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Record W3092517104 · doi:10.1039/d0nr06082h

Nanoscale assembling of graphene oxide with electrophoretic deposition leads to superior percolation network in Li-ion electrodes: TiNb<sub>2</sub>O<sub>7</sub>/rGO composite anodes

2020· article· en· W3092517104 on OpenAlexafffund
Marianna Uceda, Hsien‐Chieh Chiu, Jigang Zhou, Raynald Gauvin, Karim Zaghib, George P. Demopoulos

Bibliographic record

VenueNanoscale · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsSaskatoon Medical ImagingUniversity of SaskatchewanCanadian Light Source (Canada)McGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrophoretic depositionMaterials scienceGrapheneOxideNanoscopic scaleElectrodeAnodeComposite numberNanotechnologyPercolation (cognitive psychology)Chemical engineeringDeposition (geology)Composite materialCoatingMetallurgy

Abstract

fetched live from OpenAlex

In this paper, electrophoretic deposition (EPD) is shown to promote nanoscale assembling of graphene oxide (GO) enabling the fabrication of highly homogeneous, robust, and capacity fade resistant composite titanium niobate (TiNb2O7, TNO)/rGO anodes upon reductive annealing. Control tests revealed that EPD is superior to conventional PVDF-based casting in maximizing the performance benefits from using reduced GO in Li-ion electrode fabrication as is the case of TNO that is plagued with conductivity and capacity fading problems. In this particular study, we show that there is a synergy developed between GO and EPD with the former (1) stabilizing the EPD suspension, (2) acting as a flexible binder net that affords mechanical integrity during the volume expansion of TNO, (3) serving as a conductive filler, and (4) contributing to Li-ion storage via pseudocapacitance. As a consequence, a superior percolation network is developed. Thus while both EPD- and PVDF- built TNO/rGO composite anodes exhibited high initial capacities (∼350 and 318 mA h g-1) at 0.5 C cycling, respectively, their cycling behaviour was quite different with the latter experiencing high internal polarization and extended degradation. Post-mortem PEEM-XANES analysis clearly demonstrated a highly homogeneous mesostructure in the case of the EPD-built TNO/rGO anode vs. a highly segregated and dis-jointed rGO and TNO component clustering in the PVDF-built electrode.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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

Citations20
Published2020
Admission routes2
Has abstractyes

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