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Record W4242403479 · doi:10.1149/ma2019-02/5/299

Water-Dispersible Conducting Polymer Composite:a Promising Binder for Cathode of Lithium Ion Batteries

2019· article· en· W4242403479 on OpenAlexaff
At Van Nguyen, Christian Kuß

Bibliographic record

VenueECS Meeting Abstracts · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMaterials scienceCathodeAnodeComposite numberComposite materialInertChemical engineeringPolymerLithium (medication)Conductive polymerElectrodeOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Binders are a vital component in the electrode of Li-ion batteries that hold active materials and conductive additives in place. Most binder research focuses on anode binders after the introduction of ultrahigh capacity anode materials such as Si, Sn, Ti and its derivatives, which suffer from extreme volume expansion/contraction during charge/discharge cycles1. Cathode binders, on the other hand, attract less attention even though cathode materials such as layered transition-metal oxides, olivine LiFePO4, spinel LiMn2O4 are still experiencing mechanical deterioration (fracture, disintegration)2, poor electrical conductivity3, phase changes4 and side reactions that eventually lead to capacity fading over cycling. Cathode materials are currently also the most expensive material in commercial Li-ion batteries5 and contribute the highest weight. For these reasons, the development of better binders for cathodes is paramount important to reduce cost and increase specific energy of Li-ion batteries. Commercially prevalent is the PVDF/Carbon additives binder system at the cathode. This binder system offers limited adhesive forces between active materials. Besides that, the addition of electrochemically inert carbon additives to compensate the poor electrical conductivity also decreases the mass energy density of Li-ion batteries1. Moreover, volatile organic-solvents (most frequently N-methyl pyrrolidone) are involved in electrode fabrication with PVDF binder, posing a threat to the environment. In this research, a water-dispersible conducting polymer composite is introduced as a promising green binder for Li-ion intercalation cathodes. By carrying out in-situ polymerization of polypyrrole in the presence of carboxyl/hydroxyl containing polymers, the obtained polymers are electrically conductive and water-dispersible. The polypyrrole-based composite binder is designed to not only offer a continuous conductive matrix but also suppress capacity fading via intramolecular interactions. The presentation will describe our efforts in synthesizing these binders, characterizing their physical and chemical properties, and investigating their performance in Li-ion cathodes. Keywords: Conducting Polymers, Polypyrrole, Water-dispersive Binder, Li-ion batteries. References Chen, H. et al. Exploring Chemical, Mechanical, and Electrical Functionalities of Binders for Advanced Energy-Storage Devices. Chem. Rev. 118, 8936–8982 (2018). Wu, F. & Yushin, G. Conversion cathodes for rechargeable lithium and lithium-ion batteries. Energy Environ. Sci. 10, 435–459 (2017). Eliseeva, S. N., Levin, O. V, Tolstopyatova, E. G., Alekseeva, E. V & Kondratiev, V. V. Effect of addition of a conducting polymer on the properties of the LiFePO4-based cathode material for lithium-ion batteries. Russ. J. Appl. Chem. 88, 1146–1149 (2015). Zheng, J. et al. Corrosion/fragmentation of layered composite cathode and related capacity/voltage fading during cycling process. Nano Lett. 13, 3824–3830 (2013). Patry, G., Romagny, A., Martinet, S. & Froelich, D. Cost modeling of lithium-ion battery cells for automotive applications. Energy Sci. Eng. 3, 71–82 (2015).

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.029
GPT teacher head0.262
Teacher spread0.233 · 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
Published2019
Admission routes1
Has abstractyes

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