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Record W4285497197 · doi:10.1149/ma2022-012221mtgabs

Development of a LiMnFePO<sub>4 </sub>/ Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub> 2Ah Pouch Cell: An Example of the Effective Integration of New Materials

2022· article· en· W4285497197 on OpenAlexaff
Martin Dontigny, Alexis Péréa, Yuichiro Asakawa, Karim Zaghib, Jean‐Christophe Daigle

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMcGill UniversityHydro-Québec
Fundersnot available
KeywordsBattery (electricity)ElectrolyteMaterials scienceEnergy storageDegradation (telecommunications)PolymerCathodeZero emissionChemical engineeringEnvironmental scienceProcess engineeringNanotechnologyElectrodeElectrical engineeringChemistryComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

One of the most promising approaches for limiting climate change is the use of alternative and greener sources of energy (wind, solar, etc.). The electricity generated from these sources fluctuates, however, and a storage solution is needed. The advent of energy storage for wind farms, solar plants, etc., requires a new generation of batteries. It is therefore imperative that a battery with high energy density, a longer life cycle and improved safety be developed. In this paper, we describe our efforts to develop a safe and long-life cycle LiMnFePO4 (LMFP)/Li4Ti5O12 (LTO) 2Ah pouch cell. One of the major challenges faced in this pursuit was gas evolution during cycling. Various side reactions with active materials resulted in the generation of gas during cycling. To circumvent this, we implemented several mitigation strategies. To combat electrolyte degradation (1.0 M LiPF6 in carbonate solvents) due to Mn2+ dissolution in LMFP, we integrated a new class of polymer as a binder in the cathode preparation, which effectively decreased the degradation during cycling. This polymer also has high voltage stability.1 At the battery’s negative electrode, we developed a new carbon coating method on LTO that minimizes electrolyte degradation and optimizes high C-rate preformances, especially fast charging performances.2 Although these new materials reduce gas evolution, they do not eliminate it. Therefore, we developed the first polymer capable of trapping the carbon dioxide, major component of gases generated during cycling and, in turn, preventing pouch cell inflation. This polymer was integrated in a pouch cell in the form of an insoluble trapping sheet.3 Although relatively simple, this technology made the pouch cells safer. This unique approach is versatile and can be implemented in pouch cells with any type of chemistry when gas scavenging is required. The 2Ah pouch cells did not experience any inflation during extensive cycling and aging. Cells cycled more then 750 cycles at 45oC with a rate of 1C – 1C before reaching 80% retention capacity. Reference (1) Daigle, J.-C.; Asakawa, Y.; Zaghib, K. Polymer additives and their use in electrode materials and electrochemical cells. WO2020061710A1, 2020. (2) Daigle, J.-C.; Asakawa, Y.; Beaupre, M.; Gariepy, V.; Vieillette, R.; Laul, D.; Trudeau, M.; Zaghib, K. Boosting Ultra-Fast Charge Battery Performance: Filling Porous nanoLi4Ti5O12 Particles with 3D Network of N-doped Carbons. Sci. Rep. 2019, 9 (1), 1-9, DOI: 10.1038/s41598-019-53195-1. (3) Daigle, J.-C.; Asakawa, Y.; Perea, A.; Dontigny, M.; Zaghib, K. Novel polymer coating for chemically absorbing CO2 for safe Li-ion battery. Sci. Rep. 2020, 10 (1), 10305, DOI: 10.1038/s41598-020-67123-1.

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 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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.229
Teacher spread0.209 · 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
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
Published2022
Admission routes1
Has abstractyes

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