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Record W2889988033 · doi:10.1149/ma2018-02/2/104

In Situ Conductive Coating Strategies for Nanocrystal-Based Li-Ion Battery Electrodes Beyond Carbonization

2018· article· en· W2889988033 on OpenAlexaffabout
George P. Demopoulos, Marianna Uceda, Majid Rasool, Hsien‐Chieh Chiu, Raynald Gauvin, Jigang Zhou, Karim Zaghib

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsHydro-QuébecCanadian Light Source (Canada)McGill University
Fundersnot available
KeywordsMaterials scienceElectrolyteElectrodeCoatingNanotechnologyAnodeBattery (electricity)Chemical engineeringLithium (medication)NanocrystalElectrochemistryGrapheneLithium-ion batteryChemistry

Abstract

fetched live from OpenAlex

One of the critical issues in Li-ion battery systems is overcoming the inherent poor electronic conductivity of the electrodes and the associated slow electrode/electrolyte interfacial electrochemical kinetics because of the formation of solid electrolyte interphase (SEI). This issue is particularly challenging when high-safety electrode materials like lithium iron phosphate (LiFePO4-LFP) and lithium titanate (Li4Ti5O12-LTO) are employed. Also inevitable material degradation occurs at such interfaces that, for example, was recently discussed in connection to 2D LTO nanocrystals (1) and the spontaneous reaction between Li2FeSiO4 (LFS) and LiPF6-based electrolyte (2). Michel Armand’s pioneering work (3) on carbon coating provides an elegant and economic strategy to overcome aforementioned issues, leading to their successful commercialization by Hydro-Québec. With the advent of different nanocrystals as active electrode materials for high energy or power applications new opportunities arise for innovative engineering the electrode/electrolyte interfaces at the nanoscale. Herein two modification processes are tailored to fabrication of 2D nano-Li4Ti5O12 as anodes and to mechanochemically-nanosized orthorhombic Li2FeSiO4 (Pmn21 LFS) as cathodes. With the goal on one hand replacing the expensive NMP-PVDF coating process and on the other hand tackling the low nominal capacity issue of LTO electrodes, we are working on an alternative sustainable fabrication method involving in situ coating of reduced graphene oxide (redGO) onto 2D nano-LTO. This process involves electrophoretic co-deposition of hydrated lithium titanate (Li2−xHx)Ti2O5·yH2O) and GO that is followed by controlled thermal conversion into redGO-LTO composite anodes. Meanwhile, the exploration of Pmn21 Li2FeSiO4 as high-capacity cathode has been impeded because of lacking suitable surface modification techniques. Traditional carbon coating at elevated temperature is not suitable here as it would induce a phase transformation of LFS from orthorhombic Pmn21 into monoclinic P21/n. Therefore, in another development we have successfully coated Pmn21 LFS with a conductive polymer via in situ polymerization at room temperature. In developing this method we discovered significant differences between LFP and LFS as substrates reflecting differences in surface redox reactivity between the orthophosphate and orthosilicate polyanionic frameworks. Thanks to this low-T non-C coating method the nanometric Pmn21 LFS cathode reveals itself as very promising high-energy density and stable cathode material. H. C. Chiu, X. Lu, J. Zhou, L. Gu, J. Reid, R. Gauvin, K. Zaghib and G. P. Demopoulos, Adv. Energy Mater., 7, 1601825 (2017). Z. Arthur, H. C. Chiu, X. Lu, N. Chen, V. Emond, K. Zaghib, D. T. Jiang and G. P. Demopoulos, ChemCommun, 52, 190 (2016). M. Armand et al., Method for synthesis of carbon-coated redox materials with controlled size, US Patent No. 2004/0033360A1, Feb. 19, 2004.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.257
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 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
Published2018
Admission routes2
Has abstractyes

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