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Record W2344833930 · doi:10.1149/ma2016-03/2/1008

Control of Lattice Orientation and Interface of LiCoO<sub>2</sub> for All Solid State Batteries

2016· article· en· W2344833930 on OpenAlexaff
Andy Xueliang Sun, Yulong Liu, Qian Sun, Mohammad Norouzi Banis, Ruying Li

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceElectrolyteFast ion conductorCathodeThin filmLithium cobalt oxideElectrochemistryBattery (electricity)ElectrodeCurrent collectorNanotechnologyElectrochemical windowChemical engineeringLithium-ion batteryIonic conductivityElectrical engineeringChemistry

Abstract

fetched live from OpenAlex

All solid state batteries are widely investigated as next generation batteries because they do not suffer from leakage, volatilization, and flammability of liquid electrolyte. Both bulk type and thin film solid batteries have attract great attention. LiCoO2 thin film has been commonly used as the cathode material for solid state batteries due to its high capacity, operating voltage and long cycle life. Because of the importance of the solid-solid interface for the performance of the battery and stability during cycling, i.e. its life time, the interface of substrate/LiCoO2 and LiCoO2/solid electrolyte during the preparation of the solid battery and possible intermediate products in the interlayer attract great attention recently. [1] The deposition parameters has a big influence on the film quality in terms of structure, morphology and electrochemical properties. In the case of layered LiCoO2, lithium-ion diffusion rely on vacancy hopping mechanism within the lithium plane, showing a predominant two dimensional path. Therefore, different orientation of lattice could influence the intercalation properties of LiCoO2 thin film deposited. [2] A primary challenge in all solid state battery is the difficulty of rapidly moving charge across solid/solid interface within the electrodes and across the electrode/electrolyte interface. The consecutive study on electrode and/or electrolyte has achieved great progress for the last decades. However, interfaces still dominate the interfacial impedance during electrochemical reaction. The optimization of interface of substrate/LiCoO2 and LiCoO2 /solid electrolyte could direct the further improvement of current all solid state batteries. Both lithium ion mobility and electrochemical reaction of LiCoO2 thin film with the solid electrolyte and the substrate are related to the interfacial resistance, which could be minimized through controlling growth orientation of LiCoO2during deposition.[3] Therefore, the ionic transportation across solid/solid interface and electrode/electrolyte interface are increased, leading to improved electrochemical performance. In this work, we optimize the deposition parameter to get high crystalline HT-LiCoO2 with hexagonal structure and good electrochemical performance firstly. Next, we study on sputtering deposition of LiCoO2 with different orientation in order to study the LiCoO2/substrate and LiCoO2/solid state electrolyte interface. The compositional (XPS), microstructural (XRD, Raman, SEM) and electrochemical properties of the sputtering LiCoO2thin films with different orientation are investigated. For the study of interface, we will adopt advanced technique to investigate the chemical/physical changes at the interface layers. Reference [1] Luntz, Alan C., et al. The journal of physical chemistry letters 6.22 (2015): 4599-4604. [2] Bates, J. B., et al. Journal of The Electrochemical Society 147.1 (2000): 59-70. [3] Yoon, Yongsub, et al. Journal of Power Sources226 (2013): 186-190.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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
Published2016
Admission routes1
Has abstractyes

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