by measuring the additive reduction onset potential, first cycle inefficiency and gas evolution during formation at temperatures between 25 and 70 °C. After formation, electrolyte is extracted from pouch cells for visual inspection and quantification of redox shuttle activity in coin cells by cyclic voltammetry. The redox shuttle molecule is identified by GC-MS and NMR as dimethyl terephthalate. It is generated in the absence of an effective SEI-forming additive, according to a proposed formation mechanism that requires residual water in the electrolyte, catalytic quantities of lithium methoxide generated at the negative electrode and, surprisingly, polyethylene terephthalate tape within the cell.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.223
Teacher spread0.217 · 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 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

Citations28
Published2022
Admission routes1
Has abstractyes

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