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Record W2329571486 · doi:10.1149/ma2014-02/2/91

Use of Symmetric Cells for the Study of Na-Ion Materials and Electrolytes

2014· article· en· W2329571486 on OpenAlexaff
Timothy Hatchard, M. N. Obrovac

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrolyteElectrodeFaraday efficiencyBattery (electricity)Materials scienceIonCyclingInorganic chemistryChemistryChemical engineering

Abstract

fetched live from OpenAlex

Introduction Recent research has resulted in significant improvements in the energy density and cycle life of Na batteries. For instance, FEC electrolyte additive has shown to be beneficial for cycling hard carbon and NaNi 1/2 Mn 1/2 O 2 electrodes [1]. However, Na-ion studies have almost exclusively employed Na half-cells, in which severe dendrite and impedance growth can occur at the Na electrode during cycling [1,2]. Another disadvantage half-cells is that the counter electrode provides a huge excess of Na or Li metal, potentially masking the effects of alkali metal consuming reactions unless the coulombic efficiency (CE) is precisely measured [3]. This effect can make the working electrode appear to have long cycle life when in a full cell it would perform poorly. Recently symmetric cells have been suggested for testing the performance of Li-ion electrode materials and electrolytes [3], enabling the precise measurement of CE, cycle life and electrolyte reactions without the need for a Li metal electrode. In this study the detrimental effects of Na metal electrodes on the cycling of half-cells were confirmed. Half cells with electrolytes containing NaPF 6 or NaTFSI salts with EC/DEC 1/2 v/v were found to cycle well, while NaPF 6 or NaTFSI in PC-based electrolytes suffered from reactions with the Na electrode leading to severe capacity fade after only about 10 cycles. NaCrO 2 symmetric cells were then used to investigate the cycling performance of the same electrolytes. Electrolytes that performed poorly in half-cells were found to perform well in symmetric cells. Experimental Electrodes were an 80/10/10 weight ratio of NaCrO 2 , carbon black and PVDF on Al foil. 2325 coin-type half and symmetric cells used electrolytes comprising either EC/DEC (1:2) or PC solvent with 1M NaPF6, 1M NaTFSI or a combination of 0.7M NaTFSI and 0.3M NaPF 6 . Symmetric cells were constructed from two nominally identical NaCrO 2 electrodes, one charged to 3.5 V and the other charged to 3.5 V and then discharged to 2.0 V (vs Na/Na + ). Cells were cycled at a rate of C/10 (assuming 125 mAh/g capacity). Results and Discussion Figure 1 shows the voltage curve of a NaCrO 2 half-cell (Fig. 1a) and a NaCrO 2 symmetric cell (Fig. 1b) using 1M NaPF 6 in PC. The half-cell suffers from impedance growth and rapid capacity fade after about 20 cycles. The symmetric cell exhibits no growth in impedance and little capacity fade after 50 cycles. In this case, the half-cell results might lead one to believe that NaCrO 2 with 1M NaPF 6 in PC is a poor choice and therefore does not merit further study. However, the symmetric cell result shows this to be an excellent combination of electrode and electrolyte, achieving a CE of 99.94%. CEs of 99.97% were achieved with other conventional electrolytes with no additives. We believe these are the highest CEs for Na-ion battery materials reported so far. Electrolytes in which good cycling is achieved in half-cells may not be optimum for the working electrode. In a symmetric cell, there is no Na metal, so any capacity fade that occurs is a reflection of the working electrode performance alone. Since Na metal has proven to be much more reactive towards electrolyte than Li metal, symmetric cells are especially important for evaluating Na battery material and electrolyte performance. References. 1. S. Komaba, T. Ishikawa, N. Yabuuchi, W. Murata, A. Ito, Y. Ohsawa, ACS Applied Materials & Interfaces , 3 (11) , 4165 (2011). 2. D.A. Stevens, J.R. Dahn, Journal of The Electrochemical Society , 148 (8) , A803 (2001). 3. J.C. Burns, L.J. Krause, D.-B. Le, L.D. Jensen, a. J. Smith, D. Xiong, J.R. Dahn, Journal of The Electrochemical Society , 158 (12) , A1417 (2011).

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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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.246
Teacher spread0.223 · 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.

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
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