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Record W2332521261 · doi:10.1149/ma2014-02/5/256

In-Situ Synthesis of High Voltage Cathode Li<sub>2</sub>FeMn<sub>3</sub>O<sub>8</sub> in Garnet Scaffold for Solid State Battery Application

2014· article· en· W2332521261 on OpenAlexaff
Jiaqi Dai, Gregory T. Hitz, Xiaogang Han, Yunhui Gong, Venkataraman Thangadurai, Eric D. Wachsman, Liangbing Hu

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsElectrolyteCathodeMaterials scienceBattery (electricity)ElectrochemistryElectrodeChemical engineeringNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Introduction The safety concern of Li-ion batteries due to the potential leakage and the flammability of the electrolyte severely hinders applications. The emergence of all-solid-state batteries, consisting of solid state electrodes and solid state ionic conductor electrolyte, will solve this safety problem because it eliminates the problematic liquid electrolytes. One key issue that needs to be addressed in constructing such a battery is the contact between electrode and electrolyte. Different from liquid electrolytes that can submerge the cathodes, it is difficult for solid state electrolyte to have a sufficient touch with electrodes. A common cathode-side fabrication method is to mix the electrolyte powder with cathode powder and electronically conductive materials, yielding a point-to-point contact. This contact configuration limits the number of effective pathways of li-ion diffusion, therefore hurts the performance of the battery. solves the aforementioned problems. Starting with precursor solutions, reactants are homogenously mixed at a molecular level, and are much easier to get into the scaffold than powders. Additionally, in-situ synthesis allows the high voltage cathode material to adhere to the surface of the electrolyte scaffold, yielding a face-to-face contact. This enlarges contact area, creating more pathways for Li-ion diffusion and improves the conductivity between the cathode and the electrolyte. Experimental Methods The high voltage cathode Li2FeMn3O8 (LFMO) is synthesized by glycine-nitrate combustion. Precursor solution containing metal nitrates and glycine with an optimized ratio is infiltrated into the porous garnet electrolyte scaffold. After drying at 300℃ combustion takes place. The pellet is subsequently annealed at 700℃ to achieve the desired LFMO phase. Finally, carbon nanotube ink is infiltrated to the scaffold to form a conductive network over the cathode. Results Fig. 1a shows a schematic of the cathode. With the conductive network and improved contact of cathode and electrolyte, it is expected to have an improved performance. As is shown in Fig. 1b, the cathode adheres to the surface of the scaffold, forming a face-to-face contact. The LFMO cathode has been tested in LFMO/Li coin cell with LiPF6/ FEC electrolyte. Fig.2 a) gives the XRD spectrum of the cathode prepared by glycine-nitride combustion method. The spectrum matches with JCPDS#48-0258, indicating a Li2FeMn3O8 phase. Fig.2 b) shows the cycling performance of the cathode. It can be seen from the voltage profile of the tested cell that LFMO has two plateaus at around 4.1V and 4.9V, with capacity being 104mAh/g.

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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