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Record W4391662518 · doi:10.1149/ma2023-022433mtgabs

Can One Project Cell Lifetime Using Wide Temperature Range Ultra-High Precision Coulometry?

2023· article· en· W4391662518 on OpenAlexaff
Kenneth Tuul, Tina Taskovic, Jessie Harlow, Michel B. Johnson, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCoulometryRange (aeronautics)Nuclear engineeringMaterials scienceComputer scienceChemistryEngineeringElectrochemistry

Abstract

fetched live from OpenAlex

Using low charge voltage with Li-ion cells significantly extends their lifetime. This makes them advantageous in enabling the implementation of Li-ion batteries for widespread renewable energy storage 1 . Li[Ni 0.83 Mn 0.06 Co 0.11 ]O 2 /graphite (Ni83/graphite) cells combined with dimethyl-2,5-dioxahexane carboxylate (DMOHC) as electrolyte solvent and lithium bis(fluorosulfonyl)imide (LiFSI) as salt, operating to upper cutoff voltages of 3.8 or 3.9 V, can achieve incredible capacity retention and reduce gassing while cycling at 85°C 2 . Since these cells have exceptional lifetime projected to be decades when cycling at room temperature, there is keen interest in using high temperatures to screen cell performance in an accelerated manner 3 . However, how to project a high-temperature lifetime to room temperature remains to be determined. Ultra-high precision coulometry (UHPC) can give valuable insight into cell degradation within weeks of cycling 4 . This has been applied to Ni83/graphite cells using a blend of DMOHC and diethyl carbonate (DEC) as electrolyte solvent, LiFSI as salt, and vinylene carbonate (VC) and ethylene sulfate (DTD) as additives. Figure 1 shows the results of UHPC measurements on a series of cells over a wide temperature range between 20-100°C to help determine pathways to project cell lifetime under normal use conditions. The results present exceptional performance at high temperatures and indicate a clear relation between degradation mechanisms and temperature. Remarkably, they also demonstrate similar capacity fade rates when the cycling temperature is increased from 55°C to 100°C. The potential causes of this are further elucidated by post-mortem electrolyte analysis of the measured cells. REFERENCES C. P. Aiken, T. Taskovic, and J. R. Dahn, J. Electrochem. Soc. , 169 , 090523 (2022). T. Taskovic, A. Eldesoky, C. P. Aiken, and J. R. Dahn, J. Electrochem. Soc. , 169 , 100547 (2022). T. Taskovic, A. Eldesoky, W. Song, M. Bauer, and J. R. Dahn, J. Electrochem. Soc. , 169 , 040538 (2022). A. J. Smith, J. C. Burns, D. Xiong, and J. R. Dahn, J. Electrochem. Soc. , 158 , A1136–A1142 (2011). Figure 1 . Fractional capacity fade per hour (a), fractional charge endpoint slippage per hour (b), and coulombic inefficiency (CIE) per hour (c) of Ni83/graphite cells with 1 M LiFSI in DMOHC:DEC (20:80 w/w) with 2 wt% VC and 1 wt% DTD calculated at cycle 19 of UHPC cycling at different temperatures. Notice that the y-axis is logarithmic. Figure 1

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)0.001
metaresearch head score (Gemma)0.001
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 score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.020
GPT teacher head0.261
Teacher spread0.242 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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