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Record W3117594143 · doi:10.1149/ma2020-024669mtgabs

Designing +/+ and -/- Symmetric Cells with Matching Full Cell Voltage As a Method to Simplify the Study of Cell Degradation

2020· article· en· W3117594143 on OpenAlexaff
Yulong Liu, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrodeElectrolyteDegradation (telecommunications)VoltageElectrochemistryComputer scienceLithium (medication)IonOptoelectronicsMaterials scienceElectrical engineeringAnalytical Chemistry (journal)ChemistryEngineeringChromatographyTelecommunications

Abstract

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A lithium-ion cell is a complex electrochemical system with many degradation modes. To further improve the energy density and longevity of lithium-ion cells, various degradation modes have to be first understood before solutions can be devised and applied. To simplify the study of cell degradation, many devices and methods have been proposed1–3. Though these devices and methods are able to simplify degradation studies to some extent, the major drawback is the limited accessibility to many other researchers and scientist, not to mention industrial R&D enterprises. Symmetric cells create an environment where only the positive electrode or only the negative electrode exists. In such an environment, the cell performance is only dictated by one type of electrode and its interaction with the electrolyte, which allows a significant simplification of the study of electrode and electrolyte of interest. In previous symmetric cell studies4,5, the operating voltage of symmetric cells was more or less arbitrarily chosen, that is, the operating voltage of each electrode vs. Li/Li+ in a symmetric cell (electrode voltage) was not purposely designed, but instead, was determined using dVdQ analysis4-6 after symmetric cells were made and cycled. However, it is much more desirable to think the opposite: having the electrode voltage of interest, at what voltage should a symmetric cell shall operate before cells are made and cycled. Knowing this allows a better control of experiments and avoids obtaining the desired electrode voltage by time-consuming trial and error on symmetric cell building and the following dVdQ analysis. More importantly, carefully-designed symmetric cells with electrode voltages of interest facilitate the study of full cell degradation by “deconvolution” of full cell performance into +/+ and -/- symmetric cells with matching voltage ranges, allowing cell degradation to be studied separately and electrodes interactions unraveled. In this presentation, a detailed introduction of designing symmetric cells with desired electrode voltage vs. Li/Li+ that matches a full cell voltage profile will be discussed. Coated and uncoated single crystal NMC532 +/+ symmetric cells and graphite -/- symmetric cells were cycled together with the corresponding full cells. Using this method, two additives, vinylene carbonate (VC) and lithium difluorophosphate (LFO), were chosen to study their effect on positive and negative electrodes. It was found that +/+ cells degrade faster than -/- cells and full cells regardless of electrolyte and the presence of cathode coating. Symmetric cell results show that VC helps more on graphite by forming stable SEI whereas LFO helps more on the positive electrode but not much on graphite. More results will be discussed in the conference. References R. Sahore, F. Dogan, and I. D. Bloom, Chem. Mater., 31, 2884–2891 (2019). C. Bolli, A. Guéguen, M. A. Mendez, and E. J. Berg, Chem. Mater., 31, 1258–1267 (2019). B. Aktekin et al., J. Phys. Chem. C, 122, 11234–11248 (2018). C. Shen et al., J. Electrochem. Soc., 164, A3349–A3356 (2017) P. Ping, Q. S. Wang, J. H. Sun, X. Xia, and J. R. Dahn, J. Electrochem. Soc., 159, A1467–A1473 (2012) H. M. Dahn, A. J. Smith, J. C. Burns, D. A. Stevens, and J. R. Dahn, J. Electrochem. Soc., 159, 0–4 (2012). Figure 1

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.018
GPT teacher head0.253
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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