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Record W2419336826 · doi:10.1149/2.0951608jes

Consumption of Fluoroethylene Carbonate (FEC) on Si-C Composite Electrodes for Li-Ion Batteries

2016· article· en· W2419336826 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of The Electrochemical Society · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsnot available
FundersDalhousie University
KeywordsElectrolyteAnodeElectrochemistryChemistrySiliconPolarization (electrochemistry)ElectrodeChemical engineeringMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

The electrolyte additive fluoroethylene carbonate (FEC) is known to significantly improve the lifetime of Li-ion batteries with silicon anodes. In this work, we show that FEC can indeed improve the lifetime of silicon-carbon composite anodes but is continuously consumed during electrochemical cycling. By the use of <sup>19</sup>F-NMR spectroscopy and charge/discharge cycling we demonstrate that FEC is only capable to stabilize the cell performance as long as FEC is still remaining in the cell. Its total consumption causes a significant increase of the cell polarization leading to a rapid capacity drop. We show with On-line Electrochemical Mass Spectrometry (OEMS) that the presence of FEC in the electrolyte prohibits the reduction of other electrolyte components almost entirely. Consequently, the cumulative irreversible capacity until the rapid capacity drop correlates linearly with the specific amount of FEC (in units of μmol<sub>FEC</sub>/mg<sub>electrode</sub>) in the cell. The latter quantity therefore determines the lifetime of silicon anodes rather than the concentration of FEC in the electrolyte. By correlating the cumulative irreversible capacity and the specific amount of FEC in the cell, we present an easy tool to predict how much cumulative irreversible capacity can be tolerated until all FEC will be consumed in either half-cells or full-cells. We further demonstrate that four electrons are consumed for the reduction of one FEC molecule and that one carbon dioxide molecule is released for every FEC molecule that is reduced. Using all information from this study and combining it with previous reports in literature, a new reductive decomposition mechanism for FEC is proposed yielding CO<sub>2</sub>, LiF, Li<sub>2</sub>O, Li<sub>2</sub>CO<sub>3</sub>, H<sub>2</sub> and a partially cross-linked polymer.

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)0.000
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 score0.025
Threshold uncertainty score0.354

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 head0.010
GPT teacher head0.239
Teacher spread0.228 · 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